PAT Plugin For QGIS User Manual

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AGRICULTURE AND FOOD

PAT - Precision Agriculture Tools
Plugin for QGIS
User Manual
Christina Ratcliff, David Gobbett, Rob Bramley
January 2019 PAT v0.1.0

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 1

Citation
Ratcliff C, Gobbett D, Bramley R (2019) Precision Agriculture Tools (PAT) plugin v0.1.0 for QGIS: User
Manual. CSIRO, Australia.

Copyright
© Commonwealth Scientific and Industrial Research Organisation 2018. To the extent permitted by law, all
rights are reserved and no part of this publication covered by copyright may be reproduced or copied in any
form or by any means except with the written permission of CSIRO.

Important disclaimer
The notes and software described here are based on a number of technical, circumstantial or otherwise
specified assumptions and parameters. The user must make their own assessment of the suitability for use
of the information or material contained in or generated from these notes. To the extent permitted by law,
CSIRO excludes all liability to any party for expenses, losses, damages and costs arising directly or indirectly
from using these notes and software tools.

Enquiries
Contact PAT@csiro.au for queries about the tools described in this manual.

2 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Contents
PAT - Precision Agriculture Tools .............................................................................................................. 4
1

Installing, Upgrading and Uninstalling ......................................................................................... 7
1.1

License .......................................................................................................................... 7

1.2

Requirements ............................................................................................................... 7

1.3

Installing PAT ................................................................................................................ 8

1.4

Update PAT ................................................................................................................. 13

1.5

Uninstall PAT............................................................................................................... 14

Individual Tools ......................................................................................................................... 15
2.1

Create Block Grid ........................................................................................................ 15

2.2

Clean, Trim, Normalise Point Data ............................................................................... 16

2.3

Run Kriging Using VESPER ............................................................................................ 20

2.4

Import VESPER Results ................................................................................................ 24

2.5

Create Polygon from On-The-Go GPS Point Trail Data .................................................. 25

2.6

Rescale or Normalise a Raster ..................................................................................... 29

2.7

Generate Random Pixel Selection................................................................................ 30

2.8

Extract Pixel Statistics for Points .................................................................................. 31

2.9

Calculate Image Indices for Blocks ............................................................................... 34

2.10

Resample Image Band for Blocks ................................................................................. 37

2.11

Create Zones with k-means Clusters ............................................................................ 40

2.12

Create Strip Trial Points ............................................................................................... 42

2.13

Whole-of-block Analysis .............................................................................................. 44

2.14

Settings ....................................................................................................................... 48

Technical Notes ........................................................................................................................ 49

How-To’s .................................................................................................................................. 50
4.1

Create a block boundary polygon from a CSV of GPS collected points .......................... 50

4.2

Loading PAT Symbols into QGIS ................................................................................... 52

4.3

Analysing strip trial data using the moving window t-test ............................................ 54

Contributors ............................................................................................................................. 55

Acknowledgments .................................................................................................................... 55

References ................................................................................................................................ 56

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 3

PAT - Precision Agriculture Tools
The Precision Agriculture Tools (PAT) plugin is a suite of open source tools developed by CSIRO for Precision
Agriculture (PA) data analysis. The tools run within Quantum Geographic Information System (QGIS) version
2.18 (QGIS Development Team 2017), a free and open-source desktop geographic information system that
supports viewing, editing, and analysis of geospatial data. PAT aims to provide an easy-to-use interface for
processing PA data through an established workflow developed for constructing maps using on-the-go data
(e.g. from yield monitors or EM38 soil surveys) as shown in Figure 1 and Table 1 (Bramley and Williams
2001; Taylor et al. 2007; Bramley et al. 2008; Bramley and Jensen 2014). It also includes tools for analysis of
remotely sensed imagery and some on farm experiments and for clustering map layers to create potential
management zones. Over time more tools and ‘how-to’ instructions will be added to expand the
functionality and usefulness for both practical and research purposes.

Create block
boundary
GPS block points
Create
block grid
Create polygon
from on-the-go
data (cereal crops)

Run kriging
using
VESPER

VESPER

Raster

(Minasny
et al. 2005)

Block
boundary
Clean, trim, &
normalise data

On-the-go
data

Create rasters
from VESPER
results
Legend
PAT preferred tool
Process external to QGIS
How-to instructions
Datasets
Alternative method

Figure 1 The basic map production workflow used in PAT and some of the existing tools available for processing on-the-go
data.

4 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Table 1 Brief description of tools available in PAT
PAT TOOLS

DESCRIPTION
Convert polygon features (e.g. a block boundary – see page 50) to

Create Block Grid

 a TIFF raster and
 a VESPER text grid file of X,Y point values used by VESPER.

Clean, Trim,
Normalise Point
Data

Process an on-the-go data file (e.g. from yield monitors) by applying clipping,
cleaning and filtering rules and output as a CSV file.

Run Kriging Using
VESPER

Create a VESPER control file and data files and run VESPER kriging.

Import VESPER
Results

Convert VESPER outputs to raster TIFF format.

Create Polygon
from On-The-Go
GPS Point Trail Data

Generate a polygon block boundary from on-the-go data (e.g. from yield
monitors) containing GPS points. The GPS points must cover the entire block
(not just be a set of points around the boundary - see page 50for instructions
on creating a boundary from a set of surveyed data points)
Create rasters by

Rescale or
Normalise a Raster



rescaling (standardising) values between a fixed range (i.e. 0-1, or 0255)



normalising values to a mean of 0 and standard deviation of 1

Generate Random
Pixel Selection

Generate a selection of random pixels from a raster and save to a points
Shapefile.

Extract Pixel
Statistics for Points

Extract pixel statistics using a square neighbourhood footprint from multiple
rasters at set locations.

Calculate Image
Indices for Blocks

Resample and smooth imagery to a larger pixel size, as well as calculate
indices such as PCD and NDVI.

Resample Image
Band for Blocks

Clip imagery to one or more blocks and resample to a different pixel size.

Create Zones with kmeans Cluster

Create zones with k-means clustering
Tool for analysing simple strip-based experiments.

Create Strip Trial
Points

It generates pairs of points from a central line within a strip and offset at a
distance outset the strip. These points can be used for the comparison of
performance along and adjacent to a strip trial (such as an N-rich strip) using
the Lawes and Bramley (2012) moving window t-test method.

Whole-of-block

Analyse whole-of-block experiments where 2 or 3 treatments are applied
across a block or paddock.

Settings

User settings for PAT. Provides the ability to set data directories and the
location of VESPER (if installed).

About

About Precision Agriculture Tools (PAT). This provides information on the
currently installed release, and relevant open source licences.

Help

Display the PAT user manual.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 5

PAT Toolbar

PAT Menu

PAT Log Messages

Figure 2 PAT toolbar, menu and log messages panel within QGIS

6 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

1 Installing, Upgrading and Uninstalling
1.1 License
The PAT plugin for QGIS is free to download and use under a GPL V3 Open Source license. PAT license
details can also be found in the About tool under PAT menu. The companion Python library ‘pyprecag’ is
also freely available and is released under the CSIRO Open Source Software License Agreement (variation of
the BSD / MIT License). All source code and license files are available from https://github.com/CSIROPrecision-Agriculture.

1.2 Requirements
VESPER: To use the Run Kriging Using VESPER tool requires installation of VESPER (note: only available for
Microsoft Windows operating systems). VESPER is a kriging (map interpolation) program (Minasny et al.
2005). It needs to be installed independently if you would like to undertake kriging of maps using VESPER.
VESPER is not distributed with this plugin but is the recommended map interpolation tool. To download or
view more information on VESPER visit https://sydney.edu.au/agriculture/pal/software/vesper.shtml.
R 3.5.1+: The R statistical language (R Core Team 2018) is required to carry out the analytical processing for
the Whole-of-block Analysis (Section 2.13). R is not distributed with this plugin. If Whole-of-block analysis
is required then you must download and install R in addition to QGIS. The minimum R version suitable for
this is v3.5.1 Configuring QGIS to use R section on page 11.
QGIS LTR 2.18.21-26: Download and install the QGIS standalone long term release (versions 2.18.21 to
2.18.26). Note that the PAT tools do not currently work with QGIS version 3 or later.
QGIS 2.18.26 can be downloaded directly using these links.
32bit : http://download.osgeo.org/qgis/win64/QGIS-OSGeo4W-2.18.26-1-Setup-x86.exe
64bit: http://download.osgeo.org/qgis/win64/QGIS-OSGeo4W-2.18.26-1-Setup-x86_64.exe
Additional Python Packages: QGIS includes Python and numerous Python packages. However, PAT requires
the following additional packages: pyprecag, Fiona (Gilles et al 2011) and Rasterio (Gilles et al 2013). The
Fiona and Rasterio packages have been bundled with the PAT plugin and instructions on how to install
them are included.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 7

1.3 Installing PAT
Connect to the CSIRO Cloudstor Plugin Repository
1.
2.
3.
4.
5.
6.

In QGIS open the plugin manager (Plugins Menu → Manage and Install Plugins)
Select the Settings Section.
Tick Check for Updates and Show Experimental Plugins options.
Click Add
Enter the Name:
CSIRO CloudStor Plugins.
Enter the following URL:
https://cloudstor.aarnet.edu.au/plus/s/vcIopbrD8KnMdbI/download

7. Leave authentication blank
8. Click OK.

Install the PAT - Precision Agriculture Tools Plugin.
1. In QGIS open the plugin manager.
Plugins Menu → Manage and Install Plugins
2. Select the All or Not installed section.
3. Search for and select PAT - Precision Agriculture Tools.
4. Click Install plugin.
You will receive an Failed Dependency Check message box and Error loading plugin messages. This is
expected, and is resolved by completing the next section titled Installing or Upgrading PAT Python
Dependencies.

8 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

4.
Installing or Upgrading PAT Python Dependencies
While installing or upgrading PAT, a check will be completed to ensure the required Python packages are
installed on your system. If any of the images below appear, then this check has failed. This is normal.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 9

If the following message appears click No.

Click No

Steps to install dependencies.
1. Close QGIS and go to your windows desktop.
2. A shortcut has been created on your desktop named Install_PAT_Extras.
Double click the shortcut to run it.
3. Choose YES for the Windows Account Control and any other messages which
may appear.
4. Restart QGIS. The check will run again to ensure the installation occurred correctly.
If the PAT menu and toolbar are not present then reinstall and/or check/activate PAT using the plugin
manager. QGIS should now contain the PAT menu, toolbar and log panel similar to Figure 2 on page 6.
PAT has now been successfully installed.

10 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Configuring QGIS to use R
If R is not installed and you launch the Whole-of-block analysis tools via the menu or toolbar you will a
warning message as shown.

To resolve this, complete the following steps to configure R and QGIS

1. Download R from Windows version can be downloaded from http://r-project.org/ . The
minimum R version suitable for this is v3.5.1.
2. Install using all the default options
3. If required, activate the Processing plugin in QGIS plugin manager.
a. In QGIS open the plugin manager.
Plugins Menu → Manage and Install Plugins
b. Select the Installed section
c. Find Processing and ensure the adjacent checkbox is ticked.
d. Close the Plugins dialog.
This will give you a processing menu and the processing side panel.

4. From the Processing menu select Options.
a. Expand Providers
b. Expand R scripts
c. Tick on Activate
d. Ensure that the R installation folder is shown against R folder
e. Click OK.

When clicking OK you may get a Wrong value error message like this
PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 11

and your mouse cursor will remain a circle. To resolve treat the mouse circle as an arrow and

1. Under Providers, expand GRASS commands
2. Double click the text to the right of Msys folder, select and delete it and press the enter
key.

3. Click OK
4. Close and re-open QGIS to reset your mouse cursor.
It should now all work.

12 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

1.4 Update PAT
If the Check for Updates option is checked on in the plugin manager, QGIS will advise the user if new
plugins are available, or if installed plugins have been updated. This notification is displayed in the QGIS
interface’s status bar as shown below. It is recommended that Check for Updates is checked.

To Update
1. In QGIS open the Plugin Manager by clicking on the link in the status bar or via Plugins.
Menu → Manage and Install Plugins
2. Either select the Upgradeable left side tab or search for your plugin.
3. Upgrade by selecting the PAT plugin and click Upgrade plugin
A check will be run to ensure the Python packages required by PAT are installed and are of the correct
version. If this check fails follow the instructions in Installing or Upgrading PAT Python Dependencies to
upgrade the dependencies.

2.
.

3.
.

1.
.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 13

1.5 Uninstall PAT
If you wish to uninstall PAT and its Python dependencies you must first uninstall the Python dependencies,
followed by the plugin as instructed below.

1.5.1 Uninstall PAT Python dependencies for all users.
1. Navigate to the current user’s PAT installation directory. This folder is listed in as Plugin Dir in the
settings dialog as shown highlighted in yellow below.

2. Find the UnInstall_PAT_Extras.bat file in the python_packages folder.
3. Right click the file and select Run as Administrator and choose Yes for any messages which appear.

1.5.2 Uninstall PAT Plugin.
PAT Python dependencies should be uninstalled PRIOR to uninstalling the PAT plugin. The plugin can be
uninstalled in one of two ways.
1. Via the QGIS Plugin Manager
a. In QGIS, open the plugin manager, and find the PAT plugin.
b. Click Uninstall plugin.
2. Via Windows Explorer.
a. Navigate to the current users PAT installation directory as show in 1.5.1.1 above.
b. Delete the entire pat folder.

14 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

2 Individual Tools
2.1

Create Block Grid

Summary
This tool converts polygon features such as a block boundary to a raster grid using a set pixel size. This is a
critical part of setting up the analysis environment for creating maps from on-the-go data because it
generates the base grid onto which maps will be interpolated, by using the outer most extent of the block
boundary as the ‘frame’ for the grid. Page 50 details how to generate a block boundary if one is not already
available.
The raster outputs created by the Block Grid tool are:


a TIFF raster and



a grid file of X,Y point values used by VESPER for kriging.

Areas inside the polygon boundary will be assigned a value of 1 while areas outside will be assigned a nodata value of -9999.

Dialog

Block Grid (Polygon to Raster)
Select a polygon
layer
Use selected
features

A layer containing the block boundary polygon features in a projected coordinate
system to be converted to the raster outputs.
Default is
unchecked

If checked, will only use the selected features, if unchecked, all the features will be
used. Useful in creating a grid for a single field from a boundary layer comprising
more than one field.
The pixel size to assign to the raster outputs. This is expressed in metres.

Pixel size (m)

0.00m to 6 km
Default is 2 m

Recommended Values:
Viticulture: 2 m
Sugarcane: 2 m
Broadacre grains: < 200 ha 5 m
> 200 ha 10 m

Snap extent to
factor of pixel Size

Default is
checked

Snap the output raster extent to a factor of the pixel size. This will ensure adjacent
rasters use a common origin which is important for future analysis.

Save as TIFF raster

Default derived
from input layer

The output raster TIFF file to be created.
The VESPER grid file will have a suffix of _v.txt

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 15

2.2

Clean, Trim, Normalise Point Data

Summary
This tool processes on-the-go data files (e.g. from a yield monitor or EM38 soil survey) containing GPS
coordinates recorded as latitude and longitude in decimal degrees, to output point values in a projected
coordinate system. The tool also applies cleaning and filtering rules.
This tool:


retains all columns (except coordinate columns) from the original file.



converts coordinate columns to a projected coordinate system and renames them to Easting and
Northing. An additional column (EN_EPSG) will be created and assigned the EPSG number for the
projected coordinate system used to reproject data. An EPSG number is an international numbering
system for coordinate systems (see http://www.epsg.org/)



optionally saves a Shapefile version matching the output CSV file. A second Shapefile will also be
saved containing the string _removed in its filename. This Shapefile will contain all the points the
filter discards and will be attributed by filter type. The description of the values can be found in
Table 2

This tool filters data by:


optionally clipping the data to a Shapefile boundary (i.e. removes points that lie outside the
boundary)



optionally removing values from a given column which are null (missing) or are less than or equal to
zero



creating a normalised column using a prefix of nrm_ and calculating normalised values for the data
such that their mean is zero and standard deviation is 1. The normalised value of column Z is
calculated as (Z - mean(col Z))/(s.d.(col Z))



optionally trimming normalised outliers based on a set number of standard deviations. This trim
can optionally be performed iteratively with the normalised value re-calculated for each iteration.
It is recommended that, by default, normalised data are trimmed to +/- 3 standard deviations.



optionally thinning the data by removing points that are closer together than a set distance. For
data that have been georeferenced using a differential GPS, we recommend removing points that
are closer than 1 m apart.

As part of the filtering process, the tool may rename some data columns to adhere to Shapefile column
name limitations. The new names are displayed as a PAT log message and written to the log file. For more
information on the location of the saved log file and temporary folder refer to the Technical Notes section
on page 49.

Once processing is complete, the results of filtering are shown as a PAT log message. Only filters which
remove points are listed. When iteratively filtering, results of all iterations are shown. An explanation of
these is shown in Table 2.

16 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Dialog

Choose whether to use GPS data currently loaded in QGIS as a Points Layer
Select points layer:
Use selected features

A point layer currently loaded in QGIS.
Default is
unchecked

If checked, use only the selected features
to generate a polygon
If unchecked, all the features will be used

Or alternatively using a delimited text file
Filename

Options
include XLS,
TXT, CSV

The filename of the table file.
The sheet containing data. If the file type
doesn’t support sheets, then the filename
will be used.

Sheet

Layer name

Default is the
sheet name.

The QGIS layer name for the output point
and/or polygon files.

Number of lines to
ignore

Default is 0

The number of lines at top of file to
ignore. Can be used for skipping header
text.

The tool will
display a guess
of these
columns

The columns representing the X and Y
coordinates within the input file.

X column
Y column

The coordinate system of the XY columns.

XY columns
coordinate system

Clip polygon layer

Note: GPS most commonly record data in
WGS 1984 (EPSG: 4326)

Default is
unchecked

A layer containing polygon features used
to clip the points data.
Any points that fall outside the polygon
features will be removed.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 17

Use selected features

Default is
unchecked

Column to process
Remove values less
than or equal to 0

Clean values using X
standard deviations

Iteratively

Remove points
within X metres of
another
Save CSV file

Save as point
Shapefile

If checked, use the selected features to
clip the input points.
If unchecked, all the features will be used.
The column to normalise, trim and clean.
If checked, rows from the chosen column
will be removed where the value is null or
less than or equal to zero.

Default is
checked
0.00 to 5.00
Default is 3
Use 0 to omit

Points where the normalised value is
outside a set number of standard
deviations will be removed.
Clean the points iteratively using the set
number of standard deviations until all
values are within +/- the set standard
deviation.

Default is
checked
0.00 to 20.00
Default is 1
Use 0 to omit

Any points spaced at less than this
distance apart will be removed.

Derived from
layer name

The name and path of the output CSV file
containing the final data points.

Default is
unchecked.

If checked, save a Shapefile version of the
output CSV file.

Derived from
layer name

A second point Shapefile will be saved
with a suffix of _removed containing the
points discarded and attributed by a filter
column.

Projected coordinate
system

The output projected coordinate system
of the Shapefile.
If Auto detect is checked the following rules will apply:

Auto detect WGS84
UTM zone

Will try to match the input if it is a projected
coordinate system

If the inputs are in Geographic’s (lat/long) it will
calculate the relevant UTM Zone

Note: If in Australia then MGA GDA 1994 zones, will be used
– see Figure 5 on page 49.

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Notes
Table 2 A description of the filter type used when reporting filtering results.
ORDER FILTER TYPE

DESCRIPTION

clip

Points removed when clipping by a polygon.

zero

Nulls and/or Zeros removed.

3.0 std iter 1

Points removed during the standard deviation (std) iteration (iter) number 1 and uses 3 standard
deviations.

3.0 std iter 2

Points removed during the standard deviation (std) iteration (iter) number 2 and uses 3 standard
deviations.

3.0 std iter 3

Points removed during the standard deviation (std) iteration (iter) number 3 and uses 3 standard
deviations.

pointXY (1.0 m)

Points removed which are spaced at less than the specified distance apart, in this case 1m

pointX (1.0 m)

Points removed after sorting by the X coordinate, which are spaced at less than the specified
distance apart, in this case 1 m

pointY (1.0 m)

Points removed after sorting by the Y coordinate, which are spaced at less than the specified
distance apart, in this case 1 m

Pts remaining

The number of points left after filtering occurs.

Total

The total number of points in the dataset



The following notification occurs when a delimited text file contains invalid characters in a column
name. A copy of the file with corrected column names will be made in the PAT temporary folder
(location shown in PAT log message). For more information on the location of the saved log file and
temporary folder see the Technical Notes section on page 49.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 19

2.3

Run Kriging Using VESPER

Summary
This tool is used for mapping on-the-go data, such as are collected by a yield monitor or an EM38 soil
survey, following established protocols (Bramley and Williams 2001; Taylor et al. 2007; Bramley et al. 2008;
Bramley and Jensen 2014) using local block kriging. It will create a VESPER control file and collate the files
required for kriging. The following files will be created in a VESPER sub-folder located in the specified
output folder.


the VESPER control file. The control filename will be used as a base to derive other VESPER output
files like the kriged map result.



a subset of data to krige. All non-required columns are deleted.



a Windows batch file (Do_VESPER.bat) which can be used to launch VESPER processing for all
control files in the VESPER sub-folder. This process can be run outside of QGIS and the
Python/pyPrecAg environment.

Any files matching the control file name will be deleted from the VESPER sub-folder including VESPER
kriged results, to ensure that the files remaining belong to the newly create control file. If you want to
retain old versions, use a different name for the control file.
The coordinate system of the CSV file will be determined by interrogating the EN_EPSG or ENEPSG columns
generated as a by-product of running the Clean, Trim, Normalise Point tool. If the resulting value cannot be
found or is incorrect, the coordinate system can be set manually. The resulting EPSG number will be stored
within the control file and later used when converting VESPER outputs into raster TIFF format.
To krige (run) VESPER control files from within QGIS, VESPER must already be installed on the PC and
configured in the PAT settings (see Settings Tool on page 48).
If the Run VESPER Kriging Now option is checked the output control file will be launched in VESPER and
kriged immediately. Running this tool multiple times will add each output control file to the VESPER queue
and run consecutively. The QGIS status bar is used to manage the queue; currently the queue can only be
displayed and cleared. On the completion of each VESPER run, if the Convert VESPER Files to Raster and
Load in QGIS option is checked the kriged results will be import to TIFF files and loaded into QGIS.
If the Run VESPER Kriging Now option is unchecked the tool will create the VESPER control, data and batch
files in the selected folder allowing the user to run VESPER in their own time.
When Run VESPER Kriging Now or Convert VESPER Files to Raster and Load in QGIS options are unchecked
the Import VESPER Results (post VESPER) tool can be used to import VESPER kriged results to TIFFs then
loaded into QGIS.

20 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Dialog

Cleaned and
trimmed CSV file

A CSV file containing the data to krige.
Use the Clean, Trim, Normalise Point tool to generate this
input.

This is the coordinate system of the coordinate columns in
Coordinate system the CSV file.
for CSV file:
By default the value of the EN_EPSG or ENEPSG column in
the input CSV file will be used.
Krige column

The column containing values to krige.
The value in meters to set as the block
size when using block kriging in VESPER.
0 to 1000
Default is 10

Block kriging size

Use 0 for
Punctual
Kriging

This value should be approximately 5
times the pixel value.
Recommended Values:
Viticulture:
10 m
Sugar:
10 m
Broadacre grains:
< 200 ha 30m
> 200 ha 60 m

VESPER grid (block
grid) file

The VESPER grid file representing the area
to be kriged. Use the Create Block Grid
Tool to generate this input.

VESPER output
folder

The output folder for the VESPER files. A
sub-folder called VESPER will be created if
required.

VESPER control
filename

The name to use as the VESPER control
file. This will be appended to the output
folder.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 21

Auto create
control file name

If checked, the name will be generated from the first 20
characters of the input CSV file, the string ‘control’ and the
Krige column.
Uncheck this option to prevent manual edits from being
overwritten when changing source CSV file or Krige column.

Configure to show
VESPER graph and
map graphics
while kriging

Default is
unchecked

Checking this option will display the map
and graph while VESPER is running but
will increase the processing time.

Run VESPER
kriging now

Default is
checked

Add the control file to the VESPER Queue
for processing.

Convert VESPER
Files to Raster and
Load in QGIS

Default is
checked

On completion of VESPER processing,
convert the outputs to raster TIFF
formats.

File Naming Conventions



<> denotes an existing element or input
non-alphanumeric characters are removed with the exception of hyphens (-) and underscores ( _ ).

DESCRIPTION

FILENAME

EXTEN
SION

EXAMPLE

Files required by VESPER and copied to the VESPER output folder
VESPER control file
VESPER grid file

_< first 10 characters of krige column>_control
where control is replaced by vespergrid

.txt
.txt

swblock_YldMassDry_control.txt
swblock_YldMassDry_vespergrid.txt

VESPER data file

where control is replaced by vesperdata

.csv

swblock_YldMassDry_vesperdata.csv

Files created by VESPER and saved to the VESPER output folder
VESPER Krige file (contains Prediction and SE)

where control is replaced by kriged

.txt

swblock_YldMassDry_kriged.txt

VESPER parameter file

where control is replaced by parameter

.txt

swblock_YldMassDry_parameter.txt

VESPER report file

where control is replaced by report

.txt

swblock_YldMassDry_report.txt

.tif

swblock_YldMassDry_PRED.tif

If converting VESPER files to raster is checked or the Create Rasters from VESPER Results tool is used
Kriged Prediction TIFF

where kriged is replaced by PRED

22 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

source: VESPER Krige result above
Standard Error TIFF
source: VESPER Krige result above

where kriged is replaced by SE

.tif

swblock_YldMassDry_SE.tif

Confidence Interval (CI) metadata text file

where control is replaced by CI

.txt

swblock_YldMassDry_CI.txt

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 23

2.4

Import VESPER Results

Summary
This tool converts the output files generated by VESPER into raster TIFFs.
The output filenames will be created using the VESPER control file name as a base and demonstrated in the
Prepare Data for Kriging using VESPER Tool - File Naming Conventions section on page 22.
The files created include:


a TIFF file representing the predicted (kriged) value; these are the values used to generate the
resulting map.



a TIFF file representing the standard error (SE) of the kriging prediction.



a text file containing the calculated median kriging prediction SE and the 95% confidence interval
for the map. This is important information for testing the significance of the difference between
different zones when different map layers are clustered to generate potential management zones.

The coordinate system to be assigned to the rasters will be extracted from the value stored within the
control file. If the coordinate system cannot be found or is incorrect, it can be selected manually.

Dialog

Import VESPER Results
VESPER Control File:
Coordinate System
for CSV File:

A VESPER control file used to identify VESPER results files and convert to rasters.
This is the coordinate system of the VESPER results.
By default it is
extracted from the
input control file.

24 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

2.5

Create Polygon from On-The-Go GPS Point Trail Data

Summary
Having a block boundary polygon is central to many of the PAT processing steps. Boundary polygons are
used to constrain data to a fixed extent. It is preferably that a boundary polygon is created by collecting
accurate GPS points around the block and editing them in QGIS to create polygons (refer to How-To Create a block boundary polygon from a CSV of GPS collected points on page 50 for instructions on this
method). However, if accurate GPS data for the boundary is not available, then a less accurate block
boundary polygon can be created using this tool, based upon a file of on-the-go GPS points (i.e. from a yield
monitor or EM38 survey data). Note that this method is not preferred, but the tool is provided as a ‘quick
fix’ for those wishing to generate maps in the absence of surveyed block or field boundaries.
As the process involves a dot-to-dot approach, it is critical that the input file of points are in order (i.e.
sorted by an increasing time sequence - as would be normal for data collected by an on-the-go sensor such
as yield monitor). For efficiency, points can be thinned by removing points closer than a set distance apart
as justified by the accuracy of the GPS. Resulting points will be connected to form lines and then converted
to polygons.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 25

Dialog

Choose whether to use GPS data currently loaded as a QGIS Points Layer
Use selected
features

If checked, only uses the selected
features to generate a polygon.

Or alternatively using a delimited text file
Filename

Options include
XLS, TXT, CSV

The sheet containing data. If the file type
doesn’t support sheets, then the filename
will be used.

Sheet

Layer name

Default is the
sheet name.

The name used when displaying QGIS
layers, and as the default value for the
output point and/or polygon files.

Number of
lines to ignore

Default is 0

The number of lines at top of file to
ignore. Can be used for skipping header
text.

By default will
attempt to match
to X,Y, longitude,
latitude; lon, lat
etc.

The columns representing the X and Y
coordinates within the input file.

X column
Y column

XY columns
coordinate
system
Save point trail Default is
to file
unchecked

26 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

The filename of the table file.

The coordinate system of the XY Columns.
Note: GPS normally records data in WGS
1984 (EPSG: 4326)
If checked, save the input delimited file as
a points Shapefile in the output
coordinate system.

Thin distance
(m)

0.00 to 100.00
Default is 1
Use 0 to omit

Aggregate
distance (m)

0.00 to 100.00

Buffer
distance (m)

0.00 to 100.00

Shrink
distance (m)

0.00 to 100.00

Polygon file

Default is 25

Default is 10

Any points spaced at less than the
minimum distance apart will be removed.
The maximum distance between points
used to separate strings of connected
points into individual lines.
Typically this is slightly larger than the
row/swath width.
A distance in meters used to buffer the
lines to create overlapping polygons.
Typically this is half the row/swath width.
A distance in meters used to shrink the
overlapping polygons after dissolving.

Default is 3

Typically this is slightly less than the
buffer distance.

Derived from layer
name

The output filename for the polygon
Shapefile.

Projected
coordinate
system

The output projected coordinate system
of the Shapefile.
If Auto detect is checked the following rules will apply:

Auto detect
WGS84 UTM
zone

Will try to match the input if it is a projected
coordinate system

If the inputs are in Geographic’s (lat/long) it will
calculate the relevant WGS84 UTM Zone

Note: If in Australia then MGA GDA 1994 zones, will be used –
see Technical Notes on page 49.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 27

Notes


The following notification occurs when a delimited text file contains invalid characters in the
column name. A copy of the file will be made in the PAT temporary folder containing corrected
column names as specified in the PAT log message and to file. For more information on the location
of the saved log file and temporary folder see the Technical Notes section.



A warning is triggered when the resulting polygon is considered stripy or noisy. This can usually be
corrected by increasing the buffer and shrink distances.



The following error is caused when the wrong coordinate system is applied to the input source file
or layer. Thinning and/or clipping will result all points being removed leaving no points for further
processing

28 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

2.6

Rescale or Normalise a Raster

Summary
This tool rescales or normalises a raster and outputs to a new TIFF file. Existing no-data values will be
ignored in any calculation.


Rescale will adjust the raster between the specified values (e.g. output values all in the range 0 to
1)



Normalise will adjust the raster to a mean of zero and standard deviation of one

Such re-scaling is useful when you wish to compare several map layers, for example, yield maps for several
years.

Dialog

Rescale or normalise a raster
Select a raster layer
for band X

Default is band 1

The raster layer and band to rescale or normalise.
Options:

Method

Rescale between
(when selected)
Save as Shapefile

Default is rescale



Rescale – adjust values to a fixed range



Normalise – adjust values to a mean of zero and a standard deviation of
one

Default 0 to 255

The range of values used with rescaling.

Default will be
derived from the
input layer name

The output Shapefile to be created.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 29

2.7

Generate Random Pixel Selection

Summary
This tool is used to select randomly distributed pixel locations from an existing raster and save them to a
point Shapefile. Pixels will be selected from areas inside the raster extent which contain valid data. The
resulting points will be located in the centre of the chosen pixel and the output shapefile will contain
columns representing the X and Y coordinates. This tool provides the key location input for the Extract Pixel
Statistics for Points tool described on the following page.

Dialog

Generate random pixel selection
Generate random
sample pixels

Default is band 1

The raster to use as the base for selecting pixels. No-data pixels will be exempt
from selection.

Select a raster layer

Save as Shapefile

The number of pixels to randomly select

Default will be
derived from the
input layer name

The output Shapefile to be created.

30 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

2.8

Extract Pixel Statistics for Points

Summary
Extract pixel statistics for points is used to extract pixel statistics from multiple rasters using a pre-defined
set of points. These points could be identified using the Generate Random Pixel Selection tool described on
the previous page. Statistics are calculated on pixel values within a square neighbourhood and extracted to
a CSV file. This tool is useful when relationships are being sought between different maps layers – for
example, a regression or correlation analysis between yield and soil map data.
Applying a neighbourhood filter to rasters is useful for removing (smoothing) small anomalies introduced
from instrument inaccuracies or on-the-go movement. The neighbourhood consists of a centre pixel and a
number of pixels forming a square around the central pixel, as shown in Figure 3.
9
7

x
9
x
7
5
x
5
3 x 3
C

Figure 3. A representation of the
3x3, 5x5, 7x7, 9x9 neighbourhood
size around a central pixel (C) as is
used when calculating filtered
statistics.

For example, a mean statistic for a 3x3 neighbourhood on 2 m pixels, will
calculate the mean of the central pixel (red) and the surrounding 3x3
area of 8 pixels (yellow) equating to 36 m2 on ground.
Pixels designated no-data will be excluded from the statistical
calculation. However, a central no-data pixel may be assigned a value if
at least one pixel in the neighbourhood has a valid value.
Currently, the statistical methods supported by this tool are: mean,
standard deviation, co-efficient of variation (CV), minimum, maximum
and a count of pixels contributing to the statistical calculation.
The output values are saved to a CSV data file. Column names for each
raster and statistic combination are explained below.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 31

Dialog

A point layer in QGIS used to extract pixel
statistics values.

Select point layer
Use selected
features

Default is
unchecked

If checked, extract pixel values only for
the selected points. If unchecked, all the
points will be used

The raster layer to extract values from.
Only raster layers of the same pixel size can be analysed at
a time and this is set by the first raster layer added.
Use raster layer

The Add, Delete, Move Up, Move Down, buttons can be
used to manage the list of rasters.
The order of rasters is retained in the output CSV file with
separate columns for each raster and statistic combination.

Select the required statistical methods for each raster in
the list.
Calculate pixel
neighbourhood
statistics

Current pixel just extracts the pixel value
and/or
Statistics to be calculated using the set neighbourhood size.
The output column naming format is explained below.

Neighbourhood
size (pixels)

Save CSV file

32 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Default is
3x3

The size of the neighbourhood footprint
to use while calculating statistics.

Derived from
layer name

The name and path of the output CSV file
containing the final data points.

File and Column Naming Conventions



<> denotes an existing element or input
non-alphanumeric characters are removed with the exception of hyphens (-) and underscores ( _ ).

Output Filenames:
CSV filename

_pixelvals.csv

Column Names:
NAMING RULE

EXAMPLE

_ mean3x3_swblock_YldMassDry_PRED

EXPLANATION

The column containing values from the mean 3x3 neighbourhood filter for
the raster swblock_YldMassDry_PRED.tif.

pixel_swblock_2009YldMassDry_PRED

The column containing the pixel values for the raster
swblock_2009YldMassDry_PRED

cv5x5_seblock_2014YldMassDry_PRED

The column containing values for coefficient of variation (CV) 5x5
neighbourhood filter for the raster seblock_2014YldMassDry_PRED.tif

pixelcount7x7_swblock_2024YldMassDry_PRED

Column containing values representing the count of pixels used for
statistical calculations with a 7x7 neighbourhood filter for the raster
seblock_2014YldMassDry_PRED.tif

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 33

2.9

Calculate Image Indices for Blocks

Summary
Many providers of remotely sensed imagery deliver data to clients as multi band files. The Calculate Image
Indices for Blocks tool is used to calculate indices for a multi band image and aligns the output to the extent
and pixel size of a block grid. Indices currently supported are Normalised Difference Vegetation Index
(NDVI); the ‘simple ratio’ or Plant Cell Density index (PCD); Green Normalised Difference Vegetation Index
(GNDVI); Chlorophyll Red-Edge index (CHLRE); and Normalised Difference Red-Edge index (NDRE).
Table 3 describes how these indices are calculated.
Each band in the image file is mapped to a spectral band e.g. Red, Red-edge, Near Infrared and is then used
to calculate relevant image indices. In the case of vineyard data, if a non-vine mask is present in an existing
band of the image, it can be used to remove non-vine signals prior to the resampling and alignment to the
block grid. This will ensure that spectral signatures relating to ground cover are excluded from the resulting
image outputs. This non-vine masking is not relevant for broadacre crops.
An optional block boundary polygon layer, and a column containing the block name or ID, can be used to
separate the resulting images into individual blocks. By default, if no column is specified, then all polygons
are assumed to be from the one block and will be processed accordingly. If no block boundary layer is
specified, then a single polygon outlining the image (excluding no-data) will be used. The output from this
tool will be aligned to a block grid that will be identical to the one created separately using the Create Block
Grid on page 15.
Table 3 the list of supported indices
Normalized Difference
Vegetation Index (NDVI)

NDVI =

Green Normalized Difference
Vegetation Index (GNDVI)

Normalised Difference
Red-Edge Index (NDRE)

GNDVI =

NDRE =

Plant Cell Density Index (PCD)

Chlorophyll Red Edge Index (ChlRE)
(Gitelson 2004; Gitelson et al. 2005)

(𝑁𝐼𝑅 − 𝑅𝑒𝑑)
(𝑁𝐼𝑅 + 𝑅𝑒𝑑)

(𝑁𝐼𝑅 − 𝐺𝑟𝑒𝑒𝑛)
(𝑁𝐼𝑅 + 𝐺𝑟𝑒𝑒𝑛)

(𝑁𝐼𝑅 − 𝑅𝑒𝑑 𝐸𝑑𝑔𝑒)
(𝑁𝐼𝑅 + 𝑅𝑒𝑑 𝐸𝑑𝑔𝑒)

PCD =

𝑁𝐼𝑅
𝑅𝑒𝑑

𝑁𝐼𝑅
Chl𝑟𝑒𝑑 𝑒𝑑𝑔𝑒 = (
) −1
𝑅𝑒𝑑 𝐸𝑑𝑔𝑒

34 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Dialog

Select Image

The image layer containing the appropriate bands required
for calculate indices.

No-data value

Default from
image.

Can be used to specify a different nodata value.

Use a block
boundary

Default is
unchecked

A layer in QGIS containing polygon(s)
representing blocks.

Use selected
features

Default is
unchecked

If checked, only the selected polygons
will be used.

Block ID column

A column containing the block id or name. This will be used
treat multiple polygons with the same block id or name as
one.
The pixel size to apply to the raster
outputs. This is expressed in meters.

Resample pixel
size (m)

Specify image
bands used for
index
calculations

Recommended Values:
Viticulture: 2 m
Default is 2 m
Sugarcane: 2 m
Broadacre grains:
< 200 ha 5 m
> 200 ha 10 m
Mapping of band numbers to band types. The mapped bands
will enable/disable indices based on individual index
requirements.
0.00m to 6 km

For most images
Green is band 2, Red is band 3,
Near Infrared is band 4
Non-vine mask is a band where pixels not containing vine
signals are set to no-data. Not required for broadacre data.
The indices to calculate.

Select the indices If an index is disabled (greyed out) the bands it requires
to calculate
haven’t been mapped.
For index acronym and equation, see table above.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 35

The projected coordinate system to apply to the output files.
Projected
coordinate
system

By default it will calculate the relevant coordinate system
from the input image or block boundary’s coordinate system.
Note: If in Australia then MGA GDA 1994 zones, will be used
– see Figure 5 on page 49.
The folder to save output TIFF files.

Output folder

A folder based on the input image name will be created and
all TIFF files will be saved here.
See table below for File Naming Conventions used for output
files.

Display results

Default is
unchecked

If checked all resulting TIFF files will be
loaded into QGIS.

File Naming Conventions



<> denotes an existing element or input
non-alphanumeric characters are removed from strings with the exception of hyphens (-) and underscores ( _ ).

Filenames:
NAMING RULE

EXAMPLE

EXPLANATION

Output Folder:

\ C:\data\vineyard\rgbi_jan_50cm_84sutm54_tif

A new folder based on the image name is created in the output folder and
all created images are saved here.
In this example the image rgbi_jan_50cm_84sutm54.tif is used to create a
new folder called rgbi_jan_50cm_84sutm54_tif.

Image Names:
__.tif B1_NDVI_2m.tif
PCD_250cm.tif

36 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

The TIFF file resampled to 2m pixels for the Normalised Difference
Vegetation Index (NDVI) created for block id/name of B1.
The TIFF file resampled 250cm pixels for the Plant Cell Density (PCD) Index
created without specifying a block id column.

2.10 Resample Image Band for Blocks
Summary
Resample Image Band for Blocks is used to resample, align and smooth an existing band of an image to
match a block grid.
An optional block boundary polygon layer and a column containing the block name or ID, can be used to
separate the resulting images into individual blocks. By default, if no column is specified, then all polygons
are assumed to be from the one block and will be processed accordingly. If no block boundary layer is
specified, then a single polygon outlining the input image will be used.
The output from this tool will be aligned to a block grid that will be identical to the one created separately
using the Create Block Grid on page 15.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 37

Dialog

Select Image

The image layer containing the band to resample.

No-data value

Default from
image.

Can be used to specify a different no
data value.

Use a block
boundary

Default is
unchecked

A layer in QGIS containing polygon(s)
representing blocks.

Use selected
features

Default is
unchecked

If checked, only the selected polygons
will be used.

Block ID column

A column containing the block id or name. This will be used
treat multiple polygons with the same block id or name as
one.
The pixel size to apply to the raster
outputs. This is expressed in meters.

Resample pixel
size (m)

0.00m to 6 km
Default is 2 m

Recommended Values:
Viticulture: 2 m
Sugarcane: 2 m
Broadacre grains: 5 m for fields <
200 ha; 10 m for larger fields.

The projected coordinate system to apply to the output files.
Projected
coordinate
system

By default it will calculate the relevant coordinate system
from the input image or block boundary’s coordinate system
and extent coordinate system.
Note: If in Australia then MGA GDA 1994 zones, will be used
– see Figure 5 on page 49.
The folder to save output TIFF files.

Output folder

A folder based on the input image name will be created and
all TIFF files will be saved here.
See table below for File Naming Conventions used for output
files.

Display results

38 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Default is
unchecked

If checked all resulting TIFF files will be
loaded into QGIS.

File Naming Conventions



<> denotes an existing element or input
non-alphanumeric characters are removed from strings with the exception of hyphens (-) and underscores ( _ ).

Filenames:
NAMING RULE

EXAMPLE

EXPLANATION

Output Folder:

\ C:\data\vineyard\area1_rgbi_jan_50cm_84sutm54_tif

A new folder based on the image name is created in the output folder and
all created images are saved here.
In this example the image area1_rgbi_jan_50cm_84sutm54.tif is used to
create a new folder called area1_rgbi_jan_50cm_84sutm54_tif.

Image Names:
__.tif B1_Band6_2m.tif
Band7_250cm.tif

The TIFF file where Band 6 is resampled to 2m for block id/name of B1.
The TIFF file where Band 7 is resampled 250cm pixels without specifying a
block id column.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 39

2.11 Create Zones with k-means Clusters
Summary
This tool allows zones to be created by performing k-means clustering on multiple rasters (i.e. map layers)
to create clusters of similarity by minimising variability within clusters while maximising variability between
clusters. If significant differences between clusters are observed then the clustered results can be used as
potential management zones.
Raster files with the same single pixel size, and coordinate systems are used as inputs and the common
area of overlap will be used to generate an output TIFF containing the clustered result.
On completion of k-means clustering, the mean and standard deviation for each zone/cluster and source
raster combination will be calculated and written to a CSV File alongside the output TIFF file as well as
being displayed in PAT’s log messages panel.

Dialog

Create zones with k-means clustering
The raster layer to extract values from.
Use raster layer:

Only raster layers of the same pixel size can be analysed at a time. The first raster layer added sets both
the pixel size and the output coordinate system.
The Add, Delete, Move Up, Move Down, buttons can be used to manage and order the list of rasters.
The order of rasters is retained in the output CSV file with separate columns for each raster and statistic
combination.

Number of clusters:

Default is 3

The number of clusters/zones to create. Aside from trying 3, it is recommended that
users also try 2 clusters. 4, 5 or an even larger number of clusters may also be
appropriate.

The name and path of the output TIFF file representing the zones.
Save TIFF file

In addition, a statistics CSV file will be written to disk along with the TIFF, and results printed to PAT’s log
messages panel.

40 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

File and Column Naming Conventions



<> denotes an existing element or input
non-alphanumeric characters are removed from strings with the exception of hyphens (-) and underscores ( _ ).

FILENAMES:
Output TIFF
Naming Rule:

k-means_clusters_rasters_.tif

Example:

k-means_3clusters_5rasters_2m.tif

Description:

A 2m pixel TIFF file for 3 k-means clusters using 5 input rasters

Output Statistics CSV

< output TIFF name> where .tif is replaced by _statistics.csv

CSV COLUMN NAMES:
Naming Rule:

Example:

swblock_2024YldMassDry_PRED_std

Description:

The standard deviation value for swblock_2024YldMassDry_PRED.tif for the corresponding
cluster/zone.

Notes


To successfully use this tool, all input raster files must contain the coordinate system internal to the
file. When a file without a coordinate system is loaded into QGIS, an external coordinate system
will be applied based on your QGIS settings. These files cannot be used by this tool. The user will be
notified of this when launching the tool as follows.

Clicking on view will open the PAT Log Messages Panel and provide a list of those images. Users can
then use the Assign Projection Tool from the Raster -> Projection menu to assign an internal
coordinate system to the files. If the Assign Projection tool is unavailaalbe activate the GDALTools
plugin .

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 41

2.12 Create Strip Trial Points
Summary
This tool is used to generate the data needed to implement the moving window t-test method of Lawes
and Bramley (2012) for analysis of simple strip trials. It may be useful to users who, for example, have
implemented an N-rich strip in their cereal paddock, or who want to compare a row of vines that have been
pruned differently to the rest of a vineyard. The tool uses a line representing the centre of a strip trial and
creates points along and at an offset to the line; the offset points are those for comparison with the strip
points. In this current version of PAT, use of this tool needs to be followed by using the strip and offset
points generated as input to the Extract Pixel Statistics for Points tool to extract values from map raster(s)
relevant to the strip experiment (e.g. a yield map) which can then be analysed outside of PAT. In a future
version, the entire analysis will be provided in PAT but in the meantime follow the instructions in
Analysing strip trial data using the moving window t-test on page 54.
Points are placed along the line using the nominated distance between points. In addition, two sets of
points are placed at the offset distance either side of the line. This allows the strip data, to be compared to
data from the neighbouring (control) area.
Each point is assigned a Side, PointID and line_dist values which are saved in the shapefile. The side
attribute represents one of the following:
C – centre line;
R – Right offset to centre line
L – Left offset to centre Line.
Left and right values are assigned based on the original drawing direction of the line not how they appear
on screen. The same PointID assigned to the centre line is also applied to the relevant L/R point.
The line_dist represents the distance in metres of the point from the start of respective line. The distances
for the L/R sides are calculated from the start of the offset line, not the centre line.

42 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Dialog

Create strip trial points
Strip trial lines:
Distance between
points (m):
Offset distance (m)

The layer containing the strip trial lines.
1 – 500.00
Default is 20.0
1 – 500.00
Default is 30.0

The distance used to space points along the line. In this instance, users are advised
to select a value appropriate to their trial rather than accepting the default.
The distance used to offset the points from the line.

The projected coordinate system to apply to the output files.
Projected
coordinate system:

By default it will calculate the relevant coordinate system from input layer’s coordinate system.
Note: If in Australia then MGA GDA 1994 zones, will be used – see Technical Notes on page 49.

Points shapefile:

Save line shapefile:

Derived from
layer name
Default is
unchecked.
Derived from
layer name.

The name and path of the output points shapefile.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 43

2.13 Whole-of-block Analysis
Summary
Whole-of-block experimentation, also known as spatially distributed experimentation, involves on-farm
experiments where treatments are applied in a highly replicated design over an entire block or land
management unit, or a large section of it. Given their scale, they are typically laid down using the farmer’s
normal equipment. These experiments can be thought of as a three-dimensional version of the strip trial,
discussed in the previous section Create Strip Trial Points. Users interested in this experimental approach
may wish to read the book chapter by Bramley et al. (2013) and perhaps the references listed in that
chapter. In brief, the objective of whole-of-block experimentation is to recognise the possible effect of
underlying spatial variability in the field in which the experiment is located, on the crop response to
experimental treatments, and so use this variability as an experimental tool to guide decisions about
variable rate or targeted management. Whole-of-block experimentation therefore moves away from the
classical approach to agronomic experimentation which seeks to identify whether treatment A is better
than treatment B and typically uses small plots. Instead, it is recognised that treatments A and B may both
deliver benefit, albeit in different parts of the block or field; the whole-of-block approach identifies these
different areas.
An example is given in Figure 4. Here, some different vineyard floor management treatments have been
evaluated in an experiment aimed at improving the availability of water to the vines. The cereal/legume
treatment delivers a significant benefit over the other treatments, but this is expensive and so the vineyard
manager would only want to use this in those areas where it is beneficial. The whole-of-block analysis tool
enables users to generate maps such as those shown in Figure 4 – maps showing the response to the
different treatments over the entire block, and maps indicating the significance of differences between
these treatments.

Figure 4 An example of a whole-of-block experiment conducted in a 4.8 ha Clare Valley vineyard. Panten and
Bramley (2011) provide further information

44 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

The purpose of the Whole-of-Block analysis tool is to predict treatment responses and their differences
over the entire experimentation area as illustrated by Figure 4. Similar to the use of VESPER for kriging, this
tool interpolates point data (low or high density) to the area of the entire block. Low density data would
typically include up to a few hundred points, perhaps collected through hand sampling, dispersed across a
block, whereas high density data includes a few thousand or more points, typically collected using a sensor
such as a yield monitor. The tool will handle either two or three treatments, and will identify areas of the
block where the treatments are significantly different from each other. To address the technical and
computational challenges in this analysis, the tool uses fast and efficient global and local cokriging
techniques.

Use of R
This tool is somewhat different from the other PAT tools in that it uses the R statistical language
(http://r-project.org/) to carry out the analytical processing. This means that R must be installed on
your PC for this to work – see Configuring QGIS to use R on page a11. The minimum R version suitable
for this is v3.5.1.

Algorithm for the Local Cokriging System – a brief commentary on the data radius used
A spatially-varying local co-kriging method is used to balance the trade-off between the computation
efficiency and prediction accuracy. We use a neighbourhood radius r(s) to identify neighbours for location
s.
For subregions with lower density observations, such as at the corners, or edges of a farm field, the
neighbourhood radius required by local cokriging will be relatively bigger to ensure the stability of the
estimated cross-variograms and balance the number of observations from different treatments within the
neighbourhood.
For high density datasets we will use a relatively small neighbourhood radius, and ensure it will change
relatively smoothly across the field. This adaption is achieved by two specific algorithm choices. Firstly, an
initial neighbourhood radius is selected automatically based on the observation density and achieving a
reasonable balance in the number of observations from different treatments. This neighbourhood radius
increases iteratively to include more observations if the current radius is not large enough to meet
prediction quality criteria. Secondly, a spatial-varying neighbourhood radius surface is estimated based on
neighbourhood radius values from a subset of locations. This exploits the spatial-smoothness of the
neighbourhood radius and provides a better default neighbourhood radius from which to optimise .

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 45

Dialog

Input points
layer

Easting and
Northing

Treatment
column

Data column
Input Block
Grid or
Prediction
Grid

A text format data file (CSV format) containing the experimental data that has been loaded into QGIS. The file
should be a minimum of four columns containing, the following:

The names of columns in the CSV data file containing the projected Easting and Northing point coordinates

The name of column in the CSV data file containing the treatment applied at each point.
The treatments can be represented by numbers (1,2,3), short characters (“AM”,”BL”,”CS”) or text 10
characters or less without spaces like (“Control“,“Mulch”,”Cover_crop”).
The name of column in the CSV data file containing the measured treatment response (e.g. Yield) at each
point.
The grid onto which treatment predictions, differences and standard errors are to be interpolated by the
tool.
The block grid created by PAT Create Block Grid tool is ideal for this, or it can be a raster (TIF) file with the
same coordinate system as the Input Points Layer.
There are two model options.

Model

Default is
Global



Global cokriging (default) is useful for small datasets (a few hundred points)



Local cokriging is useful for moderate or larger datasets (thousands of points),
particularly with local heterogeneity. This option initiates a starting radius for localised
cokriging and uses an iterative algorithm to optimise the local cross-covariance structure.

The cross-variogram is fitted using a Linear Model of Coregionalisation (LMC). The current
version of the software defines 20 lag classes, giving 20 points to the cross-variogram. The
maximum distance used in this process (i.e. largest lag class) is set as 1/3 of the maximum
distance between points in the input dataset.
Covariance
Model

46 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

Default is
Exponential

Exponential (default); users may also select Spherical and Gaussian models

User Defined
Neighbourhoo
d radius for
Local
Cokriging

Save output

Default is
unchecked
Default is
30m or 15
times the
pixel size

Only applicable to the Local Cokriging method, and allows a user to define an initial
neighbourhood radius. If this option is ticked then user should define the "Input
Neighbourhood Size in Metres". The default is 30 m. A suggested starting value can be
calculated as 15 times the pixel size of the block grid. However, if "User Defined
Neighbourhood for Local Cokriging" is not ticked then the initial neighbourhood radius will be
chosen as a function of total number of data points and corresponding number of treatments.
This is the recommended starting point for using this tool.

Folder in which to save the output files.
See File Naming Conventions (below) for an explanation of the different output files that will be created in
this folder.

File Naming Conventions



<> denotes an existing element or input. For example refers to the name of the Data Column selected in the input parameters (above).
non-alphanumeric characters are removed from strings with the exception of hyphens (-) and underscores ( _ ).

Filenames:
NAMING RULE

EXAMPLE

EXPLANATION

_dump_file_.tif

Bunch_wt_dump_file_GlobalExp_.log

Logged information mainly useful for debugging purposes

_model_parameters_.txt

Bunch_wt_model_parameters_GlobalExp_.txt

Summary of parameters used during processing

_list_of_tif_files_.txt

Bunch_wt_list_of_tif_files_GlobalExp_.txt

List of TIF files generated as output

_tr___.tif

Bunch_wt_tr_KC_GlobalExp_.tif

Treatment inference in "Input Block Grid or Prediction Grid".

_tr__var__.tif

Bunch_wt_tr_KC_GlobalExp_.tif

Corresponding variances of the treatments.

_ tr_diff____.tif

Bunch_wt_p_val_KC_SP_GlobalExp_.tif

Predictions of treatment response differences between
treatments

_tr__var__.tif

Bunch_wt_tr_KC_var_GlobalExp_.tif

Corresponding covariances of the treatment differences.

_p_val____.tif

Bunch_wt_p_val_KC_SP_GlobalExp_.tif

p-values of the treatment differences between pairs of
treatments.

_z____.tif

Bunch_wt_z_KC_SP_GlobalExp_.tif

Z-statistics of the treatment differences.

Output file names:

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 47

2.14 Settings
Summary
This tool is used to display and edit PAT settings.
The input and output data directories set here will be used to set the default paths by the browse for
file/folder functionality for all tools. Each tool will store and access its own values after first time use.
Checking the Debug (keep outputs) box will save intermediate files created while processing data to file. It
should be noted that this will slow down the time taken to run tools, but can be a useful diagnostic tool.
The Display Memory/Temporary Layers checkbox can be used to add the intermediate files to QGIS along
with any in-memory or virtual layers which are used but not saved to disk.

Dialog

Input Data Directory

A folder containing input data.*

Output Data Directory

This is the location of the output file.

Location of VESPER Exe

Set the location of the VESPER executable. If this is not found or specified, VESPER
cannot be run, but relevant VESPER input files can still be created.

Debug (Keep Outputs)

When checked, various intermediate files will be written to disk to assist with
error/debugging analysis. However, this will slow down processing.

Display Memory/Temporary Layers

If checked, any files written to disk, or created in memory will be loaded into QGIS
into a grouped layer labelled DEBUG and can be used for error/debugging analysis.

* By default this will be the PAT sub-folder in the user’s home directory. To quickly navigate here type %homepath%/PAT in the
address bar of Windows Explorer.

48 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

3 Technical Notes


PAT makes use of the CSIRO-developed pyPrecAg Python module which is an open source Python
package containing a range of specialised analysis functions.



All intermediate files created while processing are located in the PrecisionAg folder of the user’s
temporary folder. To quickly navigate to the temporary folder, type %temp%/PrecisionAg in the
address bar of windows explorer. This folder is deleted when QGIS exits.



All progress, messages and errors are displayed in the PAT tab of the Log Panel as shown in Figure 2
and are saved to a log file located in the PrecisionAg folder of the user’s temporary folder. A list of
important paths including the location of temp and the user’s plugin folder.



A Users QGIS Plugin folder can be found by typing %homepath%/.qgis2/python/plugins into the
address bar of Windows Explorer.



When a projected coordinate system is predicted from the source data, and the data is identified as
being in Australia, the Map Grid of Australia (MGA) reference system is used.
The MGA zones align closely with the SUTM zones, but use the 1994 Geocentric Datum of Australia.
Figure 5 shows the position of these the MGA zones.

Figure 5 The Map Grid of Australia. (www.environment.gov.au/erin/tools/mga2geo-gda.html).

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 49

4 How-To’s
4.1 Create a block boundary polygon from a CSV of GPS collected points
1. Using the New Shapefile Layer tool from the
manage layers toolbar (or Layer menu -> Create
Layer -> New Shapefile Layer) create a new
polygon shapefile adding the relevant
coordinate system* and attribute fields you
require. Clicking OK will prompt you for the
location to save the shapefile.
More information on coordinate systems can
be found at
2. Set a style and labelling to the polygon
layer. A hatching polygon fill works well for
editing.
3. Launch the Add Delimited Text
Layer tool from the manage layers
toolbar (or Layer menu-> Add Layer -> Add
Delimited Text Layer) and load your GPS CSV
file as a layer into QGIS.
Hint: Your coordinate system is probably
WGS 84.
4. If required, load other vector or raster data,
like imagery, which can be used as
reference.

5. Setup your snapping environment.
a. Open snapping options (Settings menu -> Snapping Options)
b. Change layer selection to advanced.
c. Tick the layer containing the point layer loaded in step 3.
d. Change the tolerance to 20 and set units to pixels

*More information on Map Grid of Australia can be found in Figure 5. For further information on coordinate systems:
https://docs.qgis.org/2.18/en/docs/gentle_gis_introduction/coordinate_reference_systems.html

50 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

6. Select/activate the polygon layer in the layers panel and click the toggle editing icon
digitizing toolbar.
7. Add new features by using the add features tool

from the

from the digitizing toolbar.

8. As you move the mouse close to a point the point will change to show a magenta cross hairs ( ), this
means the mouse has snapped to this point. Clicking the mouse will add this point as a vertex in the
polygon. Continue following around the points to form a polygon. Right-mouse-click to finish a polygon.
9. When you finish a polygon a dialog will open to allow you to enter attributes. Click OK to add attributes
and finalise polygon.
Save your edits using the save layer edits icon
when complete.

on digitizing toolbar and toggle editing off

To add, move or delete a vertex, toggle to node mode using the node tool
Nodes/Vertex will appear as red squares.

. Click the polygon to edit.



Double click to add new vertex.



Single click to select existing vertex. The square will turn blue. Use the DEL key to delete



Click and drag a vertex to move.

To add a hole (donut) to a polygon use the add ring tool
sketch your polygon as described in step 8.
To delete a hole (donut) in a polygon use the delete ring tool
and click in the hole.

from the advanced digitizing toolbar and

from the advanced digitizing toolbar

To split a polygon use the split features tool
from the advanced digitizing toolbar and sketch the
path to split. Multiple polygons will be created having the same attribution.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 51

Useful editing shortcut keys.
Add new feature

Ctrl+.

Zoom in

Scroll wheel or

Ctrl ++

Delete last vertex

Del

Zoom out

Scroll wheel or

Ctrl +-

Undo

Ctrl+Z

Zoom full

Ctrl+Shift+F

Cancel edit

Escape

Pan

Middle mouse or Spacebar (while adding
a feature only)
Note: spacebar also turns active layer
visibility on/off

4.2 Loading PAT Symbols into QGIS
The PAT plugin includes a pre-defined set of symbols and colour ramps for use with datasets derived while
using the plugin.

1. In QGIS, launch the Style Manager
Settings menu -> Style Manager
2. From the lower right corner of the dialog,
select Import dialog
3. Set Import from to file specified below.
Browse to the users QGIS plugin folder and
find the PAT_symbols.xml file in the pat
folder (see 1.5 Uninstall PAT for help
finding this folder).
4. Enter PAT as the Save to group.
5. Select symbols to import or click Select all.
6. Click Import. If symbols with the same name are already loaded, will be notified and given the
option to overwrite.

52 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 53

4.3 Analysing strip trial data using the moving window t-test
Following use of the Create Strip Trial Points and Extract pixel statistics for points tools, the user should
have an output dataset which contains a minimum of five columns: Columns of x and y coordinates
corresponding to locations along the trial strip and three columns of data corresponding to the extracted
pixel values from the strip ‘centre line’ and from right and left offsets to that centre line (see page 40). The
data are the input to the moving window t-test of Lawes and Bramley (2012). These data can then be analysed
in a spreadsheet or statistics package. For users of Excel, this may be done as described below. Note that in
this example, we demonstrate testing of the difference between the strip and one offset line only and use a
simple case in which no prior information (e.g. location of different management zones) is available. In
practice, users may which to compare the strip with both of the offset lines or alternative use the mean of
the two offset lines for comparison with the strip.
1. Data setup:
Column A
Record number
Column B
x coordinate or Easting
Column C
y coordinate or Northing
Column D
Data from the trial strip
Column E
Data from the offset comparison line
It is assumed here that the column headings are in row 1 with the data starting in row 2.
2. Calculate a treatment difference
In Column F, insert a formula to calculate a treatment difference, e.g.:
= D2 – E2
Copy this formula down to the last row the dataset.
3. Select the size of your moving window.
The choice of this will need to be considered in relation to the grid pixel size, the length of the trial strip,
and the distance setting used in the Create Strip Trial Points tool. In the example given in Lawes and
Bramley (2012), they extracted values from a yield map at approximately 5 m intervals along their strip,
which was approximately 700 m in length, and then used a window of 5 data values (i.e. approximately
25 m) for the analysis.
4. Calculate the treatment difference over the moving window
This will be calculated in Column G. Assuming that the size of the window is 5 data points, enter values of
0 in the first 4 rows of the column. In cell G6, calculate the average treatment difference from the
difference data in Column F (step 2):
= Average(F2:F6)
Copy this formula down to the last row the dataset.
5. Calculate the significance (P value) of the difference calculated at step 4 using the two-tail paired student
t-Test.
This will be calculated in Column H. In the cell of H6, enter the following formula:
=TTEST(D2:D6,E2:E6,2,1)
Copy this formula down to the last row the dataset.
The data generated by steps 4 and 5 enable the kinds of graphs displayed in Lawes and Bramley (2012) to
be produced showing how the response to the treatment in the strip differs from the areas outside the
strip, and the statistical significance of that difference, along the strip length.

54 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

5 Contributors
The following individuals have contributed the production of PAT and the underpinning pyprecag Python
package, through coding, configuration and expertise in PA, and in the case of the Whole-of-block analysis
tool, the development of statistical methodology.
Core Project Team: Christina Ratcliff (lead developer), Rob Bramley (project leader) and David Gobbett
(technical lead)
Whole-of-block analysis tool: Shuvo Bakar, Warren Jin and Brent Henderson
pyprecag packaging and publishing: Andrew Spiers, Adrian D’Alessandro, David Benn and Daniel Collins

6 Acknowledgments
CSIRO’s development of PAT draws on many years of Precision Agriculture RDE across a range of cropping
sectors and variously supported by CSIRO, Wine Australia, the former Cooperative Research Centre for
Viticulture, Sugar Research Australia and the Grains Research and Development Corporation. However, the
production of the PAT toolset has been sponsored and supported by Wine Australia (Project No. CSA1603)
through funding from the Australian Federal Department of Agriculture and Water Resources as part of its
Rural R&D for Profit program (Project No. 15-02-018 - Digital Technologies for dynamic management of
disease, stress and yield). The input of Andrew Spiers, Adrian D’Alessandro and Daniel Collins was funded
through a CSIRO IMT eResearch Collaboration Project. The support of these funders is gratefully
acknowledged, as is the assistance of the project advisory panel [Dr Kathy Evans (TIA/University of
Tasmania), Colin Hinze (Bird in Hand Winery) and Hans Loder (Penley Estate)].

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 55

7 References
Bramley RGV, Jensen TA. 2014. Sugarcane yield monitoring: A protocol for yield map interpolation and key
considerations in the collection of yield data. International Sugar Journal 116, 1–12.
doi:http://www.scopus.com/inward/record.url?eid=2-s2.084916603197&partnerID=40&md5=f5f44e347b0ac4a1e0d35d95e64ddb27.
Bramley RGV, Kleinlagel B, Ouzman J. 2008. A Protocol for the Construction of Yield Maps From Data
Collected Using Commercially Available Grape Yield Monitors - Supplement No. 2. Precision
viticulture Cooperative Research Centre for Viticulture, Adelaide 1–4.
Bramley RGV, Lawes RA, Cook SE. 2013. Spatially distributed experimentation: tools for the optimization of
targeted management. Chapter 12 in: Oliver MA, Bishop TFA, Marchant BM. (Eds). Precision
Agriculture for Sustainability and Environmental Protection. Earthscan, Food and Agriculture Series.
Routledge, Abingdon, UK. pp. 205-218.
Bramley RGV, Williams S. 2001. A Protocol for the Construction of Yield Maps From Data Collected Using
Commercially Available Grape Yield Monitors. Precision viticulture Cooperative Research Centre for
Viticulture, Adelaide 1–4.
Gitelson AA. 2004. Wide Dynamic Range Vegetation Index for Remote Quantification of Biophysical
Characteristics of Vegetation. Journal of Plant Physiology 161, 165–173. doi:10.1078/0176-161701176.
Gitelson AA, Viña A, Ciganda V, Rundquist DC, Arkebauer TJ. 2005. Remote estimation of canopy
chlorophyll content in crops. Geophysical Research Letters 32, L08403. doi:10.1029/2005GL022688.
Lawes RA, Bramley RGV. 2012. A Simple Method for the Analysis of On-Farm Strip Trials. Agronomy Journal
104, 371-377.
Minasny B, McBratney AB, Whelan BM. 2005. VESPER version 1.62. Aust. Cent. Precis. Agric. McMillan
Build. A 5. https://sydney.edu.au/agriculture/pal/software/vesper.shtml.
Panten K, Bramley RGV. 2011. Viticultural experimentation using whole blocks: Evaluation of three floor
management options. Australian Journal of Grape and Wine Research 17 136-146.
QGIS Development Team 2017. QGIS Geographic Information System. Open Source Geospatial Foundation
Project. https://qgis.org
R Core Team 2018. R: A language and environment for statistical computing. R Foundation for Statistical
Computing, Vienna, Austria. http://www.R-project.org/.
Gillies S and others. 2011. Fiona is OGR's neat, nimble, no-nonsense API. Toblerity.
https://github.com/Toblerity/Fiona
Gillies S and others. 2013. Rasterio: geospatial raster I/O for Python programmers. Mapbox.
https://github.com/mapbox/rasterio
Taylor JA, McBratney AB, Whelan BM. 2007. Establishing management classes for broadacre agricultural
production. Agronomy Journal 99, 1366–1376. doi:10.2134/agronj2007.0070.

56 | PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 )

FOR FURTHER INFORMATION

t 1300 363 400
+61 3 9545 2176
e csiroenquiries@csiro.au
w www.csiro.au
w https://www.csiro.au/en/Research/AF

CSIRO Agriculture and Food
Christina Ratcliff
t +61 8 8273 8157
e christina.ratcliff@csiro.au
w https://people-my.csiro.au/r/c/christina-ratcliff

AT CSIRO, WE DO THE
EXTRAORDINARY EVERY DAY
We innovate for tomorrow and help
improve today – for our customers, all
Australians and the world.
Our innovations contribute billions of
dollars to the Australian economy
every year. As the largest patent holder
in the nation, our vast wealth of
intellectual property has led to more
than 150 spin-off companies.

CSIRO Agriculture and Food
David Gobbett
t +61 8 8303 8741
e david.gobbett@csiro.au
w https://people.csiro.au/g/d/david-gobbett
CSIRO Agriculture and Food
Dr Rob Bramley
t +61 8 8303 8594
e rob.bramley@csiro.au
w https://people.csiro.au/B/R/Rob-Bramley

With more than 5,000 experts and a
burning desire to get things done, we are
Australia’s catalyst for innovation.
CSIRO. WE IMAGINE. WE COLLABORATE.
WE INNOVATE.

PAT - Precision Agriculture Tools Plugin for QGIS ( January 2019 PAT v0.1.0 ) | 57

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Title                           : PAT Plugin for QGIS User Manual
Author                          : Ratcliff, Christina (A&F, Waite Campus)
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