Nothing
# get the series extent from SEE pre-cached GeoJSON data and plot on Google Maps
seriesExtentAsGmap <- function(s, timeout=60, exp=1.25) {
if(!requireNamespace('dismo', quietly=TRUE) & !requireNamespace('raster', quietly=TRUE) & !requireNamespace('rgdal', quietly=TRUE))
stop('please install the `raster`, `rgdal` and `dismo` packages', call.=FALSE)
# load series extent data in WGS84 GCS
x <- seriesExtent(s, timeout)
# make extent object around sites, in geographic coordinates
e <- raster::extent(spTransform(x, CRS('+proj=longlat')))
# grab ref. to google maps
g <- dismo::gmap(e, exp=exp)
# convert our points to Mercatur projection
x.M <- spTransform(x, CRS('+proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null +no_defs'))
# plot google map, and our point of interest
plot(g, interpolate=TRUE)
plot(x.M, col=rgb(1, 0, 0, alpha=0.5), add=TRUE)
}
# get pre-cached series extent GeoJSON from SoilWeb server
seriesExtent <- function(s, timeout=60) {
if(!requireNamespace('rgdal', quietly=TRUE))
stop('please install the `rgdal` package', call.=FALSE)
# encode series name
s <- gsub(pattern=' ', replacement='_', x=tolower(s))
# base URL to cached data
u <- URLencode(paste0('http://casoilresource.lawr.ucdavis.edu/series-extent-cache/json/', s, '.json'))
# init temp files / dirs
td <- tempdir()
tf.json <- tempfile(fileext='json')
# download GeoJSON file
download.file(url=u, destfile=tf.json, extra=c(timeout=timeout), quiet=TRUE)
# load into sp object and clean-up
x <- rgdal::readOGR(dsn=tf.json, layer='OGRGeoJSON', verbose=FALSE)
unlink(tf.json)
# return in WGS84 GCS
return(x)
}
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