Fed Data Manual
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Package ‘FedData’
January 11, 2019
Type Package
Title Functions to Automate Downloading Geospatial Data Available from
Several Federated Data Sources
Description Functions to automate downloading geospatial data available from
several federated data sources (mainly sources maintained by the US Federal
government). Currently, the package enables extraction from seven datasets:
The National Elevation Dataset digital elevation models (1 and 1/3 arc-second;
USGS); The National Hydrography Dataset (USGS); The Soil Survey Geographic
(SSURGO) database from the National Cooperative Soil Survey (NCSS), which is
led by the Natural Resources Conservation Service (NRCS) under the USDA; the
Global Historical Climatology Network (GHCN), coordinated by National Climatic
Data Center at NOAA; the Daymet gridded estimates of daily weather parameters
for North America, version 3, available from the Oak Ridge National Laboratory's
Distributed Active Archive Center (DAAC); the International Tree Ring Data Bank;
and the National Land Cover Database (NLCD).
Version 2.5.6
Date 2019-01-11
Author R. Kyle Bocinsky [aut, cre], Dylan Beaudette [ctb], Scott Chamberlain [ctb]
Maintainer R. Kyle Bocinsky <bocinsky@gmail.com>
URL https://github.com/ropensci/FedData
BugReports https://github.com/ropensci/FedData/issues
License MIT + file LICENSE
Depends R (>= 3.2.0), sp
Imports data.table, devtools, igraph, curl, methods, rgdal, raster,
Hmisc, rgeos, readr, lubridate, tibble, dplyr, magrittr,
foreach, ncdf4, stringr, sf, httr, jsonlite, xml2
Repository CRAN
NeedsCompilation no
RoxygenNote 6.1.1
Suggests testthat, covr, roxygen2
LazyData true
Encoding UTF-8
1
2daymet_tiles
Rtopics documented:
daymet_tiles......................................... 2
get_daymet ......................................... 3
get_ghcn_daily ....................................... 4
get_itrdb........................................... 8
get_ned ........................................... 10
get_nhd ........................................... 11
get_nlcd........................................... 12
get_ssurgo.......................................... 13
nlcd_canopy_pam...................................... 14
nlcd_impervious_pam.................................... 14
nlcd_landcover_pam .................................... 15
nlcd_tiles .......................................... 15
pal_nlcd........................................... 15
Index 17
daymet_tiles The DAYMET tiles SpatialPolygonsDataFrame.
Description
A dataset containing the DAYMET tiles.
Usage
daymet_tiles
Format
A SpatialPolygonsDataFrame with 1060 features and 5 variables:
TileID the numeric identifier of the tile
XMin the minimum longitude of the tile
XMax the maximum longitude of the tile
YMin the minimum latitude of the tile
YMax the maximum latitude of the tile
Source
https://github.com/khufkens/daymetr/blob/master/data/tile_outlines.rda
get_daymet 3
get_daymet Download and crop the 1-km DAYMET daily weather dataset.
Description
get_daymet returns a RasterBrick of weather data cropped to a given template study area.
Usage
get_daymet(template, label, elements = NULL, years = NULL,
raw.dir = "./RAW/DAYMET", extraction.dir = paste0("./EXTRACTIONS/",
label, "/DAYMET"), force.redo = F)
Arguments
template A Raster* or Spatial* object to serve as a template for cropping.
label A character string naming the study area.
elements A character vector of elements to extract.
The available elements are:
dayl = Duration of the daylight period in seconds per day. This calculation is
based on the period of the day during which the sun is above a hypothetical flat
horizon.
prcp = Daily total precipitation in millimeters per day, sum of all forms con-
verted to water-equivalent. Precipitation occurrence on any given day may be
ascertained.
srad = Incident shortwave radiation flux density in watts per square meter, taken
as an average over the daylight period of the day. NOTE: Daily total radia-
tion (MJ/m2/day) can be calculated as follows: ((srad (W/m2) * dayl (s/day)) /
l,000,000)
swe = Snow water equivalent in kilograms per square meter. The amount of
water contained within the snowpack.
tmax = Daily maximum 2-meter air temperature in degrees Celsius.
tmin = Daily minimum 2-meter air temperature in degrees Celsius.
vp = Water vapor pressure in pascals. Daily average partial pressure of water
vapor.
years A numeric vector of years to extract.
raw.dir A character string indicating where raw downloaded files should be put. The
directory will be created if missing. Defaults to ’./RAW/DAYMET/’.
extraction.dir A character string indicating where the extracted and cropped DEM should
be put. The directory will be created if missing. Defaults to ’./EXTRAC-
TIONS/DAYMET/’.
force.redo If an extraction for this template and label already exists, should a new one be
created?
Value
A named list of RasterBricks of weather data cropped to the extent of the template.
4get_ghcn_daily
Examples
## Not run:
# Extract data for the Village Ecodynamics Project 'VEPIIN'study area:
# http://village.anth.wsu.edu
vepPolygon <- polygon_from_extent(raster::extent(672800,740000,4102000,4170000),
proj4string='+proj=utm +datum=NAD83 +zone=12')
# Get the DAYMET (North America only)
# Returns a list of raster bricks
DAYMET <- get_daymet(template=vepPolygon,
label='VEPIIN',
elements = c('prcp','tmin','tmax'),
years = 1980:1985)
# Plot with raster::plot
plot(DAYMET$tmin$X1985.10.23)
## End(Not run)
get_ghcn_daily Download and crop the Global Historical Climate Network-Daily
data.
Description
get_ghcn_daily returns a named list of length 2:
1. ’spatial’: A SpatialPointsDataFrame of the locations of GHCN weather stations in the
template, and
2. ’tabular’: A named list of data.frameswith the daily weather data for each station. The
name of each list item is the station ID.
Usage
get_ghcn_daily(template = NULL, label = NULL, elements = NULL,
years = NULL, raw.dir = "./RAW/GHCN",
extraction.dir = paste0("./EXTRACTIONS/", label, "/GHCN"),
standardize = F, force.redo = F)
Arguments
template A Raster* or Spatial* object to serve as a template for cropping. Alternatively,
a character vector providing GHCN station IDs. If missing, all stations will be
downloaded!
label A character string naming the study area.
elements A character vector of elements to extract.
The five core elements are:
PRCP = Precipitation (tenths of mm)
SNOW = Snowfall (mm)
SNWD = Snow depth (mm)
TMAX = Maximum temperature (tenths of degrees C)
TMIN = Minimum temperature (tenths of degrees C)
get_ghcn_daily 5
The other elements are:
ACMC = Average cloudiness midnight to midnight from 30-second ceilometer
data (percent)
ACMH = Average cloudiness midnight to midnight from manual observations
(percent)
ACSC = Average cloudiness sunrise to sunset from 30-second ceilometer data
(percent)
ACSH = Average cloudiness sunrise to sunset from manual observations (per-
cent)
AWDR = Average daily wind direction (degrees)
AWND = Average daily wind speed (tenths of meters per second)
DAEV = Number of days included in the multiday evaporation total (MDEV)
DAPR = Number of days included in the multiday precipitation total (MDPR)
DASF = Number of days included in the multiday snowfall total (MDSF)
DATN = Number of days included in the multiday minimum temperature (MDTN)
DATX = Number of days included in the multiday maximum temperature (MDTX)
DAWM = Number of days included in the multiday wind movement (MDWM)
DWPR = Number of days with non-zero precipitation included in multiday pre-
cipitation total (MDPR)
EVAP = Evaporation of water from evaporation pan (tenths of mm)
FMTM = Time of fastest mile or fastest 1-minute wind (hours and minutes, i.e.,
HHMM)
FRGB = Base of frozen ground layer (cm)
FRGT = Top of frozen ground layer (cm)
FRTH = Thickness of frozen ground layer (cm)
GAHT = Difference between river and gauge height (cm)
MDEV = Multiday evaporation total (tenths of mm; use with DAEV)
MDPR = Multiday precipitation total (tenths of mm; use with DAPR and DWPR,
if available)
MDSF = Multiday snowfall total
MDTN = Multiday minimum temperature (tenths of degrees C; use with DATN)
MDTX = Multiday maximum temperature (tenths of degrees C; use with DATX)
MDWM = Multiday wind movement (km)
MNPN = Daily minimum temperature of water in an evaporation pan (tenths of
degrees C)
MXPN = Daily maximum temperature of water in an evaporation pan (tenths of
degrees C)
PGTM = Peak gust time (hours and minutes, i.e., HHMM)
PSUN = Daily percent of possible sunshine (percent)
SN*# = Minimum soil temperature (tenths of degrees C) where * corresponds
to a code for ground cover and # corresponds to a code for soil depth.
Ground cover codes include the following:
0 = unknown
1 = grass
2 = fallow
3 = bare ground
4 = brome grass
5 = sod
6 = straw multch
6get_ghcn_daily
7 = grass muck
8 = bare muck
Depth codes include the following:
1=5cm
2 = 10 cm
3 = 20 cm
4 = 50 cm
5 = 100 cm
6 = 150 cm
7 = 180 cm
SX*# = Maximum soil temperature (tenths of degrees C) where * corresponds
to a code for ground cover and # corresponds to a code for soil depth.
See SN*# for ground cover and depth codes.
TAVG = Average temperature (tenths of degrees C) [Note that TAVG from
source ’S’ corresponds to an average for the period ending at 2400 UTC rather
than local midnight]
THIC = Thickness of ice on water (tenths of mm)
TOBS = Temperature at the time of observation (tenths of degrees C)
TSUN = Daily total sunshine (minutes)
WDF1 = Direction of fastest 1-minute wind (degrees)
WDF2 = Direction of fastest 2-minute wind (degrees)
WDF5 = Direction of fastest 5-second wind (degrees)
WDFG = Direction of peak wind gust (degrees)
WDFI = Direction of highest instantaneous wind (degrees)
WDFM = Fastest mile wind direction (degrees)
WDMV = 24-hour wind movement (km)
WESD = Water equivalent of snow on the ground (tenths of mm)
WESF = Water equivalent of snowfall (tenths of mm)
WSF1 = Fastest 1-minute wind speed (tenths of meters per second)
WSF2 = Fastest 2-minute wind speed (tenths of meters per second)
WSF5 = Fastest 5-second wind speed (tenths of meters per second)
WSFG = Peak gust wind speed (tenths of meters per second)
WSFI = Highest instantaneous wind speed (tenths of meters per second)
WSFM = Fastest mile wind speed (tenths of meters per second)
WT** = Weather Type where ** has one of the following values:
01 = Fog, ice fog, or freezing fog (may include heavy fog)
02 = Heavy fog or heaving freezing fog (not always distinguished from fog)
03 = Thunder
04 = Ice pellets, sleet, snow pellets, or small hail
05 = Hail (may include small hail)
06 = Glaze or rime
07 = Dust, volcanic ash, blowing dust, blowing sand, or blowing obstruction
08 = Smoke or haze
09 = Blowing or drifting snow
10 = Tornado, waterspout, or funnel cloud
11 = High or damaging winds
12 = Blowing spray
13 = Mist
14 = Drizzle
get_ghcn_daily 7
15 = Freezing drizzle
16 = Rain (may include freezing rain, drizzle, and freezing drizzle)
17 = Freezing rain
18 = Snow, snow pellets, snow grains, or ice crystals
19 = Unknown source of precipitation
21 = Ground fog
22 = Ice fog or freezing fog
WV** = Weather in the Vicinity where ** has one of the following values:
01 = Fog, ice fog, or freezing fog (may include heavy fog)
03 = Thunder
07 = Ash, dust, sand, or other blowing obstruction
18 = Snow or ice crystals
20 = Rain or snow shower
years A numeric vector indicating which years to get.
raw.dir A character string indicating where raw downloaded files should be put. The
directory will be created if missing. Defaults to ’./RAW/GHCN/’.
extraction.dir A character string indicating where the extracted and cropped GHCN shapefiles
should be put. The directory will be created if missing. Defaults to ’./EXTRAC-
TIONS/GHCN/’.
standardize Select only common year/month/day? Defaults to FALSE.
force.redo If an extraction for this template and label already exists, should a new one be
created? Defaults to FALSE.
Value
A named list containing the ’spatial’ and ’tabular’ data.
Examples
## Not run:
# Extract data for the Village Ecodynamics Project 'VEPIIN'study area:
# http://village.anth.wsu.edu
vepPolygon <- polygon_from_extent(raster::extent(672800,740000,4102000,4170000),
proj4string='+proj=utm +datum=NAD83 +zone=12')
# Get the daily GHCN data (GLOBAL)
# Returns a list: the first element is the spatial locations of stations,
# and the second is a list of the stations and their daily data
GHCN.prcp <- get_ghcn_daily(template=vepPolygon, label='VEPIIN', elements=c('prcp'))
# Plot the VEP polygon
plot(vepPolygon)
# Plot the spatial locations
plot(GHCN.prcp$spatial, pch=1, add=T)
legend('bottomleft', pch=1, legend='GHCN Precipitation Records')
# Elements for which you require the same data
# (i.e., minimum and maximum temperature for the same days)
# can be standardized using standardize==T
GHCN.temp <- get_ghcn_daily(template=vepPolygon,
label='VEPIIN',
8get_itrdb
elements=c('tmin','tmax'),
standardize=T)
# Plot the VEP polygon
plot(vepPolygon)
# Plot the spatial locations
plot(GHCN.temp$spatial, pch=1, add=T)
legend('bottomleft', pch=1, legend='GHCN Temperature Records')
## End(Not run)
get_itrdb Download the latest version of the ITRDB, and extract given parame-
ters.
Description
get_itrdb returns a named list of length 3:
1. ’metadata’: A data.table or SpatialPointsDataFrame (if makeSpatial==TRUE) of the loca-
tions and names of extracted ITRDB chronologies,
2. ’widths’: A matrix of tree-ring widths/densities given user selection, and
3. ’depths’: A matrix of tree-ring sample depths.
Usage
get_itrdb(template = NULL, label = NULL, recon.years = NULL,
calib.years = NULL, species = NULL, measurement.type = NULL,
chronology.type = NULL, makeSpatial = F, raw.dir = "./RAW/ITRDB",
extraction.dir = ifelse(!is.null(label), paste0("./EXTRACTIONS/",
label, "/ITRDB"), "./EXTRACTIONS/ITRDB"), force.redo = FALSE)
Arguments
template A Raster* or Spatial* object to serve as a template for selecting chronologies. If
missing, all available global chronologies are returned.
label A character string naming the study area.
recon.years A numeric vector of years over which reconstructions are needed; if missing,
the union of all years in the available chronologies are given.
calib.years A numeric vector of all required years—chronologies without these years will
be discarded; if missing, all available chronologies are given.
species A character vector of 4-letter tree species identifiers; if missing, all available
chronologies are given.
measurement.type
A character vector of measurement type identifiers. Options include:
• ’Total Ring Density’
• ’Earlywood Width’
• ’Earlywood Density’
• ’Latewood Width’
get_itrdb 9
• ’Minimum Density’
• ’Ring Width’
• ’Latewood Density’
• ’Maximum Density’
• ’Latewood Percent’
if missing, all available chronologies are given.
chronology.type
A character vector of chronology type identifiers. Options include:
• ’ARSTND’
• ’Low Pass Filter’
• ’Residual’
• ’Standard’
• ’Re-Whitened Residual’
• ’Measurements Only’
if missing, all available chronologies are given.
makeSpatial Should the metadata be presented as a SpatialPointsDataFrame? Defaults to
FALSE.
raw.dir A character string indicating where raw downloaded files should be put. The
directory will be created if missing. Defaults to ’./RAW/ITRDB/’.
extraction.dir A character string indicating where the extracted and cropped ITRDB dataset
should be put. The directory will be created if missing. Defaults to ’./EXTRAC-
TIONS/ITRDB/’.
force.redo If an extraction already exists, should a new one be created? Defaults to FALSE.
Value
A named list containing the ’metadata’, ’widths’, and ’depths’ data.
Examples
## Not run:
# Extract data for the Village Ecodynamics Project 'VEPIIN'study area:
# http://village.anth.wsu.edu
vepPolygon <- polygon_from_extent(raster::extent(672800,740000,4102000,4170000),
proj4string='+proj=utm +datum=NAD83 +zone=12')
# Get the ITRDB records
ITRDB <- get_itrdb(template=vepPolygon, label='VEPIIN', makeSpatial=T)
# Plot the VEP polygon
plot(vepPolygon)
# Map the locations of the tree ring chronologies
plot(ITRDB$metadata, pch=1, add=T)
legend('bottomleft', pch=1, legend='ITRDB chronologies')
## End(Not run)
10 get_ned
get_ned Download and crop the 1 (~30 meter) or 1/3 (~10 meter) arc-second
National Elevation Dataset.
Description
get_ned returns a RasterLayer of elevation data cropped to a given template study area.
Usage
get_ned(template, label, res = "1", raw.dir = "./RAW/NED",
extraction.dir = paste0("./EXTRACTIONS/", label, "/NED"),
raster.options = c("COMPRESS=DEFLATE", "ZLEVEL=9", "INTERLEAVE=BAND"),
force.redo = F)
Arguments
template A Raster* or Spatial* object to serve as a template for cropping.
label A character string naming the study area.
res A character string representing the desired resolution of the NED. ’1’ indicates
the 1 arc-second NED (the default), while ’13’ indicates the 1/3 arc-second
dataset.
raw.dir A character string indicating where raw downloaded files should be put. The
directory will be created if missing. Defaults to ’./RAW/NED/’.
extraction.dir A character string indicating where the extracted and cropped DEM should
be put. The directory will be created if missing. Defaults to ’./EXTRAC-
TIONS/NED/’.
raster.options a vector of options for raster::writeRaster.
force.redo If an extraction for this template and label already exists, should a new one be
created?
Value
ARasterLayer DEM cropped to the extent of the template.
Examples
## Not run:
# Extract data for the Village Ecodynamics Project 'VEPIIN'study area:
# http://village.anth.wsu.edu
vepPolygon <- polygon_from_extent(raster::extent(672800,740000,4102000,4170000),
proj4string='+proj=utm +datum=NAD83 +zone=12')
# Get the NED (USA ONLY)
# Returns a raster
NED <- get_ned(template=vepPolygon, label='VEPIIN')
# Plot with raster::plot
plot(NED)
## End(Not run)
get_nhd 11
get_nhd Download and crop the National Hydrography Dataset.
Description
get_nhd returns a list of Spatial* objects extracted from the National Hydrography Dataset.
Usage
get_nhd(template, label, raw.dir = "./RAW/NHD",
extraction.dir = paste0("./EXTRACTIONS/", label, "/NHD"),
force.redo = FALSE)
Arguments
template A Raster* or Spatial* object to serve as a template for cropping.
label A character string naming the study area.
raw.dir A character string indicating where raw downloaded files should be put. The
directory will be created if missing. Defaults to ’./RAW/NHD/’.
extraction.dir A character string indicating where the extracted and cropped NHD shapefiles
should be put. The directory will be created if missing. Defaults to ’./EXTRAC-
TIONS/NHD/’.
force.redo If an extraction for this template and label already exists, should a new one be
created?
Value
A list of Spatial* objects extracted from the National Hydrography Dataset.
Examples
## Not run:
# Extract data for the Village Ecodynamics Project 'VEPIIN'study area:
# http://village.anth.wsu.edu
vepPolygon <- polygon_from_extent(raster::extent(672800,740000,4102000,4170000),
proj4string='+proj=utm +datum=NAD83 +zone=12')
# Get the NHD (USA ONLY)
NHD <- get_nhd(template=vepPolygon, label='VEPIIN')
# Plot the VEP polygon
plot(vepPolygon)
# Plot the NHD data
plot(NHD$NHDFlowline, add=T)
plot(NHD$NHDLine, add=T)
plot(NHD$NHDArea, col='black', add=T)
plot(NHD$NHDWaterbody, col='black', add=T)
## End(Not run)
12 get_nlcd
get_nlcd Download and crop the National Land Cover Database.
Description
get_nlcd returns a RasterLayer of NLCD data cropped to a given template study area.
Usage
get_nlcd(template, label, year = 2011, dataset = "landcover",
raw.dir = "./RAW/NLCD", extraction.dir = paste0("./EXTRACTIONS/",
label, "/NLCD"), raster.options = c("COMPRESS=DEFLATE", "ZLEVEL=9",
"INTERLEAVE=BAND"), force.redo = F)
Arguments
template A Raster* or Spatial* object to serve as a template for cropping.
label A character string naming the study area.
year An integer representing the year of desired NLCD product. Acceptable values
are 2011 (default), 2006, and 2001.
dataset A character string representing type of the NLCD product. Acceptable values
are ’landcover’ (default), ’impervious’, and ’canopy’. As of February 7, 2018,
the canopy data for 2006 are not available through the National Map Staged
datasets, and so aren’t available in FedData.
raw.dir A character string indicating where raw downloaded files should be put. The
directory will be created if missing. Defaults to ’./RAW/NLCD/’.
extraction.dir A character string indicating where the extracted and cropped DEM should
be put. The directory will be created if missing. Defaults to ’./EXTRAC-
TIONS/NLCD/’.
raster.options a vector of options for raster::writeRaster.
force.redo If an extraction for this template and label already exists, should a new one be
created?
Value
ARasterLayer DEM cropped to the extent of the template.
Examples
## Not run:
# Extract data for the Village Ecodynamics Project 'VEPIIN'study area:
# http://village.anth.wsu.edu
vepPolygon <- polygon_from_extent(raster::extent(672800,740000,4102000,4170000),
proj4string='+proj=utm +datum=NAD83 +zone=12')
# Get the NLCD (USA ONLY)
# Returns a raster
NLCD <- get_nlcd(template=vepPolygon, label='VEPIIN')
# Plot with raster::plot
get_ssurgo 13
plot(NLCD)
## End(Not run)
get_ssurgo Download and crop data from the NRCS SSURGO soils database.
Description
This is an efficient method for spatially merging several different soil survey areas as well as merg-
ing their tabular data.
Usage
get_ssurgo(template, label, raw.dir = "./RAW/SSURGO",
extraction.dir = paste0("./EXTRACTIONS/", label, "/SSURGO"),
force.redo = FALSE)
Arguments
template A Raster* or Spatial* object to serve as a template for cropping; optionally, a
vector of area names [e.g., c(’IN087’,’IN088’)] may be provided.
label A character string naming the study area.
raw.dir A character string indicating where raw downloaded files should be put. The
directory will be created if missing. Defaults to ’./RAW/SSURGO/’.
extraction.dir A character string indicating where the extracted and cropped SSURGO shape-
files should be put. The directory will be created if missing. Defaults to ’./EX-
TRACTIONS/SSURGO/’.
force.redo If an extraction for this template and label already exists, should a new one be
created? Defaults to FALSE.
Details
get_ssurgo returns a named list of length 2:
1. ’spatial’: A SpatialPolygonsDataFrame of soil mapunits in the template, and
2. ’tabular’: A named list of data.frameswith the SSURGO tabular data.
Value
A named list containing the ’spatial’ and ’tabular’ data.
Examples
## Not run:
# Extract data for the Village Ecodynamics Project 'VEPIIN'study area:
# http://village.anth.wsu.edu
vepPolygon <- polygon_from_extent(raster::extent(672800,740000,4102000,4170000),
proj4string='+proj=utm +datum=NAD83 +zone=12')
# Get the NRCS SSURGO data (USA ONLY)
14 nlcd_impervious_pam
SSURGO.VEPIIN <- get_ssurgo(template=vepPolygon, label='VEPIIN')
# Plot the VEP polygon
plot(vepPolygon)
# Plot the SSURGO mapunit polygons
plot(SSURGO.VEPIIN$spatial, lwd=0.1, add=T)
# Or, download by Soil Survey Area names
SSURGO.areas <- get_ssurgo(template=c('CO670','CO075'), label='CO_TEST')
# Let's just look at spatial data for CO675
SSURGO.areas.CO675 <- SSURGO.areas$spatial[SSURGO.areas$spatial$AREASYMBOL=='CO075',]
# And get the NED data under them for pretty plotting
NED.CO675 <- get_ned(template=SSURGO.areas.CO675, label='SSURGO_CO675')
# Plot the SSURGO mapunit polygons, but only for CO675
plot(NED.CO675)
plot(SSURGO.areas.CO675, lwd=0.1, add=T)
## End(Not run)
nlcd_canopy_pam The NLCD canopy PAM attributes.
Description
A dataset containing the PAM attributes.
Usage
nlcd_canopy_pam
Format
An object of class character of length 2345.
nlcd_impervious_pam The NLCD impervious PAM attributes.
Description
A dataset containing the PAM attributes.
Usage
nlcd_impervious_pam
Format
An object of class character of length 2345.
nlcd_landcover_pam 15
nlcd_landcover_pam The NLCD landcover PAM attributes.
Description
A dataset containing the PAM attributes.
Usage
nlcd_landcover_pam
Format
An object of class character of length 2606.
nlcd_tiles The NLCD tiles SpatialPolygonsDataFrame.
Description
A dataset containing the NLCD tiles.
Usage
nlcd_tiles
Format
A SpatialPolygonsDataFrame with 203 features and 1 variable:
Name the name of the tile
pal_nlcd NLCD colour map palettes
Description
NLCD colour map palettes
Usage
pal_nlcd()
Value
A data frame with official class descriptions and hexencoded rgb(a) colour values
16 pal_nlcd
References
https://www.mrlc.gov/data/legends/national-land-cover-database-2011-nlcd2011-legend
Examples
## Not run:
# Extract data for the Village Ecodynamics Project 'VEPIIN'study area:
# http://village.anth.wsu.edu
vepPolygon <- polygon_from_extent(raster::extent(672800,740000,4102000,4170000),
proj4string='+proj=utm +datum=NAD83 +zone=12')
NLCD <- get_nlcd(template=vepPolygon, label='VEPIIN')
NLCD <- as.matrix(table(raster::values(NLCD)))
cols <- dplyr::filter(pal_nlcd(), code %in% row.names(NLCD))
par(xpd = TRUE, mar = c(10, 3, 2, 1))
barplot(NLCD, beside = FALSE, col = cols$color)
legend("bottom", legend = cols$description, fill = cols$color,
ncol = 2, inset = c(0, -0.6))
## End(Not run)
Index
∗Topic datasets
daymet_tiles,2
nlcd_canopy_pam,14
nlcd_impervious_pam,14
nlcd_landcover_pam,15
nlcd_tiles,15
data.frame,4,13
daymet_tiles,2
get_daymet,3
get_ghcn_daily,4
get_itrdb,8
get_ned,10
get_nhd,11
get_nlcd,12
get_ssurgo,13
nlcd_canopy_pam,14
nlcd_impervious_pam,14
nlcd_landcover_pam,15
nlcd_tiles,15
pal_nlcd,15
17
