brownag

Sys.setenv(PYTHONHOME = "C:\\Program Files\\Python310")

library(rgeedim)
library(terra)
library(soilDB)

officeid <- "2SON"
ssaid <- "CA732"
scaleres <- 10
destdir <- paste0("D:/", officeid)

brownag

#' Download nationalsoilmoisture.com CONUS Soil Moisture Percentile ASCII Grids
#'
#' @return data.frame containing file name root, grid label, source URL and download status
#' @export
#'
#' @examples
#' # library(terra)
#' 
#' # options(timeout = 300)
#' # nsm_products <- get_NSM_current()

brownag

# remotes::install_github("brownag/rgeedim")
library(rgeedim)
library(terra)
library(soilDB)
library(gifski)

# this could be any extent, using a single MU polygon as a small example
bb <- fetchSDA_spatial(460954)
bb$pID <- 1:nrow(bb)
bb2 <- terra::intersect(vect(data.frame(y=39.974942, x=-121.961947), geom=c("x","y"), crs="EPSG:4326"), vect(bb))

brownag

The GeoPackage standard has an extension that allows for Rtree spatial indexes (http://www.geopackage.org/guidance/extensions/rtree_spatial_indexes.html).

When writing a SpatVector to GeoPackage, we get an Rtree "for free." But I currently don't have any workflows that really make use of it. Most of my GPKG usage is as a "storage" medium, rather than for analysis. GPKG is so much better than a directory full of shapefiles (and all their ancillary files) exploring first-class geopackage support for {terra} is https://github.com/brownag/gpkg.

For example:

library(terra)
v <- vect(system.file("ex", "lux.shp", package = "terra"))

brownag

# demonstration of soilDB SSURGO geopackage functionality for _raster_ (gNATSGO) data 
library(soilDB)
library(terra)
library(gpkg) # remotes::install_github("brownag/gpkg")

# download gSSURGO for an arbitrary extent
bb <- fetchSDA_spatial("CA760", by.col = "areasymbol", geom.src = "sapolygon")

# get mukey raster from SoilWeb web coverage service (TODO: limited to 5000x5000)
wcs <- mukey.wcs(as.polygons(ext(bb) / 2, "EPSG:4326"), db = "gNATSGO")

brownag

# demonstration of soilDB SSURGO geopackage functionality for _vector_ data
library(soilDB)
library(terra)

# increase timeout for VPN
options(timeout = 360)

# download SSURGO databases 
downloadSSURGO(areasymbols = c("CA802","CA740","CA732","CA792","CA668","CA760"), destdir = "myproject")

brownag

# remotes::install_github("brownag/rgeedim")
library(rgeedim)
library(terra)
library(soilDB)

# this could be any extent, using a single SSA as a small example
bb <- fetchSDA_spatial("CA630", by.col = "areasymbol", geom.src = 'sapolygon')

## authenticate if needed
# gd_authenticate(auth_mode = "notebook")

brownag

library(soilDB)
library(rgeedim) # remotes::install_github("brownag/rgeedim")

f <- fetchSDA("compname = 'Jacinto'", duplicates = TRUE)
s <- fetchSDA_spatial(f$nationalmusym, by.col = 'nationalmusym')

plot(s["nationalmusym"])

gd_initialize()

brownag

2022-07-14

library(aqp)

## This is aqp 1.43

library(soilDB)

brownag

# remotes::install_github("brownag/rgeedim")

library(rgeedim)
library(soilDB)
library(terra)
library(viridis)

# earth engine setup
rgeedim::gd_initialize()
# ee <- reticulate::import("ee")