R/WCS-utils.R
In ncss-tech/soilDB: Soil Database Interface
Defines functions
.prepare_AEA_AOI
WCS_details
Documented in
WCS_details
#' @title Web Coverage Services Details
#'
#' @description List variables or databases provided by soilDB web coverage service (WCS) abstraction. These lists will be expanded in future versions.
#'
#' @param wcs a WCS label ('mukey', 'ISSR800', or 'soilColor')
#'
#' @return a `data.frame`
#' @export
#'
#' @examples
#'
#' WCS_details(wcs = 'ISSR800')
WCS_details <- function(wcs = c('mukey', 'ISSR800', 'soilColor')) {
## TODO: add md5sum + vintage
# select a WCS
wcs <- match.arg(wcs)
spec <- switch(wcs,
'mukey' = .mukey.spec,
'ISSR800' = .ISSR800.spec,
'soilColor' = .soilColor.spec
)
## TODO: spec names / DSN are assumed to be identical
## it would be nice to allow for more connotative names
# all(names(spec) == sapply(spec, '[[', 'dsn'))
# extract relevant details
v <- lapply(spec, function(i) {
data.frame(
var = i[['dsn']],
description = i[['desc']],
stringsAsFactors = FALSE
)
})
# flatten / re-format
v <- do.call('rbind', v)
row.names(v) <- as.character(1:nrow(v))
# alpha order simpler to use
v <- v[order(v[['var']]), ]
# ugh, mukey.wcs() uses 'db' vs 'var
if (wcs == 'mukey') {
names(v)[1] <- 'db'
}
return(v)
}
# obj: list(aoi, crs) or Spatial*, sf, sfc, bbox object
# res: grid resolution in native CRS (meters) [ISSR-800: 800, gNATSGO: 30]
# native_crs: native CRS, usually EPSG:5070
# outside of CONUS will be different
.prepare_AEA_AOI <- function(obj, res, native_crs = 'EPSG:5070') {
return_class <- 'terra'
# pre-processing of classes to terra/sf
if (inherits(obj, 'RasterLayer') ||
inherits(obj, 'RasterStack') ||
inherits(obj, 'RasterBrick')) {
if (!requireNamespace("terra"))
stop("package terra is required to convert RasterLayer objects to an AOI", call. = FALSE)
obj <- terra::rast(obj)
return_class <- 'raster'
} else if (inherits(obj, 'bbox')) {
# note: the inherits(, 'Spatial') will bug out with a bbox, so it must come after
# do nothing
} else if (inherits(obj, 'Spatial')) {
if (!requireNamespace("sf"))
stop("package sf is required to convert Spatial objects to an AOI", call. = FALSE)
# convert to sf
obj <- sf::st_as_sf(obj)
return_class <- 'raster'
}
# convert AOI to sf/terra object and assign CRS
if (inherits(obj, 'SpatRaster') || inherits(obj, 'SpatVector')) {
if (!requireNamespace("terra"))
stop("package terra is required", call. = FALSE)
p <- terra::as.polygons(terra::ext(obj), crs = terra::crs(obj))
} else {
if (!requireNamespace("sf"))
stop("package 'sf' is required to use an sf, sfc or bbox object as an AOI", call. = FALSE)
if (inherits(obj, c('sf', 'sfc', 'bbox'))) {
# create bbox around sf/sfc/bbox, create simple feature collection
p <- sf::st_as_sfc(sf::st_bbox(obj))
rm(obj)
# explicitly check the presence of the two list elements, and length/type of aoi
} else if (!is.null(obj$aoi) && !is.null(obj$crs) &&
is.numeric(obj$aoi) && (length(obj$aoi) == 4)) {
p <- sf::st_as_sf(wk::rct(
xmin = obj$aoi[1],
ymin = obj$aoi[2],
xmax = obj$aoi[3],
ymax = obj$aoi[4],
crs = obj$crs
))
} else {
stop('invalid `aoi` specification', call. = FALSE)
}
}
# CONUS grids: ISSR800, gNATSGO, gSSURGO, STATSGO, RSS
#
# NOTE: EPSG:6350 NAD83 (2011) v.s. EPSG:5070 NAD83
# we use EPSG:5070 (https://github.com/ncss-tech/soilDB/issues/205)
# NOTE: +init=epsg:XXXX syntax is deprecated in GDAL. It might return a CRS with a non-EPSG compliant axis order.
# transform bounding polygon to WCS CRS
# could be either,
# st_bbox is commonly converted to 'sfc'
if (inherits(p, 'sfc') || inherits(p, 'sf')) {
p <- sf::st_transform(p, crs = native_crs)
e.native <- sf::st_bbox(p)
# AOI and image calculations in native CRS
# create BBOX used for WMS
# xmin, ymin, xmax, ymax
aoi.native <- e.native
} else if (inherits(p, 'SpatVector')) {
p <- terra::project(p, native_crs)
e.native <- terra::ext(p)
# AOI and image calculations in native CRS
# create BBOX used for WMS
# xmin, ymin, xmax, ymax
aoi.native <- e.native[c(1,3,2,4)]
}
# these are used for calculating xmax/ymax for WCS request
# xmax - xmin
w <- round(abs(aoi.native[3] - aoi.native[1]) / res)
# ymax - ymin
h <- round(abs(aoi.native[4] - aoi.native[2]) / res)
res <- list(bbox = aoi.native,
width = w,
height = h)
attr(res, '.input_class') <- return_class
res
}
## moist soil colors
# these are 16bit (unsigned) integers
# TODO: consider moving soil color LUT to wcs-files
# these maps all share the same RAT
.soilColorRAT <- 'http://casoilresource.lawr.ucdavis.edu/wcs/soilcolor/unique-moist-color-LUT.csv'
.soilColor.spec <- list(
'sc005cm' = list(
dsn = 'sc005cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 5cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc010cm' = list(
dsn = 'sc010cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 10cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc015cm' = list(
dsn = 'sc015cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 15cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc025cm' = list(
dsn = 'sc025cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 25cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc050cm' = list(
dsn = 'sc050cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 50cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc075cm' = list(
dsn = 'sc075cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 75cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc100cm' = list(
dsn = 'sc100cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 100cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc125cm' = list(
dsn = 'sc125cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 125cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc005cm_hr' = list(
dsn = 'sc005cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 5cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc010cm_hr' = list(
dsn = 'sc010cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 10cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc015cm_hr' = list(
dsn = 'sc015cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 15cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc025cm_hr' = list(
dsn = 'sc025cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 25cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc050cm_hr' = list(
dsn = 'sc050cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 50cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc075cm_hr' = list(
dsn = 'sc075cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 75cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc100cm_hr' = list(
dsn = 'sc100cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 100cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc125cm_hr' = list(
dsn = 'sc125cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 125cm (30m)',
na = 0,
rat = .soilColorRAT
)
)
## TODO: next release include suggested colors
# ISSR-800 layers and basic metadata
.ISSR800.spec <- list(
'statsgo_pct' = list(
dsn = 'statsgo_pct',
type = 'GEOTIFF_FLOAT',
desc = 'STATSGO data available, fraction of 800x800m grid cell',
na = -9999,
rat = NULL
),
'ssurgo_pct' = list(
dsn = 'ssurgo_pct',
type = 'GEOTIFF_FLOAT',
desc = 'SSURGO data available, fraction of 800x800m grid cell',
na = -9999,
rat = NULL
),
'om_kg_sq_m' = list(
dsn = 'om_kg_sq_m',
type = 'GEOTIFF_FLOAT',
desc = 'Total Soil Organic Matter (kg/m^2)',
na = -9999,
rat = NULL
),
'caco3_kg_sq_m' = list(
dsn = 'caco3_kg_sq_m',
type = 'GEOTIFF_FLOAT',
desc = 'Total CaCO3 (kg/m^2)',
na = -9999,
rat = NULL
),
'ec_05cm' = list(
dsn = 'ec_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'EC 0-5cm depth (dS/m)',
na = -9999,
rat = NULL
),
'ec_025cm' = list(
dsn = 'ec_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'EC 0-25cm depth (dS/m)',
na = -9999,
rat = NULL
),
'cec_05cm' = list(
dsn = 'cec_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'CEC at pH 7 0-5cm depth (cmol[+]/kg)',
na = -9999,
rat = NULL
),
'cec_025cm' = list(
dsn = 'cec_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'CEC at pH 7 0-25cm depth (cmol[+]/kg)',
na = -9999,
rat = NULL
),
'cec_050cm' = list(
dsn = 'cec_050cm',
type = 'GEOTIFF_FLOAT',
desc = 'CEC at pH 7 0-50cm depth (cmol[+]/kg)',
na = -9999,
rat = NULL
),
'paws' = list(
dsn = 'paws',
type = 'GEOTIFF_FLOAT',
desc = 'total plant available water storage (cm water)',
na = -9999,
rat = NULL
),
'paws_050cm' = list(
dsn = 'paws_050cm',
type = 'GEOTIFF_FLOAT',
desc = 'plant available water storage 0-50cm depth (cm water)',
na = -9999,
rat = NULL
),
'paws_025cm' = list(
dsn = 'paws_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'plant available water storage 0-25cm depth (cm water)',
na = -9999,
rat = NULL
),
'ph_05cm' = list(
dsn = 'ph_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'pH 1:1 H2O 0-5cm depth',
na = -9999,
rat = NULL
),
'ph_025cm' = list(
dsn = 'ph_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'pH 1:1 H2O 0-25cm depth',
na = -9999,
rat = NULL
),
'ph_2550cm' = list(
dsn = 'ph_2550cm',
type = 'GEOTIFF_FLOAT',
desc = 'pH 1:1 H2O 25-50cm depth',
na = -9999,
rat = NULL
),
'ph_3060cm' = list(
dsn = 'ph_3060cm',
type = 'GEOTIFF_FLOAT',
desc = 'pH 1:1 H2O 30-60cm depth',
na = -9999,
rat = NULL
),
'clay_05cm' = list(
dsn = 'clay_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'clay percent 0-5cm depth',
na = -9999,
rat = NULL
),
'clay_025cm' = list(
dsn = 'clay_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'clay percent 0-25cm depth',
na = -9999,
rat = NULL
),
'clay_2550cm' = list(
dsn = 'clay_2550cm',
type = 'GEOTIFF_FLOAT',
desc = 'clay percent 25-50cm depth',
na = -9999,
rat = NULL
),
'clay_3060cm' = list(
dsn = 'clay_3060cm',
type = 'GEOTIFF_FLOAT',
desc = 'clay percent 30-60cm depth',
na = -9999,
rat = NULL
),
'sand_05cm' = list(
dsn = 'sand_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'sand percent 0-5cm depth',
na = -9999,
rat = NULL
),
'sand_025cm' = list(
dsn = 'sand_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'sand percent 0-25cm depth',
na = -9999,
rat = NULL
),
'sand_2550cm' = list(
dsn = 'sand_2550cm',
type = 'GEOTIFF_FLOAT',
desc = 'sand percent 25-50cm depth',
na = -9999,
rat = NULL
),
'sand_3060cm' = list(
dsn = 'sand_3060cm',
type = 'GEOTIFF_FLOAT',
desc = 'sand percent 30-60cm depth',
na = -9999,
rat = NULL
),
'silt_05cm' = list(
dsn = 'silt_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'silt percent 0-5cm depth',
na = -9999,
rat = NULL
),
'silt_025cm' = list(
dsn = 'silt_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'silt percent 0-25cm depth',
na = -9999,
rat = NULL
),
'silt_2550cm' = list(
dsn = 'silt_2550cm',
type = 'GEOTIFF_FLOAT',
desc = 'silt percent 25-50cm depth',
na = -9999,
rat = NULL
),
'silt_3060cm' = list(
dsn = 'silt_3060cm',
type = 'GEOTIFF_FLOAT',
desc = 'silt percent 30-60cm depth',
na = -9999,
rat = NULL
),
'sar' = list(
dsn = 'sar',
type = 'GEOTIFF_FLOAT',
desc = 'SAR, entire profile',
na = -9999,
rat = NULL
),
'series_name' = list(
dsn = 'series_name',
type = 'GEOTIFF_16',
desc = 'Soil Series Name',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/series_name.csv'
),
'hydgrp' = list(
dsn = 'hydgrp',
type = 'GEOTIFF_BYTE',
desc = 'Hydrologic Soil Group',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/hydgrp.csv'
),
'drainage_class' = list(
dsn = 'drainage_class',
type = 'GEOTIFF_BYTE',
desc = 'Soil Drainage Class',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/drainage_class.csv'
),
'weg' = list(
dsn = 'weg',
type = 'GEOTIFF_BYTE',
desc = 'Wind Erodibility Group',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/weg.csv'
),
'wei' = list(
dsn = 'wei',
type = 'GEOTIFF_16',
na = 0,
desc = 'Wind Erodibility Index',
rat = NULL
),
'str' = list(
dsn = 'str',
type = 'GEOTIFF_BYTE',
desc = 'Soil Temperature Regime',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/str.csv'
),
'soilorder' = list(
dsn = 'soilorder',
type = 'GEOTIFF_BYTE',
desc = 'Soil Taxonomy: Soil Order',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/soilorder.csv'
),
'suborder' = list(
dsn = 'suborder',
type = 'GEOTIFF_BYTE',
desc = 'Soil Taxonomy: Suborder',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/suborder.csv'
),
'greatgroup' = list(
dsn = 'greatgroup',
type = 'GEOTIFF_BYTE',
desc = 'Soil Taxonomy: Greatgroup',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/greatgroup.csv'
),
'texture_05cm' = list(
dsn = 'texture_05cm',
type = 'GEOTIFF_BYTE',
desc = 'Soil Texture Class, 0-5cm',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/texture_05.csv'
),
'texture_025cm' = list(
dsn = 'texture_025cm',
type = 'GEOTIFF_BYTE',
desc = 'Soil Texture Class, 0-25cm',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/texture_025.csv'
),
'texture_2550cm' = list(
dsn = 'texture_2550cm',
type = 'GEOTIFF_BYTE',
desc = 'Soil Texture Class, 25-50cm',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/texture_2550.csv'
),
'lcc_irrigated' = list(
dsn = 'lcc_irrigated',
type = 'GEOTIFF_BYTE',
desc = 'Land Capability Class, irrigated',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/lcc.csv'
),
'lcc_nonirrigated' = list(
dsn = 'lcc_nonirrigated',
type = 'GEOTIFF_BYTE',
desc = 'Land Capability Class, non-irrigated',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/lcc.csv'
)
)
##
## TODO:
##
## * host WCS specifications as JSON on server so that changes don't require a soilDB release
## * each suite of products should have their own spec
## * remove xx.spec lists from soilDB
## * top-level names in specs via JSON are used to determine available products
## * are we just re-inventing a crummy version of STAC?
##
.mukey.spec <- list(
# FY24 data were exported as INT32 instead of UINT32
# NODATA is -2147483648
'gnatsgo' = list(
dsn = 'gnatsgo',
type = 'GEOTIFF_FLOAT',
desc = 'gNATSGO map unit keys',
vintage = 'FY2024',
na = 2147483647L,
res = 30,
rat = NULL
),
'gssurgo' = list(
dsn = 'gssurgo',
type = 'GEOTIFF_FLOAT',
desc = 'gSSURGO map unit keys',
vintage = 'FY2024',
na = 2147483647L,
res = 30,
rat = NULL
),
'hi_ssurgo' = list(
dsn = 'hi_ssurgo',
type = 'GEOTIFF_FLOAT',
desc = 'HI map unit keys (experimental)',
vintage = 'FY2024',
na = 4294967295,
res = 30,
rat = NULL
),
'pr_ssurgo' = list(
dsn = 'pr_ssurgo',
type = 'GEOTIFF_FLOAT',
desc = 'PR map unit keys (experimental)',
vintage = 'FY2024',
na = 4294967295,
res = 30,
rat = NULL
),
'statsgo' = list(
dsn = 'statsgo',
type = 'GEOTIFF_FLOAT',
desc = 'STATSGO2 map unit keys',
vintage = 'FY2023',
na = 0L,
res = 300,
rat = NULL
),
'rss' = list(
dsn = 'rss',
type = 'GEOTIFF_FLOAT',
desc = 'RSS map unit keys',
vintage = 'FY2023',
na = 0L,
res = 10,
rat = NULL
)
)
ncss-tech/soilDB documentation built on May 5, 2024, 2:21 a.m.
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Defines functions .prepare_AEA_AOI WCS_details
Documented in WCS_details
#' @title Web Coverage Services Details
#'
#' @description List variables or databases provided by soilDB web coverage service (WCS) abstraction. These lists will be expanded in future versions.
#'
#' @param wcs a WCS label ('mukey', 'ISSR800', or 'soilColor')
#'
#' @return a `data.frame`
#' @export
#'
#' @examples
#'
#' WCS_details(wcs = 'ISSR800')
WCS_details <- function(wcs = c('mukey', 'ISSR800', 'soilColor')) {
## TODO: add md5sum + vintage
# select a WCS
wcs <- match.arg(wcs)
spec <- switch(wcs,
'mukey' = .mukey.spec,
'ISSR800' = .ISSR800.spec,
'soilColor' = .soilColor.spec
)
## TODO: spec names / DSN are assumed to be identical
## it would be nice to allow for more connotative names
# all(names(spec) == sapply(spec, '[[', 'dsn'))
# extract relevant details
v <- lapply(spec, function(i) {
data.frame(
var = i[['dsn']],
description = i[['desc']],
stringsAsFactors = FALSE
)
})
# flatten / re-format
v <- do.call('rbind', v)
row.names(v) <- as.character(1:nrow(v))
# alpha order simpler to use
v <- v[order(v[['var']]), ]
# ugh, mukey.wcs() uses 'db' vs 'var
if (wcs == 'mukey') {
names(v)[1] <- 'db'
}
return(v)
}
# obj: list(aoi, crs) or Spatial*, sf, sfc, bbox object
# res: grid resolution in native CRS (meters) [ISSR-800: 800, gNATSGO: 30]
# native_crs: native CRS, usually EPSG:5070
# outside of CONUS will be different
.prepare_AEA_AOI <- function(obj, res, native_crs = 'EPSG:5070') {
return_class <- 'terra'
# pre-processing of classes to terra/sf
if (inherits(obj, 'RasterLayer') ||
inherits(obj, 'RasterStack') ||
inherits(obj, 'RasterBrick')) {
if (!requireNamespace("terra"))
stop("package terra is required to convert RasterLayer objects to an AOI", call. = FALSE)
obj <- terra::rast(obj)
return_class <- 'raster'
} else if (inherits(obj, 'bbox')) {
# note: the inherits(, 'Spatial') will bug out with a bbox, so it must come after
# do nothing
} else if (inherits(obj, 'Spatial')) {
if (!requireNamespace("sf"))
stop("package sf is required to convert Spatial objects to an AOI", call. = FALSE)
# convert to sf
obj <- sf::st_as_sf(obj)
return_class <- 'raster'
}
# convert AOI to sf/terra object and assign CRS
if (inherits(obj, 'SpatRaster') || inherits(obj, 'SpatVector')) {
if (!requireNamespace("terra"))
stop("package terra is required", call. = FALSE)
p <- terra::as.polygons(terra::ext(obj), crs = terra::crs(obj))
} else {
if (!requireNamespace("sf"))
stop("package 'sf' is required to use an sf, sfc or bbox object as an AOI", call. = FALSE)
if (inherits(obj, c('sf', 'sfc', 'bbox'))) {
# create bbox around sf/sfc/bbox, create simple feature collection
p <- sf::st_as_sfc(sf::st_bbox(obj))
rm(obj)
# explicitly check the presence of the two list elements, and length/type of aoi
} else if (!is.null(obj$aoi) && !is.null(obj$crs) &&
is.numeric(obj$aoi) && (length(obj$aoi) == 4)) {
p <- sf::st_as_sf(wk::rct(
xmin = obj$aoi[1],
ymin = obj$aoi[2],
xmax = obj$aoi[3],
ymax = obj$aoi[4],
crs = obj$crs
))
} else {
stop('invalid `aoi` specification', call. = FALSE)
}
}
# CONUS grids: ISSR800, gNATSGO, gSSURGO, STATSGO, RSS
#
# NOTE: EPSG:6350 NAD83 (2011) v.s. EPSG:5070 NAD83
# we use EPSG:5070 (https://github.com/ncss-tech/soilDB/issues/205)
# NOTE: +init=epsg:XXXX syntax is deprecated in GDAL. It might return a CRS with a non-EPSG compliant axis order.
# transform bounding polygon to WCS CRS
# could be either,
# st_bbox is commonly converted to 'sfc'
if (inherits(p, 'sfc') || inherits(p, 'sf')) {
p <- sf::st_transform(p, crs = native_crs)
e.native <- sf::st_bbox(p)
# AOI and image calculations in native CRS
# create BBOX used for WMS
# xmin, ymin, xmax, ymax
aoi.native <- e.native
} else if (inherits(p, 'SpatVector')) {
p <- terra::project(p, native_crs)
e.native <- terra::ext(p)
# AOI and image calculations in native CRS
# create BBOX used for WMS
# xmin, ymin, xmax, ymax
aoi.native <- e.native[c(1,3,2,4)]
}
# these are used for calculating xmax/ymax for WCS request
# xmax - xmin
w <- round(abs(aoi.native[3] - aoi.native[1]) / res)
# ymax - ymin
h <- round(abs(aoi.native[4] - aoi.native[2]) / res)
res <- list(bbox = aoi.native,
width = w,
height = h)
attr(res, '.input_class') <- return_class
res
}
## moist soil colors
# these are 16bit (unsigned) integers
# TODO: consider moving soil color LUT to wcs-files
# these maps all share the same RAT
.soilColorRAT <- 'http://casoilresource.lawr.ucdavis.edu/wcs/soilcolor/unique-moist-color-LUT.csv'
.soilColor.spec <- list(
'sc005cm' = list(
dsn = 'sc005cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 5cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc010cm' = list(
dsn = 'sc010cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 10cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc015cm' = list(
dsn = 'sc015cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 15cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc025cm' = list(
dsn = 'sc025cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 25cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc050cm' = list(
dsn = 'sc050cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 50cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc075cm' = list(
dsn = 'sc075cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 75cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc100cm' = list(
dsn = 'sc100cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 100cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc125cm' = list(
dsn = 'sc125cm',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 125cm (270m)',
na = 0,
rat = .soilColorRAT
),
'sc005cm_hr' = list(
dsn = 'sc005cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 5cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc010cm_hr' = list(
dsn = 'sc010cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 10cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc015cm_hr' = list(
dsn = 'sc015cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 15cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc025cm_hr' = list(
dsn = 'sc025cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 25cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc050cm_hr' = list(
dsn = 'sc050cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 50cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc075cm_hr' = list(
dsn = 'sc075cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 75cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc100cm_hr' = list(
dsn = 'sc100cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 100cm (30m)',
na = 0,
rat = .soilColorRAT
),
'sc125cm_hr' = list(
dsn = 'sc125cm_hr',
type = 'GEOTIFF_16',
desc = 'Moist soil color, 125cm (30m)',
na = 0,
rat = .soilColorRAT
)
)
## TODO: next release include suggested colors
# ISSR-800 layers and basic metadata
.ISSR800.spec <- list(
'statsgo_pct' = list(
dsn = 'statsgo_pct',
type = 'GEOTIFF_FLOAT',
desc = 'STATSGO data available, fraction of 800x800m grid cell',
na = -9999,
rat = NULL
),
'ssurgo_pct' = list(
dsn = 'ssurgo_pct',
type = 'GEOTIFF_FLOAT',
desc = 'SSURGO data available, fraction of 800x800m grid cell',
na = -9999,
rat = NULL
),
'om_kg_sq_m' = list(
dsn = 'om_kg_sq_m',
type = 'GEOTIFF_FLOAT',
desc = 'Total Soil Organic Matter (kg/m^2)',
na = -9999,
rat = NULL
),
'caco3_kg_sq_m' = list(
dsn = 'caco3_kg_sq_m',
type = 'GEOTIFF_FLOAT',
desc = 'Total CaCO3 (kg/m^2)',
na = -9999,
rat = NULL
),
'ec_05cm' = list(
dsn = 'ec_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'EC 0-5cm depth (dS/m)',
na = -9999,
rat = NULL
),
'ec_025cm' = list(
dsn = 'ec_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'EC 0-25cm depth (dS/m)',
na = -9999,
rat = NULL
),
'cec_05cm' = list(
dsn = 'cec_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'CEC at pH 7 0-5cm depth (cmol[+]/kg)',
na = -9999,
rat = NULL
),
'cec_025cm' = list(
dsn = 'cec_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'CEC at pH 7 0-25cm depth (cmol[+]/kg)',
na = -9999,
rat = NULL
),
'cec_050cm' = list(
dsn = 'cec_050cm',
type = 'GEOTIFF_FLOAT',
desc = 'CEC at pH 7 0-50cm depth (cmol[+]/kg)',
na = -9999,
rat = NULL
),
'paws' = list(
dsn = 'paws',
type = 'GEOTIFF_FLOAT',
desc = 'total plant available water storage (cm water)',
na = -9999,
rat = NULL
),
'paws_050cm' = list(
dsn = 'paws_050cm',
type = 'GEOTIFF_FLOAT',
desc = 'plant available water storage 0-50cm depth (cm water)',
na = -9999,
rat = NULL
),
'paws_025cm' = list(
dsn = 'paws_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'plant available water storage 0-25cm depth (cm water)',
na = -9999,
rat = NULL
),
'ph_05cm' = list(
dsn = 'ph_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'pH 1:1 H2O 0-5cm depth',
na = -9999,
rat = NULL
),
'ph_025cm' = list(
dsn = 'ph_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'pH 1:1 H2O 0-25cm depth',
na = -9999,
rat = NULL
),
'ph_2550cm' = list(
dsn = 'ph_2550cm',
type = 'GEOTIFF_FLOAT',
desc = 'pH 1:1 H2O 25-50cm depth',
na = -9999,
rat = NULL
),
'ph_3060cm' = list(
dsn = 'ph_3060cm',
type = 'GEOTIFF_FLOAT',
desc = 'pH 1:1 H2O 30-60cm depth',
na = -9999,
rat = NULL
),
'clay_05cm' = list(
dsn = 'clay_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'clay percent 0-5cm depth',
na = -9999,
rat = NULL
),
'clay_025cm' = list(
dsn = 'clay_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'clay percent 0-25cm depth',
na = -9999,
rat = NULL
),
'clay_2550cm' = list(
dsn = 'clay_2550cm',
type = 'GEOTIFF_FLOAT',
desc = 'clay percent 25-50cm depth',
na = -9999,
rat = NULL
),
'clay_3060cm' = list(
dsn = 'clay_3060cm',
type = 'GEOTIFF_FLOAT',
desc = 'clay percent 30-60cm depth',
na = -9999,
rat = NULL
),
'sand_05cm' = list(
dsn = 'sand_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'sand percent 0-5cm depth',
na = -9999,
rat = NULL
),
'sand_025cm' = list(
dsn = 'sand_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'sand percent 0-25cm depth',
na = -9999,
rat = NULL
),
'sand_2550cm' = list(
dsn = 'sand_2550cm',
type = 'GEOTIFF_FLOAT',
desc = 'sand percent 25-50cm depth',
na = -9999,
rat = NULL
),
'sand_3060cm' = list(
dsn = 'sand_3060cm',
type = 'GEOTIFF_FLOAT',
desc = 'sand percent 30-60cm depth',
na = -9999,
rat = NULL
),
'silt_05cm' = list(
dsn = 'silt_05cm',
type = 'GEOTIFF_FLOAT',
desc = 'silt percent 0-5cm depth',
na = -9999,
rat = NULL
),
'silt_025cm' = list(
dsn = 'silt_025cm',
type = 'GEOTIFF_FLOAT',
desc = 'silt percent 0-25cm depth',
na = -9999,
rat = NULL
),
'silt_2550cm' = list(
dsn = 'silt_2550cm',
type = 'GEOTIFF_FLOAT',
desc = 'silt percent 25-50cm depth',
na = -9999,
rat = NULL
),
'silt_3060cm' = list(
dsn = 'silt_3060cm',
type = 'GEOTIFF_FLOAT',
desc = 'silt percent 30-60cm depth',
na = -9999,
rat = NULL
),
'sar' = list(
dsn = 'sar',
type = 'GEOTIFF_FLOAT',
desc = 'SAR, entire profile',
na = -9999,
rat = NULL
),
'series_name' = list(
dsn = 'series_name',
type = 'GEOTIFF_16',
desc = 'Soil Series Name',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/series_name.csv'
),
'hydgrp' = list(
dsn = 'hydgrp',
type = 'GEOTIFF_BYTE',
desc = 'Hydrologic Soil Group',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/hydgrp.csv'
),
'drainage_class' = list(
dsn = 'drainage_class',
type = 'GEOTIFF_BYTE',
desc = 'Soil Drainage Class',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/drainage_class.csv'
),
'weg' = list(
dsn = 'weg',
type = 'GEOTIFF_BYTE',
desc = 'Wind Erodibility Group',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/weg.csv'
),
'wei' = list(
dsn = 'wei',
type = 'GEOTIFF_16',
na = 0,
desc = 'Wind Erodibility Index',
rat = NULL
),
'str' = list(
dsn = 'str',
type = 'GEOTIFF_BYTE',
desc = 'Soil Temperature Regime',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/str.csv'
),
'soilorder' = list(
dsn = 'soilorder',
type = 'GEOTIFF_BYTE',
desc = 'Soil Taxonomy: Soil Order',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/soilorder.csv'
),
'suborder' = list(
dsn = 'suborder',
type = 'GEOTIFF_BYTE',
desc = 'Soil Taxonomy: Suborder',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/suborder.csv'
),
'greatgroup' = list(
dsn = 'greatgroup',
type = 'GEOTIFF_BYTE',
desc = 'Soil Taxonomy: Greatgroup',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/greatgroup.csv'
),
'texture_05cm' = list(
dsn = 'texture_05cm',
type = 'GEOTIFF_BYTE',
desc = 'Soil Texture Class, 0-5cm',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/texture_05.csv'
),
'texture_025cm' = list(
dsn = 'texture_025cm',
type = 'GEOTIFF_BYTE',
desc = 'Soil Texture Class, 0-25cm',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/texture_025.csv'
),
'texture_2550cm' = list(
dsn = 'texture_2550cm',
type = 'GEOTIFF_BYTE',
desc = 'Soil Texture Class, 25-50cm',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/texture_2550.csv'
),
'lcc_irrigated' = list(
dsn = 'lcc_irrigated',
type = 'GEOTIFF_BYTE',
desc = 'Land Capability Class, irrigated',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/lcc.csv'
),
'lcc_nonirrigated' = list(
dsn = 'lcc_nonirrigated',
type = 'GEOTIFF_BYTE',
desc = 'Land Capability Class, non-irrigated',
na = 0,
rat = 'http://casoilresource.lawr.ucdavis.edu/800m_grids/RAT/lcc.csv'
)
)
##
## TODO:
##
## * host WCS specifications as JSON on server so that changes don't require a soilDB release
## * each suite of products should have their own spec
## * remove xx.spec lists from soilDB
## * top-level names in specs via JSON are used to determine available products
## * are we just re-inventing a crummy version of STAC?
##
.mukey.spec <- list(
# FY24 data were exported as INT32 instead of UINT32
# NODATA is -2147483648
'gnatsgo' = list(
dsn = 'gnatsgo',
type = 'GEOTIFF_FLOAT',
desc = 'gNATSGO map unit keys',
vintage = 'FY2024',
na = 2147483647L,
res = 30,
rat = NULL
),
'gssurgo' = list(
dsn = 'gssurgo',
type = 'GEOTIFF_FLOAT',
desc = 'gSSURGO map unit keys',
vintage = 'FY2024',
na = 2147483647L,
res = 30,
rat = NULL
),
'hi_ssurgo' = list(
dsn = 'hi_ssurgo',
type = 'GEOTIFF_FLOAT',
desc = 'HI map unit keys (experimental)',
vintage = 'FY2024',
na = 4294967295,
res = 30,
rat = NULL
),
'pr_ssurgo' = list(
dsn = 'pr_ssurgo',
type = 'GEOTIFF_FLOAT',
desc = 'PR map unit keys (experimental)',
vintage = 'FY2024',
na = 4294967295,
res = 30,
rat = NULL
),
'statsgo' = list(
dsn = 'statsgo',
type = 'GEOTIFF_FLOAT',
desc = 'STATSGO2 map unit keys',
vintage = 'FY2023',
na = 0L,
res = 300,
rat = NULL
),
'rss' = list(
dsn = 'rss',
type = 'GEOTIFF_FLOAT',
desc = 'RSS map unit keys',
vintage = 'FY2023',
na = 0L,
res = 10,
rat = NULL
)
)
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