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Experimental data retrieval package for developing SELECT

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TxWRI/SELECTRdata

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SELECTRdata

Project Status: WIP - Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.

SELECTRdata provides convenience functions for downloading raster and tabular data used in the Spatially Explicit Load Enrichment Calculation Tool (SELECT). By providing a SpatRaster object of the target watershed, functions are available to download cropped: - National Land Cover Dataset - FEMA USA Structures - Census Blocks - TIGER County Boundaries - USDA Agricultural Census

Sources to add: - Point sources (via ECHO or echor) - MS4 urbanized areas (via US Census)

Installation

You can install the development version of SELECTRdata like so:

# FILL THIS IN! HOW CAN PEOPLE INSTALL YOUR DEV PACKAGE?

Example

MRLC National Land Cover Dataset

library(SELECTRdata)
library(terra)
#> Warning: package 'terra' was built under R version 4.3.3
#> terra 1.7.78

## we need a template file, this is the thomsoncreek watershed in Texas
dem <- system.file("extdata", "thompsoncreek.tif", package = "SELECTRdata")
dem <- terra::rast(dem)

gpkg <- system.file("extdata", "thompsoncreek.gpkg", package = "SELECTRdata")
wbd <- terra::vect(gpkg, layer = "wbd")

dem <- terra::mask(dem, wbd,
                   filename = tempfile(fileext = ".tif"))
## set the following GDAL options to connect to
## MRLC's AWS S3 bucket
set_gdal_config("AWS_NO_SIGN_REQUEST", "YES")

## download the NLCD file cropped to the extents of the watershed
nlcd <- SELECTRdata::download_nlcd(template = dem, 
                                   overwrite = TRUE,
                                   progress = 1)
#> |---------|---------|---------|---------|=========================================                                          
plot(nlcd)
plot(wbd, add = TRUE)

FEMA US Buildings

buildings <- download_buildings(template = dem)
plot(buildings)

TIGER Counties

cen_blocks <- download_census_blocks(dem, "2020")
plot(cen_blocks, "POP100")

counties <- download_counties(dem)
plot(counties)

You’ll still need to render README.Rmd regularly, to keep README.md up-to-date. devtools::build_readme() is handy for this.

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Experimental data retrieval package for developing SELECT

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