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FedData is an R package implementing functions to automate downloading geospatial data available from several federated data sources (mainly sources maintained by the US Federal government).

FedData version 2.5 will be the final minor CRAN release of FedData 2. FedData 3 will be released in the coming months, but some code built on FedData 2 will not be compatible with FedData 3.

Currently, the package enables extraction from seven datasets:

This package is designed with the large-scale geographic information system (GIS) use-case in mind: cases where the use of dynamic web-services is impractical due to the scale (spatial and/or temporal) of analysis. It functions primarily as a means of downloading tiled or otherwise spatially-defined datasets; additionally, it can preprocess those datasets by extracting data within an area of interest (AoI), defined spatially. It relies heavily on the sp, raster, and rgdal packages.

This package has been built and tested on a source (Homebrew) install of R on macOS 10.13 (High Sierra), and has been successfully run on Ubuntu 14.04.5 LTS (Trusty), Ubuntu 16.04.1 LTS (Xenial) and binary installs of R on Mac OS 10.13 and Windows 10.

Development

Contributors

Install FedData

Demonstration

This demonstration script is available as an R Markdown document in the GitHub repository: https://github.com/ropensci/FedData.

Load FedData and define a study area

# FedData Tester
library(FedData)
library(magrittr)

# Extract data for the Village Ecodynamics Project "VEPIIN" study area:
# http://veparchaeology.org
vepPolygon <- polygon_from_extent(raster::extent(672800, 740000, 4102000, 4170000),
                                  proj4string = "+proj=utm +datum=NAD83 +zone=12")

Get and plot the National Elevation Dataset for the study area

# Get the NED (USA ONLY)
# Returns a raster
NED <- get_ned(template = vepPolygon,
               label = "VEPIIN")
# Plot with raster::plot
raster::plot(NED)

Get and plot the Daymet dataset for the study area

# Get the DAYMET (North America only)
# Returns a raster
DAYMET <- get_daymet(template = vepPolygon,
               label = "VEPIIN",
               elements = c("prcp","tmax"),
               years = 1980:1985)
# Plot with raster::plot
raster::plot(DAYMET$tmax$X1985.10.23)

Get and plot the daily GHCN precipitation data for the study area

# 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 NED again
raster::plot(NED)
# Plot the spatial locations
sp::plot(GHCN.prcp$spatial,
         pch = 1,
         add = TRUE)
legend('bottomleft',
       pch = 1,
       legend="GHCN Precipitation Records")

Get and plot the daily GHCN temperature data for the study area

# 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", 
                            elements = c('tmin','tmax'), 
                            years = 1980:1985,
                            standardize = TRUE)
#> Warning: Unknown or uninitialised column: 'ELEMENT'.
#> Warning in get_ghcn_daily_station(ID = station, elements = elements, years
#> = years, : Elements not available: TMAX, TMIN
#> Warning: Unknown or uninitialised column: 'ELEMENT'.
#> Warning in get_ghcn_daily_station(ID = station, elements = elements, years
#> = years, : Elements not available: TMAX, TMIN
#> Warning: Unknown or uninitialised column: 'ELEMENT'.
#> Warning in get_ghcn_daily_station(ID = station, elements = elements, years
#> = years, : Elements not available: TMAX, TMIN
# Plot the NED again
raster::plot(NED)
# Plot the spatial locations
sp::plot(GHCN.temp$spatial,
         add = TRUE,
         pch = 1)
legend('bottomleft',
       pch = 1,
       legend = "GHCN Temperature Records")

Get and plot the National Hydrography Dataset for the study area

# Get the NHD (USA ONLY)
NHD <- get_nhd(template = vepPolygon, 
               label = "VEPIIN")
# Plot the NED again
raster::plot(NED)
# Plot the NHD data
NHD %>%
  lapply(sp::plot,
         col = 'black',
         add = TRUE)