GeoServer Spatial Extension Geo Server WPS 1.0 User Manual En V.1.la

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Spatial Extension for GeoServer WPS v1.0 User Manual (TBD)

This manual is supported by Ministry of Land Infrastructure Transport (R&D 14NSIP-B08014401).

9 August 2016. 1st edition published
1 October 2017. 2nd edition published.

Author: Minpa Lee, Jihyun Kim
Reviewer: TBD
Cover Design: TBD
Editor: TBD

Copyright: Mangosystem(ltd.)
Publisher: Gia3D(ltd.)
Address: TBD
Tel: 042-330-0400
Fax: 042-330-0410
Publication Code: 2012-000016
ISBN: 978-89-969532-6-5(95000)

NOTICE: It is not for sale.

Copyright Notice
Copyright ⓒ 2016 MangoSystem Inc. All Rights Reserved.
Address: 2307-ho, Pyengchon O'biztower, 126, Beolmal-ro, Dongan-gu, Anyang-si, Gyeonggi-do,
431-060 South Korea
Tel: 82-31-450-3411 Fax: 82-31-450-3414
E-mail: master.mangosystem@gmail.com
Homepage: http://www.mangosystem.com
Online Documentation: http://gxt.mangosystem.com

Restricted Rights Legend
TBD

Trademarks
MangoSystem Spatial Extension for GeoServer WPS ® is belong to MangoSystem Inc. TBD.

Open Source Software Notice
TDB. It respects OSSL of “GeoTools”, “GeoServer”.


GeoTools: http://www.geotools.org



GeoServer: http://geoserver.org

User Manual Information
Title: User Manual of Spatial Extension for GeoServer WPS
Issue Date: 2016-12-31
SW Version: Spatial Extension for GeoServer WPS 1.0
User Manual Version: 1.0

목 차
1

Web Processing Service .............................................................................................................................. 6

Installation ......................................................................................................................................................... 6

Quick Start......................................................................................................................................................... 6

WPS Processes for Spatial Analysis........................................................................................................ 7
4.1.

Spatial Analysis Processes ........................................................................................................ 7

4.2.

Vector Analysis Processes ...................................................................................................... 11

4.3.

4.2.1.

Spatial Unit Creation ....................................................................................................... 11

4.2.2.

Calculation ........................................................................................................................... 35

4.2.3.

Extract .................................................................................................................................... 54

4.2.4.

Overlay................................................................................................................................... 65

4.2.5.

Proximity ............................................................................................................................... 82

4.2.6.

Aggregation ...................................................................................................................... 107

4.2.7.

Generalization .................................................................................................................. 138

4.2.8.

Editing .................................................................................................................................. 153

4.2.9.

Feature Tools .................................................................................................................... 169

Raster Analysis .......................................................................................................................... 232
4.3.1.

Descriptive ......................................................................................................................... 232

4.3.2.

Conversion ......................................................................................................................... 238

4.3.3.

Distance .............................................................................................................................. 254

4.3.4.

Math ..................................................................................................................................... 258

4.3.5.

Classification ..................................................................................................................... 264

4.3.6.

Extraction ............................................................................................................................ 267

4.3.7.

Density ................................................................................................................................. 281

4.3.8.

Interpolation ..................................................................................................................... 291

4.3.9.

Surface Analysis ............................................................................................................... 298

4.3.10. Zonal..................................................................................................................................... 310
4.3.11. Projection ........................................................................................................................... 314
4.4.

Spatial Statistics Analysis ..................................................................................................... 321
4.4.1.

Descriptive ......................................................................................................................... 321

4.4.2.

Distributions ...................................................................................................................... 333

4.4.3.

Point Pattern Analysis ................................................................................................... 350

4.4.4.

Global Spatial Auto-Correlation ............................................................................... 361

4.4.5.

Local Spatial Auto-Correlation.................................................................................. 379

4.4.6.

Global Spatial Modeling .............................................................................................. 394

1 Web Processing Service -- TBD
2 Installation -- TBD
3 Quick Start -- TBD

4 WPS Processes for Spatial Analysis
4.1. Spatial Analysis Processes
A full list of spatial analysis processes provided in Oct. 2017 is as follows.
Main

Subcategory

Process

category
Fishnet Grids by Count
Fishnet Grids by Size
Hexagonal Grids
Triangular Grids
Spatial Unit Creation

Circular Grids
Thiessen Polygon
Delaunay Triangulation polygon
Random Points
Random Points per Features
Calculate XY Coordinate
Calculate Area
Calculate Length

Calculation

Calculate Field
Calculate Count

Vector

Sum Polygon Areas

Analysis

Extract Values to Points
Select Features
Extract

Clip with Geometry
Clip with Features
Merge Features
Union
Intersect

Overlay

Symmetrical Difference
Difference
Identity
Update
Buffer Features using Expression

Proximity

Single Sided Buffer
Multiple Ring Buffer
Wedge Buffer

Near
Nearest Neighbor Count
Polar Grids from Geometry
Polar Grids from Features
Point Statistics
Aggregate Polygons
Collect Events
Spatial Join
Attribute Join
Aggregation

Buffer Point Statistics
Sum Line Lengths
Hexagonal Binning
Rectangular Binning
Circular Binning
Spatial Clump Map
Dissolve
Remove Polygon Holes

Generalization

Remove Polygon Part
Simplify
Densify
Eliminate
Reverse Line Direction
Offset Features

Editing

Snap Points To Lines
Extend Line
Trim Line
Delete Duplicated Geometries
Feature to Point
Singlepart to Multipart
Multipart to Singlepart
Feature Envelope to Polygon
Points to Line

Feature Tools

Ring Maps
Wind Rose Maps
Hub Lines by ID
Hub Lines by Nearest Distance
Feature To Line
Feature To Polygon

Feature Vertices To Points
Repair Geometry
Create Points along Line
Split Line At Point
Split Line At Vertices
Split Line By Distance Expression
Intersection Points from Lines
Feature To Octagonal Envelope
Feature To Minimum Rectangle
Feature To ConvexHull
Feature To Minimum Bounding Circle
Create Flow Map from Line Features
Descriptive

Basic Statistics
Histogram
Features To Coverage
Points To Coverage

Conversion

Geometry To Coverage
GridCoverage To Point
GridCoverage To Polygon
GridCoverage To Image

Classification

Reclass
Extract by Attributes
Conditional Expression

Raster

Extract

Analysis

Extract by Geometry
Extract by Extent
Extract by Circle
Raster Conditional Expression
Kernel Density

Density

Point Density
Line Density

Distance

Euclidean Distance

Math

Interpolation
Zonal

Inverse Distance Weighted
Thin Plate Spline
Zonal Statistics
Resample

Projection

Redefine Projection
Reproject

Raster Profile
Surface Analysis

Radial Line Of Sight
Linear Line Of Sight
Find Highest/Lowest Points
Basic Statistics

Descriptive

Pearson Correlation Coefficient
Standardized Score of Dissimilarity
Focal Location Quotients
Mean Center
Median Center

Distributions

Central Feature
Standard Distance
Standard Deviational Mean
Linear Directional Mean
Nearest Neighbor Statistic

Spatial

Point Pattern Analysis

Statistics

K-Nearest Neighbor Map
Quadrat Method
K-Means Clustering
Join Count Statistic
Moran’s I

Global Spatial Auto-Correlation

Geary’s c
Getis-Ord’s General G
Lee’s S
Lee’s L
Local Moran’s I
Local Geary’s c

Local Spatial Auto-Correlation

Local G(Gi*)
Lee’s Si
Lee’s Li

Global Spatial Modeling

Note: It will be updated continuously.

Ordinary Least Squares (OLS)

4.2. Vector Analysis Processes
These processes are for vector data analysis and processing.
4.2.1. Spatial Unit Creation
These processes are for creating various spatial analysis units like grid, hexagon,
triangular, circle, and Thissen Polygon.

4.2.1.1. Fishnet Grid by Count
Creates a Fishnet Grid based on the specified spatial extent (extent) and the number of
columns and rows (columns, rows).


Syntax

FishnetCount (ReferencedEnvelope extent, SimpleFeatureCollection boundsSource,
Boolean boundaryInside, Integer columns, Integer rows): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

extent

The extent of the grids.

Complex



boundsSource

Bounds Source Features.

Complex

boundaryInside

Bounds Inside.

Literal

columns

Number of columns.

Literal



rows

Number of Rows.

Literal



Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required



Constraints
If the boundsSource parameter is set, creates a fishnet grid only intersecting with
the boundary of boundsSource.

If the boundsSource parameter is set and the boundaryInside parameter is set to
True, creates only a fishnet grid contained within the boundary of boundsSource.



Request Examples

statistics:FishnetCount

extent

1.4111357E7 4498975.0
1.4158036E7 4537337.0

boundsSource

columns

rows

result



Response

The following figure shows an example of creating a 25 by 25 fishnet grid based on the
administrative boudary.

4.2.1.2. Fishnet Grids by Size
Creates a Fishnet Grid based on the specified spatial extent (extent) and the cell size
(width, height).


Syntax

FishnetSize (ReferencedEnvelope extent, SimpleFeatureCollection boundsSource, Boolean
boundaryInside, Double width, Double height): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

extent

The extent of the grids.

Complex



boundsSource

Bounds Source Features.

Complex

boundaryInside

Bounds Inside.

Literal

width

Width of Each Cell.

Literal



height

Height of Each Cell.

Literal



Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required



Constraints
If the boundsSource parameter is set, creates a fishnet grid only intersecting with
the boundary of boundsSource.

If the boundsSource parameter is set and the boundaryInside parameter is set to
True, creates only a fishnet grid contained within the boundary of boundsSource.



Request Examples

statistics:FishnetSize

extent

1.4111357E7 4498975.0
1.4158036E7 4537337.0

boundsSource

width

2500

height

2500

result



Response

The following figure shows an example of creating a fishnet grid of 2500×2500 meters
based on the administrative boundary (Si-Do).

4.2.1.3. Hexagonal Grids
Creates a Hexagonal Grid based on the specified spatial extent (extent) and the cell size
(sideLen).


Syntax

Hexagon (ReferencedEnvelope extent, SimpleFeatureCollection boundsSource, Double
sideLen, HexagonOrientation orientation): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

extent

The extent of the grids.

Complex



boundsSource

Bounds Source Features.

Complex

sideLen

Side length, radius.

Literal



orientation

Hexagon Orientation: FLAT (default), ANGLED.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required



Constraints
If the boundsSource parameter is set, creates hexagons only intersecting with the
boundary of the boundsSource.



The sideLen parameter defines the distance from the hexagon’s center to its edge.
Request Examples

statistics:Hexagon

extent

1.4111357E7 4498975.0
1.4158036E7 4537337.0

boundsSource

sideLen

1500

result



Response

The following figure shows an example of the choropleth map of the apartment density
calculated on the hexagonal grid with the hexagon size of 1500 meters based on the
administrative boundary.

4.2.1.4. Triangular Grids
Create a Triangular Grid based on the specified extent (extent) and the cell size (size).
Syntax



TriangularGrid (ReferencedEnvelope extent, SimpleFeatureCollection boundsSource,
Double size, HexagonOrientation orientation): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

extent

The extent of the grids.

Complex



boundsSource

Bounds Source Features.

Complex

size

Grid Size.

Literal



orientation

Orientation: FLAT (default), ANGLED.

Literal

Required



Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints


-

If the boundsSource parameter is set, creates triangular only intersecting with the
boundary of the boundsSource.





Request Examples

statistics:TriangularGrid

extent

1.4111357E7 4498975.0
1.4158036E7 4537337.0

boundsSource

size

2500

result



Response

The following figure shows

an example of creating a Triangular grid with a side length

of 2500 meter based on administrative boundary (Si-Do).

4.2.1.5. Circular Grids


Creates a Circular grid based on the specified extent (extent) and the cell size
(radius).



Syntax

CircularGrid (ReferencedEnvelope extent, SimpleFeatureCollection boundsSource, Double
radius, CircularType circularType): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

extent

The extent of the grids.

Complex



boundsSource

Bounds Source Features.

Complex

radius

Radius of the circle.

Literal



circularType

Circular Type: Grid (default), Hex.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required



Constraints
If the boundsSource parameter is set, creates circular intersecting with the
boundary of the boundsSource.

If the circularType is Grid, the rules of creating circular in grid follows the rules of
creating hexagons when the circularType is Hex.



Request Examples

statistics:CircularGrid

extent

1.4111357E7 4498975.0
1.4158036E7 4537337.0

boundsSource

radius

2500

circularType

Hex

result



Response

The following figure shows an example of creating a Circular grid with a radius of 2500
meter in both Hexagon and Grid options based on the administrative boundary (Si-Do).

4.2.1.6. Thiessen Polygon
Creates Thiessen polygon using input feature layers (inputFeatures).


Syntax

ThiessenPolygon (SimpleFeatureCollection inputFeatures, ThiessenAttributeMode
attributes, Geometry clipArea): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures
attributes
clipArea



Description
The point input features from which thiessen
polygons will be generated.
Attribute mode: ONLY_FID (default), ALL (retain input
feature’s attribute).
The clip area polygon geometry.

Type
Complex



Literal

Complex

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Required


Constraints
Though the inputFeatures can be points, lines and polygons, Thissen polygon will
be output after creating gravity center.

If the attributes parameter is All, maintains all attribute value of inputFeatures.

If the clipArea parameter is given, returns clipped polygons in the relevant areas.



Request Examples

statistics:ThiessenPolygon

inputFeatures

attributes

ALL

result



Response

The following figure showsan example of creating Thiessen Polygon within current map
boundary based on national train/subway stations.

4.2.1.7. Delaunay Triangulation Polygons
Creates Delaunay Triangulation polygons using input point feature layers (inputFeatures).
Syntax



DelaunayTriangulation (SimpleFeatureCollection inputFeatures, Geometry clipArea):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier
inputFeatures
clipArea



Description
The point input features from which delaunay
triangulations will be generated.
Clip area polygon.

Type
Complex



Complex

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required

Constraints




Required

If the clipArea parameter is given, returns clipped polygons in relevant areas.
Request Examples

statistics:DelaunayTriangulation

inputFeatures

result



Response

The following figure showsan example of creating Delaunay Triangulation Polygon using
points within some specified boundary such as the administrative boundary (Si-Do).

4.2.1.8. Random Points
Creates random points according to settings using boundary of polygon features
(polygonFeatures) or the specified Extent (extent).
Syntax



RandomPoints (ReferenceEnvelope extent, SimpleFeatureCollection polygonFeatures,
Integer pointCount): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

extent

Random points will be generated inside the extent.

Complex

Literal



Required

polygonFeatures
pointCount



The features which contains the features into which
the random points will be placed.
The number of points to be randomly generated.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints




Required

BoundingBox or polygon layers can be used as basic layers.
Request Examples

statistics:RandomPoints

polygonFeatures



pointCount

1000

result



Response

The following figure showsan example of creating 1000 random points based on the
administrative boundary (Si-Do).

4.2.1.9. Random Points per Features
Creates random point of every feature using polygon feature layers (polygonFeatures)
and expression formula (expression).
Syntax



RandomPointsPerFeatures (SimpleFeatureCollection polygonFeatures, Expression
expression): SimpleFeatureCollection
Parameters



Data Inputs

Identifier
polygonFeatures
expression



Description
The features which contains the features into which
the random points will be placed.
Field or Expression representing Number of Points.

Type

Required

Complex



Literal

Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints


-

Expression parameter can be input in numbers, fields or formulas (arithmetic
operation association between spatial and attribute fields)



Request Examples

statistics:RandomPointsPerFeatures



polygonFeatures

expression

[pop_den] / 100

result



Response

The following figure showsan example of creating random points using attribute
information of population density in the administrative boundary (Si-Gun-Gu).

4.2.2. Calculation
These processes are for calculating new values using Geometry or attribute value of
fields.

4.2.2.1. Calculate XY Coordinate
Adds X (xField) and Y (yField) field and calculates values of coordinate systems set by
users for each feature (inputFeatures).


Syntax

CalculateXYCoordinate (SimpleFeatureCollection inputFeatures, String xField, String yField,
Boolean inside, CoordinateReferenceSystem targetCRS): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The input features to be calculated.

Complex



xField

X coordinate field that will be calculated.

Literal

yField

Y coordinate field that will be calculated.

Literal

inside

Centroid(False, Default), Inside(True)

Literal

Required

targetCRS



The target coordinate reference system to use for
reprojection. Ex)epsg:4326

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required



Constraints

The inputFeatures can be points, lines, and polygons.

If the inputFeatures is polygon and the inside is set to True, center points must be
included inside the polygon.

If the targetCSR is Null, returns to coordinate value of original data, otherwise to
coordinate conversion value.



Request Examples

This is the result of returning to GML3 by loading foss:stores layer of GeoServer through
WFS and calculating values of EPSG:4326(WGS84 latitude and longitude) coordinate
system in xcoord, ycoord field.
If the inputFeatures is polygon due to the inside value is set to True, adjusted X, Y value
of the center point will be returned in order to place within the polygon.

statistics:CalculateXYCoordinate

inputFeatures

xField

xcoord

yField

ycoord

inside

True

targetCRS

EPSG:4326

result



Response

The following figure showsan example of calculating xcoord, ycoord values to
EPSG:4326(WGS84 latitude and longitude) coordinate value based on the center value of
the polygon layer.

4.2.2.2. Calculate Area
Calculates area (areaField) and perimeter (perimeterField) of polygon feature layers
(inputFeatures).


Syntax

CalculateArea (SimpleFeatureCollection inputFeatures, String areaField, String
perimeterField): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The input polygon features to be calculated.

Complex



Literal

Required

The area field that will be calculated.

areaField

geom_area is a default.

perimeterField



The perimeter field that will be calculated.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required



Constraints

InputFeatures must be polygons.

Unit of area and perimeter calculation is consistent with that of coordinate system
of inputFeatures.



Request Examples

This is the result of returning to GML format after loading foss:randomsgg layer of WFS and
calculating area and perimeter.

statistics:CalculateArea

inputFeatures

areaField

area

perimeterField

perimeter

result



Response

The following figure showsresult of calculating polygon areas in areaFeild.

4.2.2.3. Calculate Length
Adds fields to polygon or line feature layers and calculates the length (lenghFeild).
Syntax



CalculateLength (SimpleFeatureCollection inputFeatures, String lengthField):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

The input line or polygon features to be calculated.

Complex



Literal

Required

lengthField



The length field that will be calculated.
geom_len is a default.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Constraints


-

Parameter of inputFeatures must be polygon or line types.

Unit of perimeter calculation value follows that of the coordinate system.



Required

Request Examples

This is the result of returning in GML formate after loading foss:line layer of WFS and
calculating len (length of Geometry).

statistics:CalculateLength

inputFeatures

lengthField

len

result



Response

The following figure shows the result of calculating line length in len field.

4.2.2.4. Calculate Field
Calculates new field values or changes Geometry Type by using user-set expression
formula (expression).


Syntax

CalculateField (SimpleFeatureCollection inputFeatures, Expression expression, String
fieldName): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

Required

inputFeatures

The Input features to be calculated.

Complex



Literal

Required

The simple calculation expression used to create a
expression

value that will populate the selected rows.
ex) [population] / ([geom_area] / 1000000)

fieldName



The field that will be updated with the new
calculation. Evaluated is a default.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-



Constraints
If returned value through expression is Geometry, filedName is ignored and
Geometry value of returned data is applied.



Request Examples

This is the result of returning in GLM formate after calculating field value of pop_den by
loading foss:randomsgg layer of WFS and calculating population density using pop2008 (population) and
area (area([geom])).

statistics:CalculateField

inputFeatures

expression

round([pop2008] / (area( [geom] ) / 1000000))

fieldName

pop_den

result



Response

The following figure shows an example of processing mincircle ([geom]). Not only such
attribute value calculation using field arithmetic operation is possible, process of
Geometry change is also possible.



Advanced Expression

The followings are the diverse applications of expression parameter. [geom] is Geometry
field name of PostGIS, Shapefile etc.
Identifier

Expression

Return
Value

General Formula

round([pop2008] / (area( [geom] ) / 1000000))

Numeric

Area

area( [geom] )

Numeric

Perimeter/Length

geomLength( [geom] )

Numeric

X of center point

getX( centroid( [geom]))

Numeric

Polygons to lines

boundary( [geom] )

Geometry

Buffer

bufferWithSegments( [geom], 250, 16)

Polygon

Center points of gravity

centroid( [geom])

Point

Points contained within polygons

interiorPoint( [geom] )

Point

Start points of polygons or lines

startPoint( [geom] )

Point

End points of polygons or lines

endPoint( [geom])

Point

Convex Hull Convex Hull of polygons,

convexHull( [geom] )

Polygon

mincircle( [geom] )

Polygon

minimumdiameter( [geom] )

Line

minrectangle( [geom] )

Polygon

lines and multipoint
Minimum

circle

around

polygons,

lines and multipoint
Minimum radius line of the area
containing

polygons,

lines

and

multipoint
Minimum radius region containing

polygons, lines and multipoint
Least

octagonal

area

containing

octagonalenvelope( [geom] )

Polygon

offset( [geom], 4000, 3000)

Geometry

polygons, lines and multipoint
Mover by x offset, y offset

4.2.2.5. Calculate Count
Calculates feature numbers using feature layers (inputFeatures) and filters (filter).
Syntax



CountFeatures (SimpleFeatureCollection inputFeatures, Filter filter): Integer
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features to be calculated.

Complex



filter

The filter to apply

Complex



Required

Process Outputs

Identifier

Description

Type

Required

result

The number of features.

Literal



Constraints




Calculates feature numbers using layers and filters and then returns them.
Request Examples

statistics:CountFeatures

inputFeatures

filter

result



Response

Feature numbers are returned in Integer values.

4.2.2.6. Sum Polygon Areas
Calculates the sum of area of all polygon features using polygon feature layers
(inputFeatures) and filters (filter).


Syntax

SumAreas (SimpleFeatureCollection inputFeatures, Filter filter): Double


Parameters


Data Inputs

Identifier

Description

Type

Required

inputFeatures

Polygon features.

Complex



filter

The filter to apply

Complex



Process Outputs

Identifier

Description

Type

Required

result

The area of features.

Literal



Constraints




Returns to the sum of Geometry area of features using polygon layers and filters.
Request Examples

statistics:SumAreas

inputFeatures

filter

result



Response

Areas of polygon features are returned in Double values.

4.2.2.7. Extract Values to Points
Calculates cell’s digital values (valueField) of raster layers in attribute fields of points by
overlapping point features (pointFeatures) and raster layers.


Syntax

ExtractValuesToPoints (SimpleFeatureCollection pointFeatures, String valueField,
GridCoverage2D valueCoverage, ExtractionType valueType): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

pointFeatures

The input point features defining the locations.

Complex



valueField

The value field to be calculated.

Literal

valueCoverage

The gridcoverage whose values will be extracted.

Complex



Literal

Required

valueType



Extraction type: Default, SlopeAsDegree,
SlopeAsPercentrise, Aspect.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required



Constraints

If the valueField is set to Null, uses the name of evaluated field

If valueType parameter is set to Null, returns in original cell value of GridCoverage.

If valueCoverage is DEM, valueType can use SlopeAsDegree, SlopeAsPercentrise,
Aspect options.



Request Examples

statistics:ExtractValuesToPoints

pointFeatures

valueField

evaluated

valueCoverage

foss:seoul_dem30

179171.39881047895 436569.3290600816
216221.0981287582 466869.08315843146

result



Response

The following figure shows the result off calculating DEM elevation values of point data
of municipal offices.

4.2.3. Extract
These processes are for selecting or cutting features using filter or geometry.

4.2.3.1. Select Features (Query & Retype)
Selecting features by setting catalogs of fields and spatial or attributable filters (filter).


Syntax

SelectFeatures (SimpleFeatureCollection inputFeatures, Filter filter, String attributes):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

Input features to be queried.

Complex



filter

The filter to apply.

Complex

attributes

The comma separated fields list to include in output.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required



Constraints

Only feature meeting specified criteria can be selected using filter.

You can select some attribute information or change the field order by setting a
comma-separated field.



Request Examples

statistics:SelectFeatures

inputFeatures

filter

attributes

gid, geom, sgg_nm, emd_cd, emd_nm

result



Response

The following figure shows the result of selecting Gangnam-Gu in Eup-Myeon-Dong
administrative boundary data and extracting geom, sgg_nm, emd_cd, emd_nm fields.

4.2.3.2. Clip with Geometry
Sets geometry (clipGeometry) of polygons to be cut and then cuts the feature layers.
Syntax



ClipWithGeometry (SimpleFeatureCollection inputFeatures, Geometry clipGeometry):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

The features to be clipped.

Complex



Complex



clipGeometry



The polygon geometry used to clip the input
features.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints




Required

ClipGeometry must be Polygon or Multipolygon.
Request Examples

statistics:ClipWithGeometry

inputFeatures

clipGeometry

result



Response

The following figure shows the result of clipping the specified region (Geometry) in the
administrative boundary (Eup-Myeon-Dong).

4.2.3.3. Clip with Features
Sets polygon feature layers to be clipped (inputFeature) and then clips the feature layers.
Syntax



ClipWithFeatures (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection
clipFeatures): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

The features to be clipped.

Complex



clipFeatures

The features used to clip the input features.

Complex





Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints




Required

ClipGeometry must be Polygon or Multipolygon.
Request Examples

statistics:ClipWithFeatures

inputFeatures

clipFeatures

result



Response

The following figure shows an example of clipping Eup-Meyon-Dong administrative
district polygon layer using random polygon layer.

4.2.3.4. Merge Features
A few layers with the same feature type (features) merge as one layer.
Syntax



MergeFeatures (List features): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

features

Input feature collections to be merge.

Complex



Required


Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints


-

Features parameter must be the same feature type.

Since the features parameter is collection type, there is more than 1 feature layer
available and the request below is referred.

Shema of output layer is different with schema of the first layer of features
parameter.



Request Examples

statistics:MergeFeatures

features

result



Response

This is the result of mering 3 polygon layers into 1 layer.

4.2.4. Overlay
These processes are for overlay analysis between two layers such as Union, Intersect,
Symmetrical Difference, Difference, Identity, Update etc.

4.2.4.1. Union
Conducts Union Overlay analysis between two input feature layers (inputFeatures).
Output layer retains all attribute values of two features.


Syntax

Union (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection overlayFeatures):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

Input features.

Complex



overlayFeatures

Overlay features.

Complex





Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Required


Constraints
Input feature layer can be points, lines and polygons, and feature type of output
layer is the same with inputFeatures layer



Output layers contain all attribute values of inputFeatures, and overlayFeatures.
Request Examples

statistics:Union

inputFeatures

overlayFeatures

result



Response

The following figure shows the result of Union Overlay analysis between two polygon
layers. Attribute values of two layers are all contained.

4.2.4.2. Intersect
Conducts Intersect Overlay analysis between two input feature layers (inputFeatures).
Output layer retains all attribute values of two features.


Syntax

Intersect (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection
overlayFeatures): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

Input features.

Complex



overlayFeatures

Overlay features.

Complex





Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Required


Constraints
Input feature layers can be points, lines and polygons, and feature type of output
layer is the same with inputFeatures layer.



Output layers contains all attribute value of inputFeatures, and overlayFeatures.
Request Examples

statistics:Intersect

inputFeatures

overlayFeatures

result



Response

The following figure shows the result of Intersect Overlay analysis between two polygon
layers. Attribute values of two layers are all contained.

4.2.4.3. Difference
Conducts Difference Overlay analysis between two polygon feature layers
(inputFeatures).
Syntax



Difference (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection
differenceFeatures): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features.

Complex



differenceFeatures

Difference features.

Complex





Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints




Required

Feature type of input layer is the same with inputFeatures layer.
Request Examples

statistics:Difference

inputFeatures

differenceFeatures

result



Response

The following figure shows the result of Difference Overlay analysis between two
polygon layers.

4.2.4.4. Symmetrical Difference
Conducts Symmetrical Difference Overlay analysis between two polygon feature layers
(inputFeatures). Output layer retains all attribute values of two features.
Syntax



SymDifference (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection
differenceFeatures): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features.

Complex



differenceFeatures

Difference features.

Complex





Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints


-

Input layers must be polygon feature types, and the feature type of output layer is
the same with inputFeatures layer.



Output layers contains all attribute value of inputFeatures, and overlayFeatures.
Request Examples

statistics:SymDifference

inputFeatures

differenceFeatures

result



Response

The following figure shows the result of Symmetrical Difference Overlay analysis between
two polygon layers. Attribute values of two layers are all contained.

4.2.4.5. Identity
Conducts Difference Overlay analysis between two polygon feature layers
(inputFeatures).
Syntax



Identity (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection identityFeatures):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features.

Complex



identityFeatures

Identity features.

Complex





Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints


-

InputFeatures, and identityFeatures must be Polygon or MultiPolygon feature types.

Output layers contain all attribute values of inputFeatures, and overlayFeatures.



Request Examples

statistics:Identity

inputFeatures

identityFeatures

result



Response

The following figure shows the result of Identity Overlay analysis between two polygon
layers.

4.2.4.6. Update
Conducts Update Overlay analysis between two polygon feature layers (inputFeatures).
Syntax



Update (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection updateFeatures):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features.

Complex



updateFeatures

Update features.

Complex





Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints


-

InputFeatures, and identityFeatures must be Polygon or MultiPolygon feature types.

Output layers contain all attribute values of inputFeatures, and overlayFeatures.



Request Examples

statistics:Update

inputFeatures

updateFeatures

result



Response

The following figure shows the result of Identity Overlay analysis between two polygon
layers. Overlap region of Input layer and Update layer is replaced by the features of
Update layer.

4.2.5. Proximity
These processes are for distance calculation and analysis such as buffer.

4.2.5.1. Buffer Features using Expression
Conducts Buffer analysis using user-defined buffer distance (distance), buffer field or
buffer expression formula.


Syntax

BufferFeatures (SimpleFeatureCollection inputFeatures, Expression distance, int
quadrantSegments): SimpleFeatureCollection


Parameters
Data Inputs



Identifier

Description

Type

inputFeatures

The input features to be buffered.

Complex



Literal



Literal

Required

The distance expression used to create distance.

distance

Ex) 1000 or [field] or [field] * 0.5 etc...

quadrantSegments



The number of line segments used to represent a
quadrant of a circle. Default is 8.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required

Constraints

InputFeatures can be points, lines and polygons.

Distance expression can be numbers, and functions1 returned by number.



Request Examples

http://docs.geoserver.org/stable/en/user/filter/function_reference.html 참조



statistics:BufferFeatures

inputFeatures

distance

[pop_den] / 2.0) * 0.5

result



Response

The following figure shows the result of conducting buffer by using attribute values of
polygon layers and displaying the buffer distance as Expression ([pop_den] / 2.0) * 0.5).

4.2.5.2. Single Sided Buffer
Conducts One-direction Buffer analysis using user-defined buffer distance (distance),
buffer field or buffer expression formula.


Syntax

SingleSidedBuffer (SimpleFeatureCollection inputFeatures, Expression distance, Integer
quadrantSegments): SimpleFeatureCollection


Parameters
Data Inputs



Identifier

Description

Type

inputFeatures

The input features to be buffered.

Complex



Literal



Literal

Required

The distance expression used to create distance.

distance

Ex) 1000 or [field] or [field] * 0.5 etc...

quadrantSegments



The number of line segments used to represent a
quadrant of a circle. Default is 8.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required



Constraints

InputFeatures must be lines.

Distance expression can be numbers, and functions2 returned by number.

Buffer will be created on the left of line progression direction if the distance
parameter value is positive, or right if the distance parameter value is negative.



Request Examples

http://docs.geoserver.org/stable/en/user/filter/function_reference.html 참조

statistics:SingleSidedBuffer

inputFeatures

distance

250

result



Response

If the buffer distance value is positive as following, creates buffer on the left of the line
progression direction

4.2.5.3. Multiple Ring Buffer
Conducts Buffer analysis based on comma-separated buffer distance (distances).


Syntax

MultipleRingBuffer (SimpleFeatureCollection inputFeatures, String distances, Boolean
outsideOnly, Boolean dissolve): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The input features to be buffered.

Complex



Literal



Literal

Required

The comma separated list of buffer distances.

distances

Ex) 250,500,750,1000

outsideOnly

excluded from the resulting buffer. Default is True.
Determines if buffers will be dissolved to resemble

dissolve



The area inside of the input polygon features will

rings around the input features. Default is False.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required



Constraints

InputFeatures can be points, lines and polygons.

Unit of distance is the same with that of inputFeatures coordinate system.

If Dissolve parameter is true, attribute value of inputFeatures isignored and only
distance value is retained. If Dissolve parameter is false, attribute value of
inputFeatures is retained.



Request Examples

statistics:MultipleRingBuffer

inputFeatures

distances

250,500,750,1000,1250,1500

outsideOnly

True

result



Response

The following figure shows the result of processing buffer analysis with a radius of
250,500,750,1000,1250,1500 meters from municipal office point.

4.2.5.4. Wedge Buffer
Conducts Wedge Buffer analysis using point layer (pointFeatures) and attributes such as
azimuth, wedgeAngle and radius (innerRadius, outerRadius).


Syntax

WedgeBuffer (SimpleFeatureCollection pointFeatures, Expression azimuth, Expression
wedgeAngle, Expression innerRadius, Expression outerRadius): SimpleFeatureCollection


Parameters
Data Inputs



Identifier

Description

Type

pointFeatures

The point features.

Complex



Literal



Literal



Literal



The azimuth (compass direction) expression.

azimuth

Ex) 45 or [field] or [field] * 0.5 etc...

wedgeAngle
innerRadius
outerRadius



The wedge angle expression.
Ex) 45 or [field] or [field] * 0.5 etc...
The inner radius expression. The default is 0.
Ex) 25 or [field] or [field] * 0.5 etc...
The outer radius expression.
Ex) 100 or [field] or [field] * 0.5 etc...

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required

Required


Constraints

PointFeatures must be point types.

Azimuth, wedgeAngle, innerRadius, outerRadius expressions can be numbers, and
functions3 returned by number.

http://docs.geoserver.org/stable/en/user/filter/function_reference.html 참조

Lager value between innerRadius, outerRadius parameter value is used as
outerRadius value. At least one of the two values should be greater than 0.



Parameter value will be explained next.

Request Examples

statistics:WedgeBuffer

pointFeatures

azimuth

wedgeAngle

wedgeangle

innerRadius

radius1

outerRadius

radius2

result



Response

The following figure shows the result of processing Wedge buffer using attributes of
point layer.

4.2.5.5. Near (Nearest Distance & Attributes)
Calculates distances and attribute values of the neareast near features (nearFeatures) of
input feature layer (inputFeatures).


Syntax

Near (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection nearFeatures,
String nearIdField, Double maximumDistance): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

Input Features.

Complex



nearFeatures

Near Features.

Complex



nearIdField

Near ID field.

Literal

maximumDistance

Maximum distance.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required



Constraints

Unless setting nearIdField, uses inside ID of feature.

InputFeatures, nearFeatures can be points, lines and polygons, and the nearest
distance between two Geometry is calculated.

MaximumDistance is set and Null value is input when there is no feature within the
set distance.



Request Examples

statistics:Near

inputFeatures

nearFeatures

result



Response

The following figure shows the result of processing Near analysis between apartments
and municipal offices. It is calculated using the nearest distance.

4.2.5.6. Nearest Neighbor Count
Calculates number of near features (nearFeatures) inside the radius based on the input
feature layers (inputFeatures).


Syntax

NearestNeighborCount (SimpleFeatureCollection inputFeatures, String countField,
SimpleFeatureCollection nearFeatures, Double searchRadius): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

Input Features.

Complex



countField

Count field. The default is count.

Literal

nearFeatures

Near Features.

Complex



searchRadius

Search radius. Search radius must be greater than 0.

Literal





Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Required


Constraints
InputFeatures, nearFeatures can be points, lines and polygons, and the nearest
distance between two Geometry is calculated.

Unit of searchRadius parameter is the same with distance unit of inputFeatures,
which must be greater than 0.



Request Examples

statistics:NearestNeighborCount

inputFeatures

countField

pub_cnt

nearFeatures

searchRadius

500

result



Response

The following figure shows the result of graduated symbol representing the number of
points within a 500-meter radius from the main roads.

4.2.5.7. Polar Grids from Geometry
Creates polar grid based on the reference Geometry and a comma-separated radius
(radius).


Syntax

PolarGridsFromGeometry (Geometry origin, String radius, RadialType radialType, Integer
sides): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

origin

The center features of polar grids.

Complex



Literal



The list of radius(unit:data unit):

radius

Ex) 200, 300, 400, 500.

Required

radialType

Radial Type: Polar (Default), Base.

Literal

sides

The number of sides. Default is 8

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex





Constraints

Values of angle and radius of each cell in input layers are calculated.

If default value of sides parameter (8) is used, adds azimuth field, and calculates
direction value of NE, N, NW, W, SW, S, SE, E.



Request Examples

statistics:PolarGridsFromGeometry

origin

radius

500, 1000, 1500, 2000, 2500

radialType

Polar

result



Response

The following figure shows the result of creating Polar Grid with intervals of 500, 1000,
1500, 2000, 2500 meters with point (POINT (14136522.58319524 4513573.676204068)) as

the center.

4.2.5.8. Polar Grids from Features
Creates Polar grid based on the several Geometry of reference feature layers and a
comma-separated radius (radius).


Syntax

PolarGridsFromFeatures (SimpleFeatureCollection origin, String radius, RadialType
radialType, Integer sides): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

origin

The center features of polar grids.

Complex



Literal



The list of radius(unit:data unit):

radius

Ex) 200, 300, 400, 500.

Required

radialType

Radial Type: Polar (Default), Base.

Literal

sides

The number of sides.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex





Constraints

Values of angle and radius of each cell in input layers are calculated.

If default value of sides parameter (8) is used, adds azimuth field, and calculates
direction value of NE, N, NW, W, SW, S, SE, E.



Request Examples

statistics:PolarGridsFromFeatures

origin

radius

500, 1000, 1500, 2000

radialType

Polar

result



Response

The following figure shows the result of creating 8-directional Polar Grids with radius of
250,500,750,1000,1250,1500 meters from municipal offices, then calculating the number
of apartments in every cell, and mapping out.

4.2.6. Aggregation
These processes are for overlapping one or more data and calculating new values.

4.2.6.1. Point Statistics
Calculates the numbers or descriptive statistics of point layers (pointFeatures)
intersecting with the polygon layers (inputFeatures).


Syntax

PointStatistics (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection
pointFeatures, String countField, String statisticsFields): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The polygon features to be calculated.

Complex



pointFeatures

The point features to be calculated.

Complex



countField

The count field. count is a default

Literal

statisticsFields

Centroid(False, Default), Inside(True)

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required



Constraints

InputFeatures must be polygon types, and pointFeatures must be point types.

CountField stores the number of points contained within the polygons. The default
value is count.

StatisticsFields are input as [Function name, Field name] structure as follows, and
the available functions are as follows. For example, Sum.pop, Mean.pop

Input

Return field name

First: String field, Dissolve object Feature’s first value

FST_Field name

Last: String field, Dissolve object Feature’s last value

LST_ Field name

Sum: Numeric field, Dissolve object Feature’s sum value

SUM_ Field name

Mean: Numeric field, Dissolve object Feature’s mean value

AVG_ Field name

Min: Numeric field, Dissolve object Feature’s minimum value

MIN_ Field name

Max: Numeric field, Dissolve object Feature’s maximum value

MAX_ Field name

Std: Numeric field, Dissolve object Feature’s standard deviation value

STD_ Field name

Var: Numeric field, Dissolve object Feature’s variance

VAR_Field name

Range: Numeric field, Dissolve object Feature’s range

RNG_ Field name

Count: Dissolve object Feature’s number

CNT_ Field name



Request Examples

statistics:PointStatistics

polygonFeatures

pointFeatures

countField

cnt

statisticsFields

Mean.price

result



Response

The following figure shows the result of calculating and mapping the average price of
gas stations in the administrative boundary (Si-Gun-Gu).

4.2.6.2. Aggregate (Union) Polygons
Dissolves the input polygon features (polygonFeatures) and creates one polygon feature
layer.
Syntax



UnionPolygon (SimpleFeatureCollection polygonFeatures, Boolean preserveHole):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

polygonFeatures

The polygon features to be processed.

Complex



preserveHole

Preserve or remove hole (interior ring).

Literal

Required



Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints


-

If preserveHole parameter is set to false, all interior rings are returned to polygons
eliminated.





Request Examples

statistics:UnionPolygon

polygonFeatures

preserveHole

False

result



Response

If there is any InteriorRing(Hole) due to the preserveHole parameter is false, eliminates
interior rings(Hole).

4.2.6.3. Collect Events
If points have the same locations, or they are contained within a specified radius, merges
them into one feature.


Syntax

CollectEvents (SimpleFeatureCollection inputFeatures, String countField, Double tolerance):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The features representing event or incident data.

Complex



Literal

Required

countField

icount (Default).
The tolerance distance for considering two points

tolerance



The field to be calculated coincident points count.

equal.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required



Constraints

Unless setting countField, uses default value of countField.

If the tolerance value is 0, considers exactly matching points. If the tolerance value
is greater than 0, the features within the tolerance distance are regarded as the
same.



Request Examples

statistics:CollectEvents

inputFeatures

countField

icount

tolerance

result



Response

The following figure shows the result of joining all the points within a set distance into
one feature.

4.2.6.4. Spatial Join
Performs spatial join of two features based on spatial relationships. All attribute values of
two feature layers are contained.


Syntax

SpatialJoin (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection joinFeatures,
SpatialJoinType joinType, Double searchRadius): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

Input features.

Complex



joinFeatures

Join features.

Complex



joinType

Join Type. KeepAllRecord, OnlyMatchingRecord

Literal

searchRadius

Search Radius.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required



Constraints
If joinType parameter value is set to KeepAllRecord, returns all features of
inputFeatures that have not been spatial joined.

If provides searchRdius parameter, performs join with features contained within
searchRadius.



Request Examples

statistics:SpatialJoin

inputFeatures

joinFeatures

joinType

KeepAllRecord

result



Response

The following figure showsthe result of Spatial Join of information of the administrative
boundary (Si-Gun-Gu) layer containing point layer of larger markets. For point or line

layers, you can set the search radius to get the properties of nearby features.

4.2.6.5. Attribute Join
Performs join using two feature layers (inputFeatures) and join fields. All attribute values
of two feature layers are contained.
Syntax



AttributeJoin (SimpleFeatureCollection inputFeatures, String primaryKey,
SimpleFeatureCollection joinFeatures, String foreignKey, Join.Type joinType):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features.

Complex



primaryKey

Primary key field.

Literal



joinFeatures

Join features.

Complex



foreignKey

Foreign key field.

Literal



joinType

Join type. INNER, OUTER

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints




Required

If joinType is set to INNER, returns joined features of inputFeatures.
Request Examples

statistics:AttributeJoin



inputFeatures

primaryKey

sgg_cd

joinFeatures

foreignKey

sgg_cd

joinType

OUTER

result



Response

The following figure shows the result of joining large markets with join field of code of
the administrative district (Si-Gun-Gu).

4.2.6.6. Buffer Point Statistics
Inputs radius and calculates the numbers or statistics (Sum, Max, Min, Mean etc.) of
attribute information of points within the radius.


Syntax

BufferPointStatistics (SimpleFeatureCollection inputFeatures, Double distance,
SimpleFeatureCollection pointFeatures, String countField, String statisticsFields):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

Required

inputFeatures

Input features.

Complex



distance

Search distance.

Literal



pointFeatures

Point features.

Complex



countField

Count field. Default is count.

Literal

Required

Statistics Fields:
statisticsFields

Function.PropertyName(First, Last, Sum, Mean, Min,
Max, Std, Count)



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-



Constraints
CountField stores the number of points contained in the polygons. The default
value is count.

StatisticsFields are input as [Function name, Field name] structure as follows, and
the available functions are as follows. For example, Sum.pop, Mean.pop

Input

Return feild

First: String field, Dissolve object Feature’s first value

FST_Field Name

Last: String field, Dissolve object Feature’s last value

LST_ Field Name

Sum: Numeric field, Dissolve object Feature’s sum

SUM_Field Name

Mean: Numeric field, Dissolve object Feature’s mean value

AVG_ Field Name

Min: Numeric field, Dissolve object Feature’s minimum value

MIN_ Field Name

Max: Numeric field, Dissolve object Feature’s maximum value

MAX_ Field Name

Std: Numeric field, Dissolve object Feature’s standard deviation

STD_ Field Name

Var: Numeric field, Dissolve object Feature’s variance

VAR_ Field Name

Range: Numeric field, Dissolve object Feature’s range

RNG_ Field Name

Count: Dissolve object Feature’s number

CNT_ Field Name



Request Examples

statistics:BufferPointStatistics

inputFeatures

distance

2000

pointFeatures

countField

cnt

result



Response

The following figure shows the result of calculating and mapping the number of
apartments within 2000 meter of municipal office.

4.2.6.7. Sum Line Lengths
Clips the line feature layers intersecting with the polygon features (polygons) and
calculates numbers of intersecting line features and the sum of length.


Syntax

SumLineLength (SimpleFeatureCollection polygons, String lengthField, String countField,
SimpleFeatureCollection lines): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

polygons

The polygon features that will be calculated.

Complex



Literal



Literal

Complex



lengthField
countField
lines

The length field that will be calculated. sum_len is
default.
The count field that will be calculated. line_cnt is
default.
The line features that will be calculated.



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Required


Constraints
LengthField stores sum of cut length of lines intersecting with polygon features. The
default value is sum_len.

CountField stores the numbers of lines contained within the polygons. The default
value is line_cnt.



Request Examples

statistics:SumLineLength

polygons

lengthField

len

lines

result



Response

The following figure showsthe result of calculating and mapping of the extension of
main roads inthe administrative boundary (Eup-Myeon-Dong).

4.2.6.8. Spatial Clump Map
Creates Spatial Clump Map using point features (inputFeatures) and radius expressions
(radious).
Syntax



SpatialClumpMap (SimpleFeatureCollection inputFeatures, Expression radius, Integer
quadrantSegments): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features to be buffered.

Complex



Literal



Literal

The radius expression used to create distance. Ex)

radius

1000 or [field] or [field] * 0.5 etc...

quadrantSegments



The number of line segments used to represent a
quadrant of a circle. Default is 8.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints




Required

The default value of quatrantSegments parameter is 8.
Request Examples

statistics:SpatialClumpMap

inputFeatures

radius

5000

result



Response

The following figure showsthe result of Spatial Clump Map by setting the radius as 5Km.

4.2.6.9. Hexagonal Binning
Creates Hexagon grid using point features (features), extents, and radius and then
creates polygon features counting for the numbers of points in each cell.


Syntax

HexagonalBinning (SimpleFeatureCollection features, Expression weight,
ReferencedEnvelope bbox, Double size, Boolean validGrid): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

features

Input point features to be aggregated.

Complex



Literal

The numeric field or expression used to weight

weight

values. Ex) [field] or [field] * 0.5 etc...

Required

bbox

The extent of the grids.

Complex

size

Size of the grids.

Literal



validGrid

Returns only valid grid. Default is True.

Literal



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

If bbox is set to Null, extent of feature data is used.

If gives weight expression, accumulates weight values.

Size must be greater than 0.

Default value of validGrid parameter is true, and only the grid of which number is
more than 0 is returned.



Request Examples

statistics:HexagonalBinning

features

size

1500

result



Response

The following figure showsthe result of creating and visualizing of hexagons with a size
of 1000 meters created from apartment point data of Seoul.

4.2.6.10.

Rectangular Binning

Creates rectangle grids using point features (features), extent (bbox), and radius (width,
height) and then creates polygon features counting for the number of points in each cell.


Syntax

RectangularBinning (SimpleFeatureCollection features, Expression weight,
ReferencedEnvelope bbox, Double width, Double height, Boolean validGrid):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

features

Input point features to be aggregated.

Complex



Literal

The numeric field or expression used to weight

weight

values. Ex) [field] or [field] * 0.5 etc...

Required

bbox

The extent of the grids.

Complex

width

Width of the grids.

Literal



height

Height of the grids.

Literal



validGrid

Returns only valid grid. Default is True.

Literal



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

If bbox is set to Null, uses extent of feature data.

If gives weight expression, accumulates weight values.

Width, height must be greater than 0.

Default value of validGrid parameter is true, and only the grids of which number is
more than 0 are returned.



Request Examples

statistics:RectangularBinning

features

width

1500

height

1500

result



Response

The following figure shows the result of creating and visualizing of rectangles with a
side length of 1500 meters created from apartment point data of Seoul.

4.2.6.11.

Circular Binning

Creates circle grids using point features (features), extent (bbox), radius (radius) and
then creates polygon features counting for the number of points in each cell.


Syntax

CircularBinning (SimpleFeatureCollection features, Expression weight, ReferencedEnvelope
bbox, Double radius, Boolean validGrid): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

features

Input point features to be aggregated.

Complex



Literal

The numeric field or expression used to weight

weight

values. Ex) [field] or [field] * 0.5 etc...

Required

bbox

The extent of the grids.

Complex

radius

Radiuss of the grids.

Literal



validGrid

Returns only valid grid. Default is True.

Literal



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

If bbox is set to Null, uses extent of feature data.

If gives weight expression, accumulates weight values.

Radius must be greater than 0.

Default value of validGrid parameter is true, and only the grids of which numbers
are more than 0 are returned.



Request Examples

statistics:CircularBinning

features

radius

750

result



Response

The following figure showsthe result of creating and visualizing of circles with a radius of
750 meters created from apartment point data of Seoul.

4.2.7. Generalization
These processes are for generalization such as Dissolve, Simplification etc.

4.2.7.1. Dissolve
Performs Dissolve analysis using attribute fields of feature layers (inputFeatures) and
aggregate functions.


Syntax

Dissolve (SimpleFeatureCollection inputFeatures, String dissolveField, String
statisticsFields, Boolean useMultiPart): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

Required

inputFeatures

Input features.

Complex



dissolveField

The field on which to dissolve features.

Literal



Literal

Required

The fields and statistics with which to summarize
statisticsFields

attributes.
Statistics fields(Function.PropertyName): First, Last,
Sum, Mean, Min, Max, Std, Count.

useMultiPart



Specifies whether multipart features are allowed in
the output features.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex





Constraints

If useMultiPart is set to False, converts and returns dissolved features in Single Part.

StatisticsFields are input as [Function name, Field name] structure as follows, and
the available functions are as follows. For example, Sum.pop, Mean.pop

Input

Return feild

First: String field, Dissolve object Feature’s first value

FST_Field Name

Last: String field, Dissolve object Feature’s last value

LST_ Field Name

Sum: Numeric field, Dissolve object Feature’s sum

SUM_Field Name

Mean: Numeric field, Dissolve object Feature’s mean value

AVG_ Field Name

Min: Numeric field, Dissolve object Feature’s minimum value

MIN_ Field Name

Max: Numeric field, Dissolve object Feature’s maximum value

MAX_ Field Name

Std: Numeric field, Dissolve object Feature’s standard deviation

STD_ Field Name

Var: Numeric field, Dissolve object Feature’s variance

VAR_ Field Name

Range: Numeric field, Dissolve object Feature’s range

RNG_ Field Name

Count: Dissolve object Feature’s number

CNT_ Field Name



Request Examples

statistics:Dissolve

inputFeatures

dissolveField

sgg_nm

statisticsFields

fst.sid_nm,sum.pop2007,sum.pop2008,sum.pts

result



Response

The following figure shows the result of setting Si-Gun-Gu name (sgg_nm) fields of the
administrative boundary (Eup-Myeon-Dong) and aggregated fields of fst.sid_nm,
sum.pop2007, sum.pop2008, sum.pts and then conducting Dissolve.

4.2.7.2. Remove Polygon Holes
Eliminates all holes (Interior Rings) of polygon feature layers (inputFeatures) or holes
smaller than the set size (minimumArea).


Syntax

RemoveHoles (SimpleFeatureCollection inputFeatures, Expression minimumArea):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The polygon features to be removed.

Complex



Literal

Required

minimumArea



Remove holes smaller than this area expression.
Ex) 10.0 or filter expression.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required



Constraints
MinimumArea combines numbers or field values and expressions of returning in
numbers are available.

If minimumArea parameter value is set to 0, eliminates all holes (Interior Ring) of
polygons, and if the value is greater than 0, eliminates Hole with area smaller than
the set values.



Request Examples

statistics:RemoveHoles

inputFeatures

minimumArea

1000

result



Response

The following figure showsan example of eliminating holes from polygons with Interior
Ring (Hole).



4.2.7.3. Remove Polygon Part
Leaves only the parts smaller than the set size or the parts with the largest area with
removing all others in the polygon feature layers consisting of Multipart Geometry.


Syntax

RemoveParts (SimpleFeatureCollection inputFeatures, Expression minimumArea):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

Required

inputFeatures

The polygon features to be removed.

Complex



Literal

Required

Remove polygon parts smaller than this area
minimumArea

expression.
ex) 10.0 or filter expression.



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-



Constraints
MinimumArea combines numbers or field values and expressions of returning in
numbers are available.

If minimumArea parameter value is set to 0, eliminates all holes (Interior Ring) of
polygons, and if the value is greater than 0, eliminates holes with area smaller than
the set value.



Request Examples

statistics:RemoveParts

inputFeatures

result



Response

The following figure shows an example of eliminating polygons less than the specified
area in MultiPolygon. All of the islands with small areas are eliminated, as shown in
figure.

4.2.7.4. Simplify
Simplifies polygon or line features using Douglas-Peucker simplifying algorithm.


Syntax

Simplify (SimpleFeatureCollection inputFeatures, Expression tolerance, Boolean
preserveTopology): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The input line or polygon features to be simplified.

Complex



Literal



Literal

Required

Distance tolerance to simplify ex) 10.0 or filter

tolerance

expression.

preserveTopology



If True, ensures that simplified features are
topologically valid. Default is True

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required



Constraints
Tolerance parameter can use numbers and functions, and Douglas–Peucker
algorithm is used.

If the preserveTopology parameter is set to True, maintains minimum topology rule
regardless of the Tolerance value.



Request Examples

statistics:Simplify

inputFeatures

tolerance

result



Response
The blue line is the original, and the red line is the result of Simplifying.

4.2.7.5. Densify
Adds vertices with set tolerance (tolerance) interval in every line segment of polygon or
line features.
Syntax



Densify (SimpleFeatureCollection inputFeatures, Expression tolerance):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

The input line or polygon features to be calculated.

Complex



Literal



Required

Distance tolerance to densify ex) 10.0 or filter

tolerance



expression.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints




Required

Tolerance parameter can use numbers and functions.
Request Examples

statistics:Densify

inputFeatures



tolerance

250

result



Response

The following figure shows the result of conducting Densify with a 250-meter interval in
the original lines composed with start points and end points. The blue ones are the
original vertices, and the red ones are the added vertices.

4.2.7.6. Eliminate
Removes the Sliver polygon based on the shared area or length of the neighbor
polygons.


Syntax

Eliminate (SimpleFeatureCollection inputFeatures, EliminateOption option, Filter
exception): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures

The layer whose polygons will be merged into
neighboring polygons.
The options specify which method will be used for

option

eliminating features.

exception



Description

The exception filter used to identify features that will
not be altered.

Type
Complex



Literal

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required

Required


Constraints

InputFeatures layers must be polygon types.

The option parameter incorporates the Sliver polygons with the largest shared
length (Length), the largest area (SmallArea), or the smallest neighbor (SmallArea)
based on the basis of eliminating Sliver polygons..



Exception parameter sets features excluded from processing as filters.
Request Examples

statistics:Eliminate

inputFeatures

option

Length

result



Response

The following figure shows the original feature and result of eliminating Sliver polygon
based on the shared length in the origin layer containing Sliver polygon.

4.2.8. Editing
These processes are for simplification such as Dissolve, Simplification etc.

4.2.8.1. Reverse Line Direction
-

Changes the vertex order of line feature layers (lineFeatures).
Syntax



FlipLine (SimpleFeatureCollection lineFeatures): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

lineFeatures

The input line features.

Complex





Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints




Required

LineFeature parameter must be line layer.
Request Examples

statistics:FlipLine

lineFeatures

result



Response

The following figure shows the original (red) line data and converted result (blue) data.

4.2.8.2. Offset Features
Moves all features of feature layers (inputFeatures) by x, y offsets (offsetX, offsetY).


Syntax

OffsetFeatures (SimpleFeatureCollection inputFeatures, Double offsetX, Double offsetY):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures

Description
Input features that can be multipoint, line, and
polygon.

Type

Required

Complex



offsetX

X offset.

Literal

offsetY

Y offset.

Literal



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required


Constraints
Based on the original locations, moves to right if offsetX is positive, left if negative,
up if offsetY value is positive, and down if negative.



Request Examples

statistics:OffsetFeatures

inputFeatures

offsetX

500

offsetY

500

result



Response

The following figure shows the result of moving the original layer by 500 meters on the
X axis and 500 meters on the Y axis.

4.2.8.3. Snap Points To Lines
Moves to the nearest line or polygon boundaries (lineFeatures) based on the feature
snap distance of the point layers (pointFeatures).


Syntax

SnapPointsToLines (SimpleFeatureCollection pointFeatures, SimpleFeatureCollection
lineFeatures, Double tolerance): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

pointFeatures

Point features to be snapped.

Complex



lineFeatures

Line features that can be Line or polygon boundary.

Complex



Literal

Snap tolerance. If tolerance is 0, nearest line feature

tolerance



will be used.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required

Required


Constraints

LineFeatures layers must be line or polygon types.

If tolerance parameter is 0, moves to the nearest line features, anduses the distance
unit of pointFeatures.



Request Examples

statistics:SnapPointsToLines

pointFeatures

lineFeatures

result



Response

The following figure shows the result of snapping points near roads to the nearest roads
(line).

4.2.8.4. Extend Line
Extends the features of the line layers (lineFeatures) to the intersection of the first
intersecting line within a specified distance (length).


Syntax

ExtendLine (SimpleFeatureCollection lineFeatures, Double length, Boolean extendTo):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

lineFeatures

The line features to be extended.

Complex



Literal



Literal

The maximum distance a line segment can be

length

extended to an intersecting feature.

Required

Controls whether line segments can be extended to
extendTo

other extended line segments within the specified
extend length.



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

LineFeatures layer must be line type.

Length parameter is the maximum distance that a line segment can extend to, and
uses the distance units of lineFeatures.



If the extendTo parameter is set to True, extends all segments by length.
Request Examples

statistics:ExtendLine

lineFeatures

length

2000

extendTo

True

result



Response

The following figures shows the result of extending line by specified distance.

4.2.8.5. Trim Line
Trims the features in the line layers (lineFeatures) that is shorter than a specified length
(dangleLength) and do not intersect with other lines at start/end points.


Syntax

TrimLine (SimpleFeatureCollection lineFeatures, Double dangleLength, Boolean
deleteShort): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

Required

lineFeatures

The line features to be trimmed.

Complex



Literal



Literal

Line segments that are shorter than the specified
dangleLength

Dangle Length and do not touch another line at
both endpoints (dangles) will be trimmed.
Controls whether line segments which are less than

deleteShort

the dangle length and are free-standing will be
deleted. Default is True.



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

LineFeatures layer must be line type.

If deleteShort parameter is set to True and the length of an independent line not
intersecting with other lines at start/end points is less than the length of
dangleLength, eliminates this line.



Request Examples

statistics:TrimLine

lineFeatures

dangleLength

1700

deleteShort

True

result



Response

The following figure shows the result of trimming segment smaller than specified
length.

4.2.8.6. Delete Duplicated Features
Leaves only one feature with the same Geometry in the feature layers (inputFeatures)
and deletes others.
Syntax



DeleteDuplicates (inputFeatures SimpleFeatureCollection): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

The input features to be processed.

Complex



Required


Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required

Constraints


-

InputFeatures can be points, lines and polygons. Only features with the same
Geometry are seen as duplicated.



Request Examples

statistics:DeleteDuplicates

inputFeatures

result



Response

Among duplicated points, only one feature is stored, as shown as follows.

4.2.9. Feature Tools
These processes are for conversions such as Geometry type conversion, and format
conversion.

4.2.9.1. Feature to Point
Converts feature layers (inputFeatures) into point feature layers such as center points
and so on.


Syntax

FeatureToPoint (SimpleFeatureCollection inputFeatures, Boolean inside, Boolean
singlePart): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures

Description
The input features that can be multipoint, line,
polygon.

Type

Required

Complex



inside

Centroid(False), Inside(True, Default)

Literal

singlePart

Centroid of each part. Default is False

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex





Constraints

InputFeatures can be points, lines and polygons.

If the inputFeatures is polygon and inside is set to True, the center point is
contained within the polygon.

If singlePart is set to True and geometry is MultiPart, converts geometry of all parts
into cenert points.



Request Examples

statistics:FeatureToPoint

inputFeatures

inside

True

singlePart

False

result



Response

The following figure shows the situation that the inside parameter is True and singlePart
parameter is True. If it is MultiPolygon, it is converted into one center point.

This is the situation that inside parameter is set to True and singlePart parameter is set
to False. If it is MultiPolygon, it is converted into center points by the number of
polygons.

4.2.9.2. Multipart to Singlepart
Converts feature layers (inputFeatures) that configured with MultiPart into that with
SinglePart.
Syntax



MultipartToSinglepart (SimpleFeatureCollection inputFeatures): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features that can be any feature type.

Complex



Required


Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required

Constraints


-

InputFeatures parameter must be Multipart (MultiPoint, MultiLineString,
MultiPolygon) feature types.



Request Examples

statistics:MultipartToSinglepart

inputFeatures

result



Response

The following figure shows the result of converting MultiPolygon configured with more
than 2 polygons into single polygon.



4.2.9.3. Singlepart to Multipart
Converts feature layers (inputFeatures) that configured with SinglePart into that with
MultiPart based on attribute values.
Syntax



SinglepartToMultipart (SimpleFeatureCollection inputFeatures, String caseField, Boolean
dissolve): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features that can be point, line, polygon.

Complex



caseField

The field on which to aggregate features.

Literal



Literal

Required

If true, neighborhood features are dissolved. Default

dissolve



is False

Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints


-

If dissolve parameter is set to True, returns in geometry that dissolves the adjacent
polygons or lines.





Request Examples

statistics:SinglepartToMultipart

inputFeatures

caseField

sgg_nm

result



Response

The following figure shows an example of converting layer configured with single
polygon back into MultiPolygon based on the name of the administrative doundary (SiGun-Gu).



4.2.9.4. Feature Envelope to Polygon
Converts the minimum boundary area for each feature in the feature layer to a polygon
feature layer.
Syntax



FeatureEnvelopeToPolygon (SimpleFeatureCollection inputFeatures, Boolean
singleEnvelope): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

Required

inputFeatures

Input features that can be multipoint, line, polygon.

Complex



Literal

Required

Specifies whether to use one envelope for each entire
singleEnvelope

multipart feature or one envelope per part of a
multipart feature. Default is True



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Constraints


-

If singleEnvelope is set to False and the geometry of each feature is MultiLineString
or MultiPolygon, converts to Single Part and returns Envelope polygon for each
geometry.



Request Examples

statistics:FeatureEnvelopeToPolygon

inputFeatures

singleEnvelope

False

result



Response

The following figure showsthe result of converting Envelopes of polygon feature
geometry to polygons.

Minimum bounding Envelope surrounding the polygon can be get using the [Calculate
Field] function.

4.2.9.5. Points to Line
Sets line field (lineField) and aligned field value in the point feature layer (inputField)
and converts into line or polygon layers.


Syntax

PointsToLine (SimpleFeatureCollection inputFeatures, String lineField, String sortField,
Boolean closeLine): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The point features to be converted into lines.

Complex



Literal

Each feature in the output will be based on unique

lineField

values in the Line Field.

Required

By default, points used to create each output line
sortField

feature will be used in the order they are found. If a
different order is desired, specify a Sort Field.
Specifies whether output line features should be

closeLine



closed. Default is False.

Literal

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required


Constraints
If sets lineField parameter, lines are created separately according to the unique
value of lineField.

If sets sortField parameter, lines are created using points aligned to sortField.

If the closeLine parameter is set to True, creates polygons by linking the start point
with the end point.



Request Examples

statistics:PointsToLine

inputFeatures

lineField

cat

sortField

closeLine

False

result



Response

The following figure shows the result of converting all points including the category and
serial number to lines. The lines are created according to the serial number sequence
and consist of two categories.

Polygon is created when closeLine is set to True in the example above.

4.2.9.6. Ring Maps
Creates a Ring Map by setting the property fields (fields) or the numbers of rings
separated by a comma of the feature layers (inputFeatures).


Syntax

RingMap (SimpleFeatureCollection inputFeatures, String fields, String targetField, Integer
ringGap): [SimpleFeatureCollection, SimpleFeatureCollection]


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

Input features that can be point, line, and polygon.

Complex



fields

Comma separated field or ring count.

Literal



targetField

Output ring value field. ring_val is default.

Literal

ringGap

Gap of rings.

Literal

Required



Required

Process Outputs

Identifier

Description

Type

anchor

Anchor features.

Complex



ringmap

Ring map features.

Complex




-

Constraints
The fields parameter uses the number of consecutive fields or numbers of rings,
such as a comma-separated yearly time series field.

If targetField is set to Null, Ring_val field is the default value.

RingGap parameter ranges from 1~9, and 1 is the default value.

Output returns to two layers of ringmap polygons that created by the anchor line
and the ring map displaying the leader lines.



Request Examples

statistics:RingMap

inputFeatures

fields

a3_2000,a3_2001,a3_2002,a3_2003,a3_2004,a3_2005

targetField

ring_val

anchor

ringmap



Response

The following figure showsthe result of creating the Ring Map using the natural
population growth rate from 2000 to 2005 in Seoul.

4.2.9.7. Wind Rose Maps
Creates a Wind Rose Map by setting the point feature layer and center point.


Syntax

WindRoseMap (SimpleFeatureCollection inputFeatures, String weightField, Geometry
center): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

Input features that can be point, line, and polygon.

Complex



weightField

Weight field.

Literal

center

Center (geometry) of wind rose.

Complex



Required

Process Outputs

Identifier

Description

Type

anchor

anchor features.

Complex



windRose

Wind rose features.

Complex




-

Required

Constraints
The weightField parameter must be a Numeric field. If sets the parameter, the sum
of these field values is reflected in the result, otherwise the number of features is
reflected.

Output returns the anchor line and the windrose polygon layers to display the
leader lines.



Request Examples

statistics:WindRoseMap

inputFeatures

center

anchor

windRose



Response

The following figure showsthe result of creating Wind Rose Map using distribution of
apartments with Seoul City Hall as the center.

4.2.9.8. Hub Lines by ID
Creates a shortest distance of Hub line feature layers (hubFeatures) using the Join field
of the Hub feature layers (hubIdFeild) and the Spoke feature layers (spokeIdFeild).


Syntax

HubLinesByID (SimpleFeatureCollection hubFeatures, String hubIdField,
SimpleFeatureCollection spokeFeatures, String spokeIdField, Boolean preserveAttributes,
Boolean useCentroid, Boolean useBezierCurve, Double maximumDistance):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

hubFeatures

Hub Features.

Complex



hubIdField

Hub id field.

Literal



spokeFeatures

Spoke Features.

Complex



spokeIdField

Spoke id field.

Literal



preserveAttributes

Preserve spoke feature's attributes. Default is True

Literal

useCentroid

Use centroid of feature. Default is True

Literal

useBezierCurve

Use Bezier Curve. Defautl is False.

Literal

maximumDistance

Maximum distance.

Literal



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Required


Constraints
If the useCentroid parameter is set to True and the geometry feature types of
hubFeatures, spokeFeatures are line or polygon layers, creates the hub line using
centroid of geometry.

If the useBezierCurve parameter is set to True, creates the Bezier curve with the
shortest line between the two features.

If the maximumDistance parameter is greater than 0, creates a hub line only for
features within this distance



Request Examples

statistics:HubLinesByID

hubFeatures

hubIdField

sgg_nm

spokeFeatures

spokeIdField

sgg_nm

preserveAttributes

True

useCentroid

True

result



Response

The following figure showsthe result of setting the city municipal offices as the hubs,
setting the Eup-Myeon-Dong district polygon as a spoke layer, and creating the hub
lines based on the Si-Gun-Gu administrative district code.

4.2.9.9. Hub Lines by Nearest Distance
Creates a hub line feature layer between the closest hub features (hubFeatures) in the
spoke features (spokeFeatures), using the hub feature layers and the spoke feature
layers.


Syntax

HubLinesByDistance (SimpleFeatureCollection spokeFeatures, SimpleFeatureCollection
hubFeatures, String hubIdField, Boolean preserveAttributes, Boolean useCentroid, Boolean
useBezierCurve, Double maximumDistance): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

spokeFeatures

Spoke Features.

Complex



hubFeatures

Hub Features.

Literal



hubIdField

Hub id field.

Literal

preserveAttributes

Preserve spoke feature's attributes. Default is True

Literal

useCentroid

Use centroid of feature. Default is True

Literal

useBezierCurve

Use Bezier Curve. Defautl is False.

Literal

maximumDistance

Maximum distance.

Literal



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Required


Constraints
If the useCentroid parameter is set to True and the geometry feature types of
hubFeatures, spokeFeatures are lines or polygons, creates the hub lines using
centroid of geometry.

If the useBezierCurve parameter is set to True, creates the Bezier curve with the
shortest line between the two features.

If the maximumDistance parameter is greater than 0, creates a hub line only for
features within set distance



Request Examples

statistics:HubLinesByDistance

spokeFeatures

hubFeatures

preserveAttributes

True

useCentroid

True

result



Response

The following figure showsthe result of connecting the nearest apartments of the
municipal offices by setting the municipal offices as the hubs and the apartment
distribution as the spoke. It will be placed in the same area as Thiessen Polygon as
shown in the following figure.

If uses the Bezier curve option, creates line layers as curves as follows.

4.2.9.10.

Feature To Line

Creates line layers divided by the nodes that intersect with the polygon or line layers.
Syntax



FeatureToLine (SimpleFeatureCollection inputFeatures, Boolean preserveAttributes):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

The input features that can be line or polygon.

Complex



Literal

preserveAttributes



Specifies whether to preserve or omit the input
attributes in the output features. Default is True.

Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required


Constraints


-

The inputFeature layers must be line or polygon types.

Default value of the preserveAttributes parameter is True, and if it is set to true,
retains the property values of the original features.



Request Examples

statistics:FeatureToLine

inputFeatures

preserveAttributes

True

result



Response

The following figure shows the result of converting the polygon layers to line layers.
The converted lines are divided into segments that share polygons as shown in the
following figure.

4.2.9.11.

Feature To Polygon

Creates polygon layers using polygon or line layers (inputFeatures).


Syntax

FeatureToPolygon (SimpleFeatureCollection inputFeatures, Double tolerance,
SimpleFeatureCollection labelFeatures): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

Required

inputFeatures

The input features that can be line or polygon.

Complex



tolerance

Tolerance. The default is 0.001 feature unit.

Literal

Complex

The optional input point features that hold the
labelFeatures

attributes to be transferred to the output polygon
features.



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

The inputFeatures layers must be line or polygon layer types.

Default value of the tolerance parameter is 0.001, and the units of the inputFeatures
coordinate system.

The labelFeatures layers must be point layer types.

If the labelFeatures parameter is not Null, uses this schema and assign the attribute
values of the labelFeatures points contained in the polygon after polygon
generation.



Request Examples

statistics:FeatureToPolygon

inputFeatures

tolerance

0.001

result



Response

The following figure shows the result of converting the line layers to polygon layers.

4.2.9.12.

Feature Vertices to Points

Creates point feature layers based on the set vertex position (location)using polygon or
line data (inputFeatures).


Syntax

VerticesToPoints (SimpleFeatureCollection inputFeatures, PointLocationType location):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The input features that can be line or polygon.

Complex



Literal

Specifies where an output point will be created.

location



Default is All

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

The inputFeatures parameter must be line or polygon layers.

The location parameter has the following five options.

Options

Description

All

All vertices of line or polygon geometry, Default value.

Mid

Midpoint of line or polygon geometry

Start

Starting point of line or polygon geometry.

End

Endpoint of line or polygon geometry.

BothEnds

Starting and ending points of the line or polygon geometry.



Required

Request Examples

statistics:VerticesToPoints

inputFeatures

location

Mid

result



Response

The following figure showsthe result of converting the Mid(midpoint) of the line features
to points.

4.2.9.13.

Repair Geometry

Modifies the errors after validating the geometry of each feature in the feature layers
(inputFeatures).
Syntax



RepairGeometry (inputFeatures SimpleFeatureCollection): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features that will be repaired.

Complex





Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Required

Constraints


-

Checks null geometry and self-intersection

Validates coordinates

Removes empty shell/holes and duplicated vertices/points



Required

Request Examples

statistics:RepairGeometry

inputFeatures



result


-

Response
None

4.2.9.14.

Create Points along Line

Creating point feature layers with a constant distance (distance) as interval using
polygon or line data (lineFeatures).
Syntax



PointsAlongLines (SimpleFeatureCollection lineFeatures, Expression distance):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier
lineFeatures
distance



Description
The line or polygon features to be converted into
points.
Field or Expression representing distance.

Type

Required

Complex



Literal



Process Outputs

Identifier

Description

Type

result

Output point features.

Complex

Required


Constraints


-

The inputFeatures parameter must be line or polygon layers.

The distance parameter can use the fields or the Function Expression formula.



Request Examples

statistics:PointsAlongLines

lineFeatures

distance

geomLength( [geom] ) / 5

result



Response

The following figure shows the result of creating points at 1/5 of the line length.

4.2.9.15.

Split Line at Point

Splits the line feature layers (lineFeatures) into point feature layers (pointFeatures).


Syntax

SplitLineAtPoint (SimpleFeatureCollection lineFeatures, SimpleFeatureCollection
pointFeatures, Double tolerance): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

lineFeatures

The line features to be splitted.

Complex



Complex



Literal

pointFeatures

split the line features.
Search radius. If tolerance is 0, the nearest point will

tolerance



The point features whose locations will be used to

be used to split the line feature.

Process Outputs

Identifier

Description

Type

result

Output line features.

Complex



Required

Required


Constraints

The inputFeatures parameter must be line feature types.

If the tolerance parameter is 0, all points that intersect with each line feature are
used; if there are no intersecting point features, the closest point feature is used for
line splitting.

If the tolerance parameter is greater than or equal to 0, all point features within the
search radius are used for partitioning.



Request Examples

statistics:SplitLineAtPoint

lineFeatures

pointFeatures

tolerance

result



Response

The following figure shows the result of splitting the line layers into point layers.

4.2.9.16.

Split Line at Vertices

Creates line feature layers (lineFeatures) divided by vertices.
Syntax



SplitLineAtVertices (SimpleFeatureCollection lineFeatures): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

lineFeatures

The line or polygon features that will be splitted.

Complex





Process Outputs

Identifier

Description

Type

result

Output line features.

Complex

Required


Constraints




Required

The inputFeatures parameter must be line or polygon layer types.
Request Examples

statistics:SplitLineAtVertices

lineFeatures

result



Response

The following figure showsthe result of converting the boundary of polygon features to
the line feature vertex by vertex.

4.2.9.17.

Split Line by Distance Expression

Creates line feature layers (lineFeatures) divided by the set distance (distance).
Syntax



SplitLineByDistance (SimpleFeatureCollection lineFeatures, Expression distance):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

lineFeatures

The line features that will be splitted.

Complex



distance

Field or Expression representing distance.

Literal





Required

Process Outputs

Identifier

Description

Type

result

Output line features.

Complex



Constraints


-

The inputFeatures parameter must be line or polygon layer types.

The distance parameter can use the fields or function expression formula.



Required

Request Examples

statistics:SplitLineByDistance

lineFeatures

distance

100

result



Response

The following figure showsthe result of dividing boundaries of polygon features into lines
with an interval of 100 meters.

4.2.9.18.

Intersection Points from Lines

Converts the nodes (intersectFeatures) where each line intersects in the two input
polygon or line feature layers (inputFeatures) to points.


Syntax

IntersectionPoints (SimpleFeatureCollection inputFeatures, SimpleFeatureCollection
intersectFeatures, String intersectIDField): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

Input features that can be line or polygon type.

Complex



intersectFeatures

Intersect that can be line or polygon type.

Complex



intersectIDField

Intersect id field.

Literal



Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Required


Constraints
InputFeatures and intersectFeatures feature layers can be set both line and
polygon.

The output layers contain all field values of inputFeatures. If intersectIDField is set,
adds the value of intersectFearures.



Request Examples

statistics:IntersectionPoints

inputFeatures

intersectFeatures

result



Response

The following figure showsthe result of analysis between polygon and line feature layers.

4.2.9.19.

Create Flow Map from Line Features

Creates Polygon Flow Map feature layers using line feature layers (lineFeatures)
consisting of Origin-Destination and attribute values (odValue, doValue) of it.


Syntax

FlowMap (SimpleFeatureCollection lineFeatures, Expression odValue, Expression doValue,
Double maxSize): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

lineFeatures

The input line features.

Complex



Literal



Literal

The o-d value expression.

odValue

Ex) [field] or [field] * 0.5 etc...
The d-o value expression.

doValue

Ex) [field] or [field] * 0.5 etc...

maxSize



The maximum arrow size.

Process Outputs

Identifier

Description

Type

result

Output polygon features.

Complex



Required

Required


Constraints

The lineFeatures parameter must be line layers.

If the maxSize parameter is Null or 0, uses the value of dividing the smaller one
between the width and height of the extents of the lineFeatures by 20.



Request Examples

statistics:FlowMap

lineFeatures

odValue

o_d

maxSize

2500

result



Response

The following figure shows the result of generating the Flow Map using the population
moving data of Seoul Gu-administrative district.

4.2.9.20.

Feature To Octagonal Envelope

Converts each feature into the minimum bounding octagonal polygon that surrounds
each feature in the feature layers (inputFeatures).


Syntax

FeatureToOctagonalEnvelope (SimpleFeatureCollection inputFeatures, Boolean singlePart):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures

Description
The input features that can be multipoint, line,
polygon.

Type

Required

Complex



Literal

Specifies whether to use one circle for each entire
singlePart

multipart feature or one circle per part of a multipart
feature.



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

The inputFeatures can be points, lines, and polygons.

If singlePart is set to True and the geometry is MultiPart, converts the geometry of
all parts.



Request Examples

statistics: FeatureToOctagonalEnvelope

inputFeatures

result



Response

The following figure shows the result of converting the polygon features to the minimum
bounding octagonal polygons.

4.2.9.21.

Feature To Minimum Rectangle

Converts each feature into the minimum bounding rectangle polygon that surrounds
each feature in the feature layers (inputFeatures).


Syntax

FeatureToMinimumRectangle (SimpleFeatureCollection inputFeatures, Boolean singlePart):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures

Description
The input features that can be multipoint, line,
polygon.

Type

Required

Complex



Literal

Specifies whether to use one circle for each entire
singlePart

multipart feature or one circle per part of a multipart
feature.



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

The inputFeatures can be points, lines, and polygons.

If singlePart is set to True and the geometry is MultiPart, converts the geometry of
all parts.



Request Examples

statistics: FeatureToMinimumRectangle

inputFeatures

result



Response

The following figure shows the result of converting the polygon features to the minimum
bounding rectangles.

4.2.9.22.

Feature To ConvexHull

Converts each feature into a convex hull polygon that surrounds the featurein the feature
layers (inputFeatures).


Syntax

FeatureToConvexHull (SimpleFeatureCollection inputFeatures, Boolean singlePart):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures

Description
The input features that can be multipoint, line,
polygon.

Type

Required

Complex



Literal

Specifies whether to use one circle for each entire
singlePart

multipart feature or one circle per part of a multipart
feature.



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

The inputFeatures can be points, lines, and polygons.

If singlePart is set to True and the geometry is MultiPart, converts the geometry of
all parts.



Request Examples

statistics: FeatureToConvexHull

inputFeatures

result



Response

The following figure showsthe result of converting the polygon features to ConvexHull.

4.2.9.23.

Feature To Minimum Bounding Circle

Converts each feature into the minimum bounding circle

that surrounds each feature in

the feature layers (inputFeatures).


Syntax

FeatureToMinimumBoundingCircle (SimpleFeatureCollection inputFeatures, Boolean
singlePart): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures

Description
The input features that can be multipoint, line,
polygon.

Type

Required

Complex



Literal

Specifies whether to use one circle for each entire
singlePart

multipart feature or one circle per part of a multipart
feature.



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Required


Constraints

The inputFeatures can be points, lines, and polygons.

If singlePart is set to True and the geometry is MultiPart, converts the geometry of
all parts.



Request Examples

statistics:FeatureToMinimumBoundingCircle

inputFeatures

result



Response

The following figure showsthe result of converting the polygon features to the minimum
bounding circles.

4.3. Raster Analysis
These process groups are associated with raster analysis and processing.
4.3.1. Descriptive
These processes are for calculating the basic statistics for raster's property values.

4.3.1.1. Basic Statistics
Sets raster layers and specific areas to analyze basic statistics (Sum, Minimum, Maximum,
Mean, Standard Deviation, etc.) for raster cell values contained in the area.


Syntax

StatisticsGridCoverage (GridCoverage2D inputCoverage, Geometry cropShape, Integer
bandIndex): DataStatisticsResult


Parameters


Data Inputs

Identifier

Description

Type

inputCoverage

The input gridcoverage to be calculated.

Complex



cropShape

The Polygon or MultiPolygon to crop gridcoverage.

Complex

bandIndex

The zero-based band index, default index is a 0.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Result Statistics.

Complex



Required

Constraints

If cropShape is set to Null, creates statistics for all cells in the input raster.

The geometry type of cropShape must be Polygon or MultiPolygon.

The bandIndex is zero-base and 0 is default value.

Output is returned in XML format.





Request Examples

statistics:StatisticsGridCoverage

inputCoverage

foss:seoul_dem30

179171.39881047895 436569.3290600816
216221.0981287582 466869.08315843146

cropShape

result



Response

dem
Value
678064
0
1.0
754.0
753.0
1.0 - 754.0
4.2785658E7
63.09973394841785
7285.154424054373
85.35311607700315
1.3526699834705607
-9999

4.3.1.2. Histogram
Sets raster layers and specific regions to extract unique values and frequencies of raster
cells contained within the regions.


Syntax

HistogramGridCoverage (GridCoverage2D inputCoverage, Geometry cropShape, Integer
bandIndex): GridCoverage2D


Parameters


Data Inputs

Identifier

Description

Type

inputCoverage

The input gridcoverage to be calculated.

Complex



cropShape

The Polygon or MultiPolygon to crop gridcoverage.

Complex

bandIndex

The zero-based band index, default index is a 0.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Result Statistics.

Complex



Constraints

The geometry type of cropShape must be Polygon or MultiPolygon tpye.

The bandIndex is zero-base and 0 is the default value.

Output is returned in XML format.



Required

Request Examples



statistics:HistogramGridCoverage

inputCoverage

foss:landuse

179171.39881047895 436569.3290600816
216221.0981287582 466869.08315843146

cropShape

result



Response

The following figure shows the result of creating a statistic by clipping a specific area of
raster layers with the same grade in the Environmental Conservation Value Assessment
Map(ECVAM). Since the number of cells for each value is returned, multiplying by one
cell area (CellSize * CellSize) yields the area by grade.

landuse
Value
25498176.913556
30.0

1
876

2
543

3
292

4
1345

5
765

4.3.2. Conversion
These processes are for conversion between vector data and raster data.

4.3.2.1. Features To Raster
Converts point, line, and polygon feature layers (inputFeatures) to raster.


Syntax

FeaturesToRaster (SimpleFeatureCollection inputFeatures, String inputField, Double
cellSize, ReferencedEnvelope extent): GridCoverage2D


Parameters


Data Inputs

Identifier
inputFeatures

Description
The input feature dataset to be converted to a
raster.

Type

Required

Complex



inputField

The field used to assign values to the output raster.

Literal

cellSize

The cell size for the output raster.

Literal

extent

The extent for the output raster.

Complex



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex



Required


Constraints

The inputField parameter must be a numeric field or a constant value.

Unless sets the extent parameter, uses the range of inputFeatures.

Unless sets the cellSize parameter, the smaller one between width and height of the
extent is divided by 250.



Request Examples

statistics:FeaturesToRaster

inputFeatures

inputField

pop_den

cellSize

result



Response

The following figure shows the result of the converting the polygon geometry to raster
data.

4.3.2.2. Points To Raster
Converts the point feature layers (inputFeatures) into raster using the cell value
assignment method.


Syntax

PointsToRaster (SimpleFeatureCollection inputFeatures, String inputField,
PointAssignmentType cellAssignment, Double cellSize, ReferencedEnvelope extent):
GridCoverage2D


Parameters


Data Inputs

Identifier
inputFeatures
inputField

Description
The point or multipoint input feature dataset to be
converted to a raster.
The field used to assign values to the output raster.

Type

Required

Complex



Literal



Literal

The method to determine how the cell will be
cellAssignment

assigned a value when more than one feature falls
within a cell.

cellSize

The cell size for the output raster.

Literal

extent

The extent for the output raster.

Complex



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex



Required


Constraints

The inputFeatures parameter must be point or multiPoint feature types.

The inputField parameter must be numeric fields or values(constant value).

Unless sets the extent parameter, uses the range of the inputGeometry.

Unless sets the cellAssignment parameter, chooses the smaller value between
extent's width and height, and divides it by 250.

The cellAssignment parameter defines how to assign cell values when more than
one point is nested in a cell, and following options can be used.

Option

Desciption

MostFrequent

Frequency, If the frequency is the same, it arranged by the features order

Sum

Mean

Maximum

Minimum

Range

Count

The number of points, Force assignment even if not a numeric field



Request Examples

statistics:PointsToRaster

inputFeatures

inputField

gid

cellAssignment

Count

cellSize

result



Response

The following figure shows the result of converting the polygon geometry to raster
data.

4.3.2.3. Geometry To Raster
Converts geometry (inputGeometry) to raster.



Syntax

GeometryToRaster (Geometry inputGeometry, CoordinateReferenceSystem forcedCRS,
Number defaultValue, RasterPixelType pixelType, Double cellSize, ReferencedEnvelope
extent): GridCoverage2D


Parameters


Data Inputs

Identifier
inputGeometry
forcedCRS

Description
The input geometry to be converted to a raster
dataset.
Coordinate reference system to use for input
geometry.

Type

Required

Complex



Literal

defaultValue

The default value for the output pixel: 1(default).

Literal

pixelType

The pixel type for the output raster.

Literal

cellSize

The cell size for the output raster.

Literal

extent

The extent for the output raster.

Complex



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex


-

Required


Constraints
If the forcedCRS parameter is set to Null, uses CRS value of inputGeometry, and
CRS of inputGeometry must be set.

If the defaultValue parameter is set to Null, the default value is 1(Integer).

If the pixelType parameter is set to Null, uses Integer as the default value.

The pixelType parameter can use BYTE, SHORT, INTEGER, FLOAT, and DOUBLE
values.

Unless sets the extent parameter, uses the range of the inputGeometry.

Unless sets the cellSize parameter, chooses the smaller value between extent's width
and height, and divides it by 250.



Request Examples

statistics:GeometryToRaster

inputGeometry

forcedCRS

EPSG:3857

defaultValue

pixelType

INTEGER

cellSize

result



Response

The following figure showsthe result of converting the polygon geometry to raster data.

4.3.2.4. Raster To Point
Converts raster layers (inputCoverage) to point layers.
Syntax



RasterToPoint (GridCoverage2D inputCoverage, Integer bandIndex, String valueField):
SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputCoverage

The input gridcoverage to be converted.

Complex



bandIndex

The zero-based band index, default index is 0.

Literal

valueField



The field used to assign values from the cells.
Default is value.

Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex

Required

Constraints




Required

If valueField is set to Null, uses the fields of value names by default.
Request Examples

statistics:RasterToPoint

inputCoverage



valueField

val

result



Response

The following figure showsthe result of converting raster data to points.

4.3.2.5. Raster to Polygon
Converts raster layers (inputCoverage) to polygon layers.


Syntax

RasterToPolygon (GridCoverage2D inputCoverage, Integer bandIndex, Boolean weeding,
String valueField): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputCoverage

The input gridcoverage to be converted.

Complex



bandIndex

The zero-based band index, default index is 0.

Literal

Determines if the output polygons will be smoothed

weeding

into simpler shapes. Default is False.

valueField



The field used to assign values from the cells.
Default is value.

Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex


-

Required

Required


Constraints
If weeding is set to True, simplifies it using the Douglas-Puecker algorithm. The
tolerance is sqrt(0.5) * cell size.



If valueField is set to Null, uses the fields of value names by default.
Request Examples

statistics:RasterToPolygon

inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

weeding

True

result



Response

The following figure showsthe result of converting the DEM layer to polygon layers after
extracting features with elevation larger than 250 meters above sea level from DEM.

4.3.2.6. Raster to Image
Converts a raster layer (coverage) to an image using WMS parameter.


Syntax

RasterToImage (GridCoverage2D coverage, String bbox, CoordinateReferenceSystem crs,
Style style, Integer width, Integer height, String format, Boolean transparent, String
bgColor): Image


Parameters


Data Inputs

Identifier

Description

Type

coverage

The input gridcoverage to be converted.

Complex



Literal

Complex

Bounding box corners (lower left, upper right): minx,

bbox

miny, maxx, maxy.

crs

CRS for Bounding Box. Ex) EPSG:3857
Styled Layer Descriptor (SLD) style containing a

style

raster symbolizer.

Required

width

Image width in pixels of resulting map.

Literal



height

Image height in pixels of resulting map.

Literal



Literal

Output format of map. Valid values are image/jpeg,

format

image/png (Default), and image/gif.

transparent

Hexidecimal red-blue-green color value for the map

bgColor



Map background transparency. Default is True.
background color. Default is 0xFFFFFF (white).

Process Outputs

Identifier

Description

Type

result

Output image.

Complex


-

Required

Constraints
If the bbox and crs parameter are set to Null, uses the extents and coordinate
system of the coverage.



If the style parameter is set to Null, applies the Equal Interval Style using the
minimum / maximum value.



Request Examples

statistics:RasterToImage

coverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

width

500

height

400

format

image/png

transparent

True.

result



Response

The following figure showsthe result of requesting the Seoul DEM layer to an image (500
by 400 pixels). The requested result can be added to the image layer in OpenLayers.

4.3.3. Distance
Analysis the distance and adjacency of vector and raster data.

4.3.3.1. Euclidean Distance
Creates a raster dataset based on Euclidean distance between each cell and feature.


Syntax

EuclideanDistance (SimpleFeatureCollection inputFeatures, Double maximumDistance,
Double cellSize, ReferencedEnvelope extent): GridCoverage2D


Parameters


Data Inputs

Identifier
inputFeatures
maximumDistance

Description
The input features for which to calculate the
distance.
Defines the threshold that the accumulative distance
values cannot exceed.

Type

Required

Complex



Literal

cellSize

The cell size for the output raster.

Literal

extent

The extent for the output raster.

Complex



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex


-

Required


Constraints
If set the maximumDistance parameter, areas above the specified distance will be
assigned the No Data value.

Unless set the extent parameter, use the range of the inputFeatures layer.

Unless set the cellSize parameter, choose the smaller value between Extent's Width
and Height, and divide it by 250.



Request Examples

statistics:EuclideanDistance

inputFeatures

maximumDistance

2500

cellSize

result



Response

The following figure shows the result of Euclidean Distance analysis with maximum
distance of 2.5km and cell size of 30m, using Seoul big store point data.

4.3.4. Math
Createsthe new raster using a filter or formula.

4.3.4.1. Math Operation
Use the formula to create a new raster.
Syntax



RasterMath (GridCoverage2D inputCoverage, Integer bandIndex, Expression expression):
GridCoverage2D
Parameters



Data Inputs

Identifier

Description

Type

inputCoverage

The input raster to be calculated.

Complex



bandIndex

The zero-based band index, default index is a 0.

Literal



expression



A mathematical expression that evaluates raster cells.
Ex> log(Value * 250)

Required

Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex

Required

Constraints


-

The functions available in the expression parameter use the Filter Function4 of
GeoTools.



Request Examples

statistics:RasterMath

inputCoverage

cite:dem05

321541.5348100797 235208.86605789233
359950.1365611528 281299.18815918005

bandIndex

expression

log(Value * 250)

result



Response

The following figure shows result of applying log(Value * 250) calculation formula in
Seoul DEM raster data.

4.3.4.2. Set Null
Converts the cell value that corresponds to the filter condition to a NoData value, or
replaces the existing NoData value with another value.


Syntax

RasterSetNull (GridCoverage2D inputCoverage, Integer bandIndex, Filter filter, Boolean
replaceNoData, Double newValue): GridCoverage2D


Parameters


Data Inputs

Identifier

Description

Type

inputCoverage

The input raster to be evaluated.

Complex



bandIndex

The zero-based band index, default index is a 0.

Literal



A logical expression that determines which of the

filter

input cells are to be nodata. ex> Value > 250

replaceNoData
newValue



If true, nodata value will be replaced as a newValue
parameter. Default is False.
The new valid value to replace nodata.

Literal
Literal

Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex



Required

Required


Constraints

The field name of the filter parameter must be Value.

If the value of the replaceNoData parameter is True, replace the existing NoData
value with the value of the newValue parameter.



Request Examples

statistics:RasterSetNull

inputCoverage

cite:dem30

322223.9108718962 235108.16003333713
360624.44972726464 281188.51233892346

bandIndex

filter

250]]>

result



Response

The following figure shows the result of processing NoData areas, where the value is
more than 50 in the Seoul DEM raster data.

4.3.5. Classification
Reclass the raster values to a specific range of values.

4.3.5.1. Reclass
Reclass the raster data to the given range and the assigned value of each range.
Syntax



RasterReclass (GridCoverage2D inputCoverage, Integer bandIndex, String ranges):
GridCoverage2D
Parameters



Data Inputs

Identifier

Description

Type

inputCoverage

The input raster to be reclassified.

Complex



bandIndex

The zero-based band index, default index is a 0.

Literal



Ranges that defines how the values will be

ranges



reclassified. ex) 0.0 30.0 1; 30.0 270.0 2; 270.0 365.0 3

Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex

Required


Constraints




Required

The values in the ranges parameter treated as NoData values.
Request Examples

statistics:RasterReclass

inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

ranges

0.1 30.0 1; 30.0 200.0 2; 200.0 500.0 3

result



Response

The following figure shows the result of Reclass the Seoul DEM layer, 0.1 ~ 30.0 is 1
value, 30.0 ~ 200.0 is 2 value, and 200.0 ~ 500.0 is 3 value.

4.3.6. Extraction
Extract the raster that matches a space or attribute filter condition.

4.3.6.1. Extract by Attributes
Extract the raster that matches a space or attribute filter condition.


Syntax

RasterExtraction (GridCoverage2D inputCoverage, Integer bandIndex, Filter filter):
GridCoverage2D


Parameters


Data Inputs

Identifier

Description

Type

inputCoverage

The input raster from which cells will be extracted.

Complex



bandIndex

The zero-based band index, default index is a 0.

Literal

Complex



A logical expression that selects a subset of raster

filter

cells. ex> Value > 250



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex



Required

Constraints

The field name of the filter parameter must be Value.

The filter parameter can use a spatial filter.



Required

Request Examples

statistics:RasterExtraction

inputCoverage

filter

250]]>

result



Response

The following figure shows the result of extracting the area where the cell value is 250 or
more(value >= 250) from the raster data.

4.3.6.2. Extract by Extent
Extract the intersecting raster data.


Syntax

RasterClipByExtent (GridCoverage2D inputCoverage, ReferencedEnvelope extent):
GridCoverage2D


Parameters


Data Inputs

Identifier

Description

Type

inputCoverage

The input gridcoverage to be clipped.

Complex



extent

The Reference envelope to clip gridcoverage.

Complex





Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex


-

Required

Constraints
The extent parameter is of type BoundingBoxData and consists of crs, dimensions,
LowerCorner, UpperCorner as follows.

0.0 0.0
1.0 1.0





Request Examples

statistics:RasterClipByExtent

inputCoverage

foss:seoul_dem30

179171.39881047895 436569.3290600816
216221.0981287582 466869.08315843146

cropShape

196200.93382496 446742.832084541
200948.405261965 450277.401141511

result



Response

The following figure shows the result of extracting the raster data by setting
BoundingBox(MinX, MinY, MaxX, MaxY, CRS) area.

4.3.6.3. Extract by Geometry
Extract the intersecting raster data by setting Polygon Geometry.
Syntax



RasterClipByGeometry (GridCoverage2D inputCoverage, Geometry cropShape):
GridCoverage2D
Parameters



Data Inputs

Identifier

Description

Type

inputCoverage

The input gridcoverage to be clipped.

Complex



cropShape

The Polygon or MultiPolygon to clip gridcoverage.

Complex





Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex

Required

Constraints




Required

The geometry type of cropShape must be Polygon or MultiPolygon features.
Request Examples

statistics:RasterClipByGeometry

inputCoverage



foss:seoul_dem30

179171.39881047895 436569.3290600816
216221.0981287582 466869.08315843146

cropShape

result



Response

The following figure shows the result of extracting the raster data, set by the Polygon or
MultiPolygon Geometry.

4.3.6.4. Extract by Circle
Set the circle based on the center point and radius, extract it by the intersecting raster
data.
Syntax



RasterClipByCircle (GridCoverage2D inputCoverage, Geometry center, Double radius,
Boolean inside): GridCoverage2D
Parameters



Data Inputs

Identifier

Description

Type

inputCoverage

The input gridcoverage to be clipped.

Complex



Complex



The center point of the circle defining the area to be

center

extracted.

Required

radius

Radius of the circle defining the area to be extracted.

Literal



inside

Default is True

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex

Constraints




If the inside parameter is False, return the area excluding the circle.
Request Examples

statistics:RasterClipByCircle



inputCoverage

foss:seoul_dem30

179171.39881047895 436569.3290600816
216221.0981287582 466869.08315843146

center

radius

1500

result



Response

The following figure shows the result of extracting the raster data, corresponding to a
circle with a radius of 1500 meters around a certain point.

4.3.6.5. Conditional Expression
Converts the raster's cell value to a True or False value according to the filter conditions.


Syntax

RasterCon (GridCoverage2D inputCoverage, Integer bandIndex, Filter filter, Integer
trueValue, Integer falseValue): GridCoverage2D


Parameters


Data Inputs

Identifier

Description

Type

inputCoverage

The input gridcoverage to be clipped.

Complex



bandIndex

The zero-based band index, default index is a 0.

Literal

Complex



Literal



Literal

A logical expression that determines which of the

filter

input cells are to be true or false. ex> Value > 250

trueValue
falseValue



The input whose values will be used as the output
cell values if the condition is true.
The input whose values will be used as the output
cell values if the condition is false. Default is NoData.

Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex



Required


Constraints

The field name of the filter parameter must be Value.

The trueValue and falseValue parameter must be Integer values.

If the falseValue parameter value is Null, apply the NoData value.



Required

Request Examples

statistics:RasterCon

inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

filter

250]]>

trueValue

result



Response

The following figure shows the result of extracting the raster data, corresponding to a
circle with a radius of 1500 meters around a certain point.

4.3.7. Density
Perform density analysis of the raster.

4.3.7.1. Kernel Density
Perform Kernel Density analysis based on point features and various kernel functions.


Syntax

KernelDensity (SimpleFeatureCollection inputFeatures, KernelType kernelType, String
populationField, Double searchRadius, Double cellSize, ReferencedEnvelope extent):
GridCoverage2D


Parameters


Data Inputs

Identifier
inputFeatures
kernelType

Description
The input point features for which to calculate the
density.
Kernel functions.

Type

Required

Complex



Literal

populationField

The field denoting population values for each feature.

Literal

searchRadius

The search radius within which to calculate density.

Literal

cellSize

The cell size for the output raster.

Literal

extent

The extent for the output raster.

Complex



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex

Required


Constraints


-

Kernel Type5 consists of BINARY, COSINE, DISTANCE, EPANECHNIKOV, GAUSSIAN,
INVERSE_DISTANCE, QUADRATIC, QUARTIC, TRIANGULAR, TRIWEIGHT, TRICUBE.

Unless set the extent parameter, use the range of the inputFeatures layer.

Unless set the cellSize parameter, choose the smaller value between Extent's Width
and Height, and divide it by 250.

Unless set the searchRadius parameter, choose the smaller value between Extent's
Width and Height, and divide it by 30.



Request Examples

statistics:KernelDensity

inputFeatures

https://en.wikipedia.org/wiki/Kernel_%28statistics%29

kernelType

QUADRATIC

cellSize

extent

1.4111357E7 4498975.0
1.4158036E7 4537337.0

result



Response

The following figure shows the result of Kernel Density analysis of 30 meters cell size
based on Seoul gas station data.

4.3.7.2. Point Density
Perform density analysis by setting point features and neighbors.


Syntax

PointDensity (SimpleFeatureCollection inputFeatures, String populationField, String
neighborhood, Double cellSize, ReferencedEnvelope extent): GridCoverage2D


Parameters


Data Inputs

Identifier
inputFeatures
populationField

Description
The input point features for which to calculate the
density.
The field denoting population values for each
feature.

Type

Required

Complex



Literal

Neighborhood:
neighborhood

Ex> Circle + Radius
Ex> Rectangle + width + height

cellSize

The cell size for the output raster.

Literal

extent

The extent for the output raster.

Complex



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex


-

Required


Constraints
Unless set the neighborhood parameter, use the Circle + radius (the width and
height of the extent of inPutFeatures, whichever is smaller, divided by 30).

Unless set the extent parameter, use the range of the inputFeatures layer.

Unless set the cellSize parameter, choose the smaller value between Extent's Width
and Height, and divide it by 250.



Request Examples

statistics:PointDensity

inputFeatures

cellSize

result



Response

The following figure shows the result of Kernel Density analysis of 30 meters cell size
based on Seoul point data.

4.3.7.3. Line Density
Performs line density analysis using line features and search radius.


Syntax

LineDensity (SimpleFeatureCollection inputFeatures, String populationField, Double
searchRadius, Double cellSize, ReferencedEnvelope extent): GridCoverage2D


Parameters


Data Inputs

Identifier
inputFeatures
populationField

Description
The input line features for which to calculate the
density.
The field denoting population values for each
feature.

Type

Required

Complex



Literal

searchRadius

The search radius within which to calculate density.

Literal

cellSize

The cell size for the output raster.

Literal

extent

The extent for the output raster.

Complex



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex


-

Required


Constraints
Unless set the searchRadius parameter, choose the smaller value between Extent's
Width and Height, and divide it by 30.

Unless set the extent parameter, use the range of the inputFeatures layer.

Unless set the cellSize parameter, choose the smaller value between Extent's Width
and Height, and divide it by 250.



Request Examples

statistics:LineDensity

inputFeatures

cellSize

result



Response

The following figure shows the result of Line Density analysis of 30 meters cell size based
on Seoul major road data.

4.3.8. Interpolation
Perform interpolation analysis, using points and attribute values.

4.3.8.1. IDW (Inverse Distance Weighted)
Perform the Inverse Distance Weighted(IDW) Interpolation analysis using the point
feature layers.


Syntax

IDW (SimpleFeatureCollection inputFeatures, String inputField, Double power, RadiusType
radiusType, Integer numberOfPoints, Double distance, Double cellSize,
ReferencedEnvelope extent): GridCoverage2D


Parameters


Data Inputs

Identifier
inputFeatures
inputField

Description
The input point features for which to calculate the
density.
The field that holds a height or magnitude value for
each point.

Type

Required

Complex



Literal



power

The exponent (default 2.0) of distance.

Literal

radiusType

The search radius type Variable, Fixed

Literal

The numberOfPoints is an integer value specifying
numberOfPoints

the number of nearest input sample points to be
used to perform the interpolation.
The distance specifies the distance, in map units, by

distance

which to limit the search for the nearest input sample
points.

cellSize

The cell size for the output raster.

Literal

extent

The extent for the output raster.

Complex



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex



Constraints

Required


Unless set the Extent parameter, use the range of the inputFeatures layer.

Unless set the cellSize parameter, choose the smaller value between Extent's Width
and Height, and divide it by 250.



Request Examples

statistics:IDW

inputFeatures

inputField

price

power

2.0

radiusType

Variable

numberOfPoints

cellSize

extent

1.4111357E7 4498975.0
1.4158036E7 4537337.0

result



Response

The following figure shows the result of Inverse Distance Weighted(IDW) analysis of 30
meter cell size based on oil price information of Seoul gas station.

4.3.8.2. TPS (Thin Plate Spline)
Performs Thin Plate Spline(TPS) interpolation analysis using the point feature layers.


Syntax

TPS (SimpleFeatureCollection inputFeatures, String inputField, Double cellSize,
ReferencedEnvelope extent): GridCoverage2D


Parameters


Data Inputs

Identifier
inputFeatures
inputField

Description
The input point features for which to calculate the
density.
The field that holds a height or magnitude value for
each point.

Type

Required

Complex



Literal



cellSize

The cell size for the output raster.

Literal

extent

The extent for the output raster.

Complex



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex



Required


Constraints

Unless set the extent parameter, use the range of the inputFeatures layer.

Unless set the cellSize parameter, choose the smaller value between Extent's Width
and Height, and divide it by 250.



Request Examples

statistics:TPS

inputFeatures

inputField

price

cellSize

extent

1.4111357E7 4498975.0
1.4158036E7 4537337.0

result



Response

The following figure shows the result of Thin Plate Spline(TPS) analysis of 30 meter cell
size based on oil price information of Seoul gas station.

4.3.9. Surface Analysis
Perform the terrain analysis.

4.3.9.1. Raster Profile
Converts the raster data such as DEM and line layers to point data after longitudinal
section(Profile) analysis.


Syntax

RasterProfile (GridCoverage2D inputCoverage, Geometry userLine, Double interval):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputCoverage

The input surface raster.

Complex



userLine

LineString or MultiLineString geometry.

Literal



Literal

The interval of distance. Default = length of

interval



geometry / 20.

Process Outputs

Identifier

Description

Type

result

Output line features.

Complex


-

Required

Required


Constraints
Unless set the interval parameter, apply the value that divided the userLine length
by 20.

The Output point layers contain the distance(cumulative distance) and value (cell
value of the raster, such as height value) field.



Request Examples

statistics:RasterProfile

inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

userLine

result



Response

The following figure shows the result of Profile analysis as point layers and graph using
Seoul DEM.

4.3.9.2. Radial Line Of Sight
Perform Radial Line Of Sight analysis using observation points and radius using DEM
raster data.


Syntax

RadialLineOfSight (GridCoverage2D inputCoverage, Geometry observerPoint, Double
observerOffset, Double radius, Integer sides, Boolean useCurvature, Boolean
useRefraction, Double refractionFactor): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputFeatures

The input surface raster.

Complex



observerPoint

The observer's coordinate.

Complex



Literal



Literal



Literal

Required

observerOffset

The observer's offset above the surface rater. The
default is 0.0 units.
The radius from the observer point, for which the

radius

radial visibility will be calculated.

sides

The number of sides. The default sides is 180.

Required

Indicates whether the earth's curvature should be
useCurvature

taken into consideration for the line-of-sight analysis.
Default is False.
Indicates whether atmospheric refraction should be

useRefraction

taken into consideration when generating a line of
sight from a functional surface. Default is False.

refractionFactor



The refraction factor. The default refraction factor is
0.13.

Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex


-

Constraints
The useRefraction and refractionFactor parameter are only applied if the
useCurvature parameter is True.



If the useCurvature parameter is True and the useRefraction parameter is False,
then refractionFactor applies a value of 0.13.

The output line layers includes the Angle, Visible field, the visible field if the Visible
field value is 1, and the invisible area if it is 0.



Request Examples

statistics:RadialLineOfSight

inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

observerPoint

observerOffset

1.8

radius

5000

result



Response

The following figure shows the result of visible area analysis of 5000m radius based on
Namsan of Seoul DEM.

4.3.9.3. Linear Line Of Sight
Performs Linear Line Of Sight analysis using observation points and target points using
DEM raster data.


Syntax

LinearLineOfSight (GridCoverage2D inputCoverage, Geometry observerPoint, Double
observerOffset, Geometry targetPoint, Boolean useCurvature, Boolean useRefraction,
Double refractionFactor): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

inputCoverage

The input surface raster.

Complex



observerPoint

The observer's coordinate.

Complex



Literal



Complex



Literal

observerOffset
targetPoint

The observer's offset above the surface rater. The
default is 0.0 units.
The target's coordinate.

Required

Indicates whether the earth's curvature should be
useCurvature

taken into consideration for the line-of-sight
analysis. Default is False.
Indicates whether atmospheric refraction should be

useRefraction

taken into consideration when generating a line of
sight from a functional surface. Default is False.

refractionFactor



The refraction factor. The default refraction factor is
0.13.

Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex


-

Required


Constraints
If the useCurvature parameter is True, the useRefraction and refractionFactor
parameter are only applied.

If the useCurvature parameter is True and the useRefraction parameter is False,
then refractionFactor applies a value of 0.13.

The output line layers include a visible field, a visible area when the Visible field
value is 1, and a non-visible area when the value is 0.



Request Examples

statistics:LinearLineOfSight

inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

observerPoint

observerOffset

1.8

targetPoint

result



Response

The following figure shows the result of analyzing the line of sight of Yeouido, based on
Namsan of Seoul DEM.

4.3.9.4. Find Highest/Lowest Points
Find the highest and lowest positions in a specific area of raster data, such as DEM, and
return to the point.
Syntax



RasterHighLowPoints (GridCoverage2D inputCoverage, Integer bandIndex, Geometry
cropShape, HighLowType valueType): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputCoverage

The input gridcoverage to be processed.

Complex



bandIndex

The zero-based band index, default index is a 0.

Literal

cropShape

The Polygon or MultiPolygon to clip gridcoverage.

Complex

valueType

Value Type (Both, High, Low). Default is High.

Literal



Process Outputs

Identifier

Description

Type

result

Output Raster.

Complex

Required


Constraints


-

The cropShape parameter must be Polygon or MultiPolygon.

The valueType parameter uses the values of Both, High, and Low.



Required

Request Examples

statistics:RasterHighLowPoints

inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

valueType

Both

result



Response

The following figure shows the analysis result of the highest point based on the current
map range of Seoul DEM.

4.3.10. Zonal
Performs the zonal statistics.

4.3.10.1.

Zonal Statistics

Calculates statistics on the values of raster data for each area of section data.


Syntax

ZonalStatistics (SimpleFeatureCollection zoneFeatures, GridCoverage2D inputCoverage,
Integer bandIndex): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
zoneFeatures
targetField
valueCoverage

Description
The Dataset (polygon features) that defines the
zones.
The output field to be calculated.
The Raster that contains the values on which to
calculate a statistic.

Type

Required

Complex



Literal

Complex



bandIndex

The zero-based band index, default index is a 0.

Literal

statisticsType

Zonal statisticx type to be calculated.

Literal



Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Constraints

The zoneFeatures parameter must be Polygon or MultiPolygon type.

Unless set the targetField parameter, use val value as default.

If there are multiple raster bands, the bandIndex uses 0 value as default.

The statisticsType parameter can use the following options.

Required


Option

Description

Count

Number of cells

Sum

Sum of cells

Mean

Mean of cells (Default)

Minimum

Minimum of cells

Maximum

Maximum of cells

Range

Range of cells

StdDev

Stard deviation



Request Examples

statistics:ZonalStatistics

zoneFeatures

targetField

h_mean

valueCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

bandIndex

statisticsType

Mean

result



Response

The following figure shows the analysis result of average elevation by administrative
boundary(Si-Gun-Gu) using Seoul DEM.

4.3.11. Projection
Define the coordinate system, transforming and changing cell size, of raster data.

4.3.11.1.

Resample

Change the resolution (cell size) of the raster data.


Syntax

RasterResample (GridCoverage2D inputCoverage, Double cellSize, ResampleType
resamplingType): GridCoverage2D


Parameters


Data Inputs

Identifier
inputCoverage
cellSize

The raster dataset for which you want to change the
spatial resolution.
The cell size for the output raster.

resamplingType



Description

The resampling algorithm to be used.
Ex> NEAREST (default), BILINEAR, BICUBIC.

Type
Complex



Literal



Complex

Process Outputs

Identifier

Description

Type

result

Output raster.

Complex


-

Required

Constraints
The resamplingType parameter can use the NEAREST(default), BILINEAR, and
BICUBIC options.



Request Examples

statistics:RasterResample

inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

cellSize

resamplingType

NEAREST

result

4.3.11.2.

Redefine Projection

Define or redefine the coordinate system of the raster data with a new coordinate
system.
Syntax



RasterForceCRS (GridCoverage2D inputCoverage, CoordinateReferenceSystem forcedCRS):
GridCoverage2D
Parameters



Data Inputs

Identifier
inputCoverage
forcedCRS



Description
The raster dataset for which you want to redefine
the coordinate reference system.
Coordinate reference system to use for input raster
dataset.

Type
Complex



Literal



Process Outputs

Identifier

Description

Type

Result

Output raster.

Complex

Required

Constraints


-



Required

The forcedCRS parameter must be in the [EPSG: code number] format.

Request Examples

statistics:RasterForceCRS



inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

forcedCRS

EPSG:5181

result



Response

The following figure shows the result of redefining the original Daegu EPSG:5181 DEM as
EPSG:5186.

4.3.11.3.

Reproject

Converts the coordinate system of raster data.


Syntax

RasterReproject (GridCoverage2D inputCoverage, CoordinateReferenceSystem targetCRS,
ResampleType resamplingType, Double cellSize, CoordinateReferenceSystem forcedCRS):
GridCoverage2D


Parameters


Data Inputs

Identifier
inputCoverage
targetCRS
resamplingType
cellSize

Description
The raster dataset for which you want to change the
spatial reference system.
Target coordinate reference system to use for
reprojection.
The resampling algorithm to be used. NEAREST
(default), BILINEAR, BICUBIC.
The cell size for the output raster.

Type

Required

Complex



Literal



Literal

Coordinate reference system to use for input raster

forcedCRS



dataset.

Literal

Process Outputs

Identifier

Description

Type

result

Output raster.

Complex

Required


Constraints


-

The targetCRS and forcedCRS parameter must be [EPSG: code number] format.

The resamplingType parameter can use the NEAREST (default), BILINEAR, BICUBIC
options.

Unless set the cellSize parameter, the original cell size is used. If converting from
the geographic coordinate system to the projection coordinate system, the
converted cell size is applied.

If the forcedCRS parameter is set, converting the original raster data to the defined
coordinate system.



Request Examples

statistics:RasterReproject

inputCoverage

foss:seoul_dem30

1.4111343323506365E7 4498971.750719266
1.4158021303411832E7 4537343.6431004135

targetCRS

EPSG:5181

resamplingType

NEAREST

cellSize

result

4.4. Spatial Statistics Analysis
A process group associated with spatial statistical analysis.
4.4.1. Descriptive
Calculates the statistical information using Geometry or attribute value of field.

4.4.1.1. Basic Statistics
Perform basic statistical analysis based on field values in the feature layers.


Syntax

StatisticsFeatures (SimpleFeatureCollection inputFeatures, String inputFields, String
caseField): DataStatisticsResult


Parameters


Data Inputs

Identifier
inputFeatures

Description
The input features containing the field(s) that will be
used to calculate statistics.

Type

Required

Complex



Literal



Literal

Required

Single field or comma (,) separated numeric field(s)
inputFields

containing attribute values used to calculate the
specified statistic.
The field used to group features for separate

caseField



statistics calculations.

Process Outputs

Identifier

Description

Type

result

Output Statistics.

Complex


-

Constraints
If the caseField parameter is set, statistical information is generated for each unique
value of the caseField.



Output is returned in XML format.



Request Examples

statistics:StatisticsFeatures

inputFeatures

inputFields

a3_2005

caseField

sid_nm

result



Response

This is the result of analyzed basic statistic by administrative boundary(Si-Gun-Gu) using
the a3_2000 field value of the national Si-Gun-Gu administrative district is converted XML
format.

korea_sgg
강원도
a3_2000
18
0
0.24774
7.81668
7.56894
0.24774 - 7.81668
79.64533043000002
4.424740579444445
6.976857255428096
2.641374122578643
0.5969557028607279

korea_sgg
경기도
a3_2000
31
0
0.0
15.46253
15.46253
0.0 - 15.46253
271.03358996
8.74301903096774
21.209124717119646
4.605336547649872
0.5267444267635456

4.4.1.2. Pearson Correlation Coefficient
Calculates the Pearson's Correlation Coefficient using two or more attribute fields.
Syntax



Pearson (SimpleFeatureCollection inputFeatures, String inputFields): PearsonResult
Parameters



Data Inputs

Identifier

Description

Type

Required

inputFeatures

Input features to be calculated.

Complex



Literal



Required

The comma separated numeric field(s) containing
inputFields

attribute values used to calculate the specified
statistic.



Process Outputs

Identifier

Description

Type

result

Result Pearson Correlation Coefficient.

Complex

Constraints




Output is returned in XML format.
Request Examples

statistics:Pearson

inputFeatures



inputFields

pop2008, pop_den

result



Response

This is the result of analyzing Pearson correlation, using two fields of the administrative
boundary(Si-Gun-Gu). Ouput is converted XML format.

1.0

0.3002549407911261

1.0

4.4.1.3. Standardized Score of Dissimilarity
Calculates the standardized score of dissimilarity(SSD, degree of concentration), using the
two attribute field values.


Syntax

StandardizedScores (SimpleFeatureCollection inputFeatures, Expression xField, Expression
yField, String targetField): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures

Description
The features for which the standardized score of
dissimilarity will be calculated.

Type

Required

Complex



xField

X Value Field.

Literal



yField

Y Value Field.

Literal



targetField

Target Field. std_scr is default.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex






Constraints
Unless set the targetField parameter, the std_scr is default,.
Request Examples

statistics:StandardizedScores

inputFeatures

xField

a0_2005

yField

a3_2005

targetField

std_scr

result



Response

The following figure shows the result of the SSD analysis using the two fields of the
administrative boundary(Si-Gun-Gu). Using the property values of targetField, visualize
the SSD.

4.4.1.4. Focal Location Quotients
Calculates the Focal Location Quotients(FLQ, degree of specialization) using two attribute
field values.
Syntax



FocalLQ (SimpleFeatureCollection inputFeatures, String fieldName1, String fieldName2,
Double searchDistance): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

The features for which the focal LQ will be calculated.

Complex



fieldName1

X Value Field.

Literal



fieldName2

Y Value Field.

Literal



searchDistance

The maximun search distance.

Literal

Required



Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints




Required

The fields of the Output layer return values of flq, flqd, and fz.
Request Examples

statistics:FocalLQ

inputFeatures



xField

a0_2005

yField

a3_2005

result



Response

The following figure shows the visualized result of analyzing the FLQ, using the two fields
of the administrative boundary(Si-Gun-Gu).

4.4.2. Distributions
Analyze the distribution of vector data patterns.

4.4.2.1. Mean Center
Returns the geographic center or center of concentration for all features in the feature
layer.


Syntax

MeanCenter (SimpleFeatureCollection inputFeatures, String weightField, String caseField,
String dimensionField): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures
weightField

A features for which the mean center will be
calculated.
The numeric field used to create a weighted mean
center.
The field used to group features for separate mean

caseField

center calculations.

dimensionField



Description

A numeric field containing attribute values from
which an average value will be calculated.

Type
Complex



Literal

Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex




Required

Constraints
Calculates using Centroid of inputFeatures.
Request Examples

statistics:MeanCenter

inputFeatures

caseField

sgg_nm

result



Response

The following figure shows the result of analyzing the Mean Center about the
distribution of Seoul apartment by administrative boundary(Si-Gun-Gu).

4.4.2.2. Median Center
Returns the point at which the sum of the total distances is the smallest(Median Center)
for all features in the feature layers.


Syntax

MedianCenter (SimpleFeatureCollection inputFeatures, String weightField, String caseField,
String attributeFields): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures
weightField

A features for which the median center will be
calculated.
The numeric field used to create a weighted median
center.
The field used to group features for separate median

caseField

center calculations.

attributeFields



Description

(Comma separated) Numeric field(s) for which the
data median value will be computed.

Type
Complex



Literal

Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex




Required

Constraints
Calculate using Centroid of inputFeatures.
Request Examples



statistics:MedianCenter

inputFeatures

caseField

sgg_nm

result



Response

The following figure shows the result of analyzing the Median Center about the
distribution of Seoul apartment by administrative boundary(Si-Gun-Gu)..

4.4.2.3. Central Feature
Returns the Central Feature with the smallest sum of the total distances for all features in
the feature layer.


Syntax

CentralFeature (SimpleFeatureCollection inputFeatures, DistanceMethod distanceMethod,
String weightField, String selfPotentialWeightField, String caseField):
SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

Required

The features containing a distribution of features
inputFeatures

from which to identify the most centrally located

Complex



Literal

Required

feature.
Specifies how distances are calculated from each
distanceMethod

feature to neighboring features. Euclidean (default) or
Manhattan.
The numeric field used to weight distances in the

weightField

origin-destination distance matrix.
The field representing self-potential. The distance or

selfPotentialWeightField

weight between a feature and itself.
The field used to group features for separate central

caseField



feature computations.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex




Constraints
Calculates using Centroid of inputFeatures.
Request Examples

statistics:CentralFeature

inputFeatures

distanceMethod

Euclidean

caseField

sgg_nm

result



Response

The following figure shows the result of analyzing the Central Feature about the
distribution of Seoul apartment by administrative boundary(Si-Gun-Gu).

4.4.2.4. Standard Distance
Measures the extent to which all features in the feature layers are centered or scattered
by the Mean Center.


Syntax

StandardDistance (SimpleFeatureCollection inputFeatures, String circleSize, String
weightField, String caseField): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

Required

The features containing a distribution of features for
inputFeatures

which the standard deviational ellipse will be

Complex



Literal

Required

calculated.
The size (1, 2, 3) of output circles in standard

circleSize

deviations.

weightField

to their relative importance.
The field used to group features for separate

caseField



The numeric field used to weight locations according

standard distance calculations.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex





Constraints

Calculate using Centroid of inputFeatures.

The Circle generally includes features of 68% for 1_Standard_Deviation, 95% for
2_Standard_Deviation, and 99% for 3_Standard_Deviation.



Request Examples

statistics:StandardDistance

inputFeatures

circleSize

1_Standard_Deviation

caseField

sgg_nm

result



Response

The following figure shows the result of analyzing the Standard Distance about the
distribution of Seoul apartment by administrative boundary(SiGun-Gu).

4.4.2.5. Standard Deviational Ellipse
Measures the degree which all features of the feature layer are concentrated or centered
by the Mean Center and the orientation of the distribution.


Syntax

StandardDeviationalEllipse (SimpleFeatureCollection inputFeatures, String ellipseSize,
String weightField, String caseField): SimpleFeatureCollection


Parameters


Data Inputs

Identifier

Description

Type

Required

The features containing a distribution of features for
inputFeatures

which the standard deviational ellipse will be

Complex



Literal

Required

calculated.
ellipseSize
weightField

deviations.
The numeric field used to weight locations according
to their relative importance.
The field used to group features for separate

caseField



The size (1, 2, 3) of output ellipses in standard

directional distribution calculations.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex





Constraints

Calculates using Centroid of inputFeatures.

The Ellipse typically includes features of 68% for 1_Standard_Deviation, 95% for
2_Standard_Deviation, and 99% for 3_Standard_Deviation.



Request Examples

statistics:StandardDeviationalEllipse

inputFeatures

ellipseSize

1_Standard_Deviation

caseField

sgg_nm

result



Response

The following figure shows the result of analyzing the Standard Deviational Ecclipse
about the distribution of Seoul apartment by administrative boundary(Si-Gun-Gu)district.

4.4.2.6. Linear Directional Mean
Identify the geographic center, the average length, and the direction for all features of
line feature layers.
Syntax



LinearDirectionalMean (SimpleFeatureCollection inputFeatures, Boolean orientationOnly,
String caseField): SimpleFeatureCollection
Parameters



Data Inputs

Identifier
inputFeatures
orientationOnly

The line features containing vectors for which the
mean direction will be calculated.
The From and To nodes are utilized in calculating the
mean.
The field used to group features for separate

caseField



Description

directional mean calculations.

Type
Complex



Literal

Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints




Required

The inputFeatures must be line features type.
Request Examples

statistics:LinearDirectionalMean



inputFeatures

orientationOnly

True

result



Response

The following figure shows the result of Linear Directional Mean analysis for line layers
with length and directionality.

4.4.3. Point Pattern Analysis
Analyze the pattern of the point data.

4.4.3.1. Nearest Neighbor Statistic
Calculates the Nearest Neighbor Index based on the average distance from the feature
closest to each feature in the feature layer.


Syntax

NearestNeighborIndex (SimpleFeatureCollection inputFeatures, DistanceMethod
distanceMethod, Double area): NearestNeighborResult


Parameters


Data Inputs

Identifier

Description

Type

Required

inputFeatures

Input features.

Complex



Literal

Required

Specifies how distances are calculated from each
distanceMethod

feature to neighboring features: Euclidean (default) or
Manhattan.

area

A numeric value representing the study area.



Process Outputs

Identifier

Description

Type

result

Result Nearest Neighbor Index

Complex





Constraints

Calculates using Centroid of inputFeatures.

Unless set the area parameter, use the Convex Hull Polygon area for Centroid in
inputFeatures.

The output is returned in XML format. If the returned Nearest Neighbor Ratio value
is 1, Random, if it is larger than 1, it is distributed. If it is smaller than 1, it is
concentrated.



Request Examples

statistics:NearestNeighborIndex

inputFeatures

distanceMethod

Euclidean

result



Response

This is the result of analyzing Average Nearest Neighbor for the distribution of
apartments in Seoul and is returned in XML format. Since the Nearest Neighbor Ratio is
less than 1, it can explain Cluster.

apartment
4052
1.047557075141607E9
200.00446
254.22844
0.786712
-25.973484
0.0
2.087667

4.4.3.2. Quadrat Method
Analyze the point pattern using Quadrat analysis method.
Syntax



QuadratAnalysis (SimpleFeatureCollection inputFeatures, Double cellSize): QuadratResult
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

The point features to be calculated.

Complex



cellSize

The size of the grid cell.

Literal



Required

Process Outputs

Identifier

Description

Type

result

The Result of quadrat analysis

Complex

Required


Constraints


-

Calculates using Centroid of inputFeatures.

If you do not set the cellSize parameter, use the following formula to calculate the
cell size. Math.sqrt ((BBOX area of inputFeatures * 2) / number of points).



Request Examples

statistics:QuadratAnalysis

inputFeatures

result



Response

This is the result of analyzing the Quadrate Method for the distribution of gas stations in
Seoul and is returned in XML format.

gasstation
587
1.4406602767217913E9
2215.5254234488443
19
16
304
1.930921052631579
5.643254414819944
2.9225712812696134
0.32209069225598863
0.078001349515991

4.4.3.3. K-Nearest Neighbor Map
Creates line feature layers that connects the k-th nearest feature from all features in the
feature layer.
Syntax



KNearestNeighborMap (SimpleFeatureCollection inputFeatures, Integer neighbor, Boolean
convexHull): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features that can be point, line, polygon.

Complex



neighbor

Number of Neighbors. Default is 1.

Literal



Literal

Required

convexHull



Add convex hull boundary to the output features.
Default is True.

Required

Process Outputs

Identifier

Description

Type

result

Output features.

Complex



Constraints


-

The Neighbor parameter must be greater than or equal to 1 and defaults to 1.

The Output layer is the line feature type.



Request Examples

statistics:KNearestNeighborMap

inputFeatures

neighbor

convexHull

False

result



Response

The following figure shows the result of the K-Nearest Neighbor with the Neighbor
parameter set to 2.

4.4.3.4. K-Means Clustering
All features in the feature layer are grouped into K clusters using the K-Means Clustering
algorithm.
Syntax



KMeansClustering (SimpleFeatureCollection inputFeatures, String targetField, Integer
numberOfClusters): SimpleFeatureCollection
Parameters



Data Inputs

Identifier

Description

Type

inputFeatures

Input features to be clustered.

Complex



Literal



Literal



Required

targetField
numberOfClusters



The numeric cluster id field to be calculated. Default
is cluster
The number of clusters to be grouped. Default is 5.

Process Outputs

Identifier

Description

Type

result

Output features.

Complex

Constraints


-

Unless set the targetField parameter, use default cluster field,

Unless set the numberOfClusters parameter, use default value of 5.



Required

Request Examples

statistics:KMeansClustering



inputFeatures

targetField

cluster

numberOfClusters

result



Response

The following figure shows the result of point layers Clusters with the set 5.

4.4.4. Global Spatial Auto-Correlation
It consists of processes for analyzing global spatial autocorrelation.

4.4.4.1. Join Count Statistic
Measure the global spatial autocorrelation of binary data (such as 1 or Black, 0 or White)
based on the field values of the feature layer.


Syntax

JoinCount (SimpleFeatureCollection inputFeatures, Filter blackExpression, ContiguityType
contiguityType): JoinCountProcessResult


Parameters


Data Inputs

Identifier
inputFeatures
blackExpression
contiguityType



Description
The features for which join count statistics will be
performed.
Black Expression for 1 or True (for Black) value ex)
[pop] > 1500.
Contiguity Type(Queen, Rook, Bishops). Default is
Queen.

Type
Complex



Complex



Literal

Required

Process Outputs

Identifier

Description

Type

result

Join Count Statistics.

Complex



Required



Constraints

Both field and combination formula of fields can be the blackExpression parameter.

Output is returned in XML format.



Request Examples

statistics:JoinCount

inputFeatures

blackExpression

18890]]>

contiguityType

Queen

result



Response

This is the result of analyzing the Join Count statistic by the method of the Queen, and it
returns in the XML format.

sgg
Queen
25
11
14
56
11
18
27
10.8416
17.561600000000002
27.5968
5.487588556005269
6.831669500202715
3.9479960283667954
0.028865137825731742
0.06417172259094052
-0.15116529898002093

4.4.4.2. Moran’s I
Measures the global Moran's I spatial autocorrelation based on the location and attribute
values of the feature layer.


Syntax

GlobalMoransI (SimpleFeatureCollection inputFeatures, String inputField, SpatialConcept
spatialConcept, DistanceMethod distanceMethod, StandardizationMethod standardization,
Double searchDistance): MoransI


Parameters


Data Inputs

Identifier
inputFeatures
inputField
spatialConcept
distanceMethod
standardization
searchDistance



Description
The features for which spatial autocorrelation will be
calculated.
The numeric field used in assessing spatial
autocorrelation.
Specifies how spatial relationships among features
are conceptualized. Default is InverseDistance
Specifies how distances are calculated from each
feature to neighboring features. Default is Euclidean
Row standardization. Default is None
Specifies a cutoff distance for Inverse Distance and
Fixed Distance options.

Type
Complex



Literal



Literal

Required

Process Outputs

Identifier

Description

Type

result

Output XML.

Complex




Required

Constraints
Output is returned in XML format.
Request Examples

statistics:GlobalMoransI

inputFeatures

inputField

a3_2005

spatialConcept

InverseDistance

distanceMethod

Euclidean

standardization

Row

result



Response

korea_sgg
a3_2005
0.070175
-0.004292
0.000203
5.230945
0
InverseDistance
Euclidean
Row
191807.950591

4.4.4.3. Geary’s c
Measures the global Geary's c spatial autocorrelation based on the location and attribute
values of the feature layer.


Syntax

GlobalGearysC (SimpleFeatureCollection inputFeatures, String inputField, SpatialConcept
spatialConcept, DistanceMethod distanceMethod, StandardizationMethod standardization,
Double searchDistance): GearysC


Parameters


Data Inputs

Identifier
inputFeatures
inputField
spatialConcept
distanceMethod
standardization
searchDistance



Type
Complex



Literal



Literal

Process Outputs

Identifier

Description

Type

result

Output XML.

Complex




Required

Constraints
Output is returned in XML format.
Request Examples

statistics:GlobalGearysC

inputFeatures

inputField

a3_2005

spatialConcept

InverseDistance

distanceMethod

Euclidean

standardization

Row

result



Response

korea_sgg
a3_2005
0.908981
1
0.00029
-5.341097
0
InverseDistance
Euclidean
Row
191807.950591

4.4.4.4. Getis-Ord’s General G
Measures the global Getis-Ord General G spatial autocorrelation based on the location
and attribute values of the feature layer.


Syntax

GlobalGStatistics (SimpleFeatureCollection inputFeatures, String inputField,
SpatialConcept spatialConcept, DistanceMethod distanceMethod, StandardizationMethod
standardization, Double searchDistance): GeneralG


Parameters


Data Inputs

Identifier
inputFeatures
inputField
spatialConcept
distanceMethod
standardization
searchDistance



Type
Complex



Literal



Literal

Process Outputs

Identifier

Description

Type

result

Output XML.

Complex




Required

Constraints
Output is returned in XML format.
Request Examples

statistics:GlobalGStatistics

inputFeatures

inputField

a3_2005

spatialConcept

InverseDistance

distanceMethod

Euclidean

standardization

Row

result



Response

korea_sgg
a3_2005
0.004492
0.004292
0
4.275913
0.000019
InverseDistance
Euclidean
Row
191807.950591

4.4.4.5. Lee's S
Measures the global Lee's S spatial autocorrelation based on the location and attribute
values of the feature layer.


Syntax

GlobalLeesS (SimpleFeatureCollection inputFeatures, String inputField, SpatialConcept
spatialConcept, DistanceMethod distanceMethod, StandardizationMethod standardization,
Double searchDistance): LeesS


Parameters


Data Inputs

Identifier
inputFeatures
inputField
spatialConcept
distanceMethod
standardization
searchDistance



Type
Complex



Literal



Literal

Process Outputs

Identifier

Description

Type

result

Output XML.

Complex




Required

Constraints
Output is returned in XML format.
Request Examples

statistics:GlobalLeesS

inputFeatures

inputField

a3_2005

spatialConcept

InverseDistance

distanceMethod

Euclidean

standardization

Row

result



Response

korea_sgg
a3_2005
0.065413
0.090566
0
0
1
InverseDistance
Euclidean
Row
191807.950591

4.4.4.6. Lee's L
Measures the global Lee's L spatial autocorrelation based on the location and two
attribute values of the feature layer.


Syntax

GlobalLeesL (SimpleFeatureCollection inputFeatures, String xField, String yField,
SpatialConcept spatialConcept, DistanceMethod distanceMethod, StandardizationMethod
standardization, Double searchDistance): LeesL


Parameters


Data Inputs

Identifier
inputFeatures

The features for which spatial autocorrelation will be
calculated.
The numeric x field used in assessing spatial

xField

autocorrelation.
The numeric y field used in assessing spatial

yField

autocorrelation.

spatialConcept
distanceMethod
standardization
searchDistance



Description

Specifies how spatial relationships among features
are conceptualized. Default is InverseDistance
Specifies how distances are calculated from each
feature to neighboring features. Default is Euclidean
Row standardization. Default is None
Specifies a cutoff distance for Inverse Distance and
Fixed Distance options.

Type
Complex



Literal



Literal



Literal

Process Outputs

Identifier

Description

Type

result

Output XML.

Complex




Required

Constraints
Output is returned in XML format.
Request Examples

Required


statistics:GlobalLeesL

inputFeatures

inputField

a3_2005

spatialConcept

InverseDistance

distanceMethod

Euclidean

standardization

Row

result



Response

korea_sgg
a + b
0.42206509
0.090566
0
0
1
0.42206509
Euclidean
Row
0

4.4.5. Local Spatial Auto-Correlation
It consists of processes for analyzing local spatial autocorrelation.

4.4.5.1. Local Moran’s I
Using the Anselin’s local Moran’s I statistics from the feature layers, identify statistically
significant hot spot, cold spot and spatial outliers.


Syntax

LocalMoransI (SimpleFeatureCollection inputFeatures, String inputField, SpatialConcept
spatialConcept, DistanceMethod distanceMethod, StandardizationMethod standardization,
Double searchDistance): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures
inputField
spatialConcept
distanceMethod
standardization
searchDistance



Type
Complex



Literal



Literal

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Required


Constraints
The Output layer contains all the fields of inputFeatures, with the field of LMiIndex,
LMiZScore, LMiPValue, LMizValue, LMiwzValue, and COType added.



Request Examples

statistics:LocalMoransI

inputFeatures

inputField

a3_2005

spatialConcept

InverseDistance

distanceMethod

Euclidean

standardization

Row

result



Response

4.4.5.2. Local G (Gi*)
Identify statistically significant hot spots and cold spots using the local Getis-Ord Gi*
statistic from the feature layer.


Syntax

LocalGStatistics (SimpleFeatureCollection inputFeatures, String inputField, SpatialConcept
spatialConcept, DistanceMethod distanceMethod, StandardizationMethod standardization,
Double searchDistance): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures
inputField
spatialConcept
distanceMethod
standardization
searchDistance



Type
Complex



Literal



Literal

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required


Constraints
The Output layer contains all the fields of inputFeatures, with the fields of GiZScore,
GiMean, GiVar, and GiPValue added.



Required

Request Examples

statistics:LocalGStatistics

inputFeatures

inputField

pts

spatialConcept

InverseDistance

distanceMethod

Euclidean

standardization

Row

result



Response

4.4.5.3. Local Geary’s c
Calculates the local Geary's c statistic from the feature layer


Syntax

LocalGearysC (SimpleFeatureCollection inputFeatures, String inputField, SpatialConcept
spatialConcept, DistanceMethod distanceMethod, StandardizationMethod standardization,
Double searchDistance): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures
inputField
spatialConcept
distanceMethod
standardization
searchDistance



Type
Complex



Literal



Literal

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Constraints
The Output layer contains all the fields of inputFeatures, with the fields of LGcIndex,
LGcZScore, and LGcPValue added.





Request Examples

statistics:LocalGearysC

inputFeatures

inputField

a3_2005

spatialConcept

InverseDistance

distanceMethod

Euclidean

standardization

Row

result



Response

4.4.5.4. Lee's Si
Calculates the local Lee’s Si statistics from the feature layer.


Syntax

LocalLeesS (SimpleFeatureCollection inputFeatures, String inputField, SpatialConcept
spatialConcept, DistanceMethod distanceMethod, StandardizationMethod standardization,
Double searchDistance): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures
inputField
spatialConcept
distanceMethod
standardization
searchDistance



Type
Complex



Literal



Literal

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required

Constraints
The Output layer contains all the fields of inputFeatures, with the fields of LLsIndex,
LLsZScore and LLsPValue added.





Request Examples

statistics:LocalLeesS

inputFeatures

inputField

pts

spatialConcept

InverseDistance

distanceMethod

Euclidean

standardization

Row

result



Response

4.4.5.5. Lee's Li
Calculates the local Lee's Li statistic from the feature layer and two attribute values.


Syntax

LocalLeesL (SimpleFeatureCollection inputFeatures, String xField, String yField,
SpatialConcept spatialConcept, DistanceMethod distanceMethod, StandardizationMethod
standardization, Double searchDistance): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures

The features for which spatial autocorrelation will be
calculated.
The numeric x field used in assessing spatial

xField

autocorrelation.
The numeric y field used in assessing spatial

yField

autocorrelation.

spatialConcept
distanceMethod
standardization
searchDistance



Description

Type
Complex



Literal



Literal



Literal

Process Outputs

Identifier

Description

Type

result

Output features.

Complex


-

Required


Constraints
The Output layer contains all the fields of inputFeatures, with the fields of LLlIndex,
LLlZScore, and LLlPValue fields added.



Required

Request Examples

statistics:LocalLeesL

inputFeatures

xField

a2009

yField

b2009

spatialConcept

ContiguityEdgesNodes

distanceMethod

Euclidean

standardization

Row

result



Response

4.4.6. Global Spatial Modeling
It consists of processes that analyze global spatial modeling and spatial relationships.

4.4.6.1. Ordinary Least Squares (OLS)
Performs global Ordinary Least Squares(OLS) linear regression.


Syntax

OrdinaryLeastSquares (SimpleFeatureCollection inputFeatures, String dependentVariable,
String explanatoryVariables): SimpleFeatureCollection


Parameters


Data Inputs

Identifier
inputFeatures
dependentVariable
explanatoryVariables



olsFeatures
report

The features containing the dependent and
independent variables for analysis.
The numeric field containing values for what you are
trying to model.
The comma separated fields representing
explanatory variables in your regression model.

Type
Complex



Literal



Literal



Description

Type

Required

The output features to receive dependent variable
estimates and residuals.
Output OLS results.

Complex
Complex





Constraints
The olsFeatures layer contains all the fields of inputFeatures, with the fields of
Estimated, Residual, StdResid, and StdResid2 added.

Required

Process Outputs

Identifier



Description

Output is returned in XML format.
Request Examples



Response


Map



XML

0.6101560399292024
0.3722903930620865
0.3290000753422304
12.933848555707566
63
508.1174991231418
509.6174991231418

4
5754.486696189348
1438.621674047337

8.599853562435902
1.609736408525464E-5

58
9702.497430794765
167.2844384619787

62
15456.984126984113

Intercept
1.8149624761790997
2.256350184412793
0.8043797849806887
0.42445922884684884

etc
6.922393697035605
1.217664912349127
5.684974270697246
5.13680658710916E-7

ccc
-0.2585330201573057
0.4672538188264545
-0.5533031721530541
0.5821837017619861

mlbflb
-0.04321817419824479
2.571603704239341
-0.01680592313932304
0.9866481737384326

airport
-2.3644517041718496
2.64338529816144
-0.8944786466870351
0.3747591210649666

Source Exif Data:

File Type                       : PDF
File Type Extension             : pdf
MIME Type                       : application/pdf
PDF Version                     : 1.5
Linearized                      : No
Page Count                      : 397
Language                        : ko-KR
Tagged PDF                      : Yes
Title                           : GeoServer Spatial Extension
Author                          : LeeMinPa
Subject                         : GXT for Desktop
Keywords                        : GeoServer
Creator                         : Microsoft® Word 2013
Create Date                     : 2018:04:11 17:44:22+09:00
Modify Date                     : 2018:04:11 17:44:22+09:00
Producer                        : Microsoft® Word 2013

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GeoServer Spatial Extension Geo Server WPS 1.0 User Manual En V.1.la

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