Submit a query to the Soil Data Access (SDA) REST/JSON web-service and return the results as a data.frame. There is a 100,000 record limit and 32Mb JSON serializer limit, per query. Queries should contain a WHERE statement or JOIN condition to limit the number of rows affected / returned. Consider wrapping calls to SDA_query in a function that can iterate over logical chunks (e.g. areasymbol, mukey, cokey, etc.). The function makeChunks can help with such iteration.

SDA_query(q)

Arguments

q

A valid T-SQL query surrounded by double quotes

Value

a data.frame result (NULL if empty, try-error on error)

Details

The SDA website can be found at https://sdmdataaccess.nrcs.usda.gov and query examples can be found at https://sdmdataaccess.nrcs.usda.gov/QueryHelp.aspx. A library of query examples can be found at https://nasis.sc.egov.usda.gov/NasisReportsWebSite/limsreport.aspx?report_name=SDA-SQL_Library_Home.

SSURGO (detailed soil survey) and STATSGO (generalized soil survey) data are stored together within SDA. This means that queries that don't specify an area symbol may result in a mixture of SSURGO and STATSGO records. See the examples below and the SDA Tutorial for details.

Note

This function requires the httr, jsonlite, and XML packages

See also

Author

D.E. Beaudette

Examples

# \donttest{ if(requireNamespace("curl") & curl::has_internet()) { ## get SSURGO export date for all soil survey areas in California # there is no need to filter STATSGO # because we are filtering on SSURGO area symbols q <- "SELECT areasymbol, saverest FROM sacatalog WHERE areasymbol LIKE 'CA%';" x <- SDA_query(q) head(x) ## get SSURGO component data associated with the ## Amador series / major component only # this query must explicitly filter out STATSGO data q <- "SELECT cokey, compname, comppct_r FROM legend INNER JOIN mapunit mu ON mu.lkey = legend.lkey INNER JOIN component co ON mu.mukey = co.mukey WHERE legend.areasymbol != 'US' AND compname = 'Amador';" res <- SDA_query(q) str(res) ## get component-level data for a specific soil survey area (Yolo county, CA) # there is no need to filter STATSGO because the query contains # an implicit selection of SSURGO data by areasymbol q <- "SELECT component.mukey, cokey, comppct_r, compname, taxclname, taxorder, taxsuborder, taxgrtgroup, taxsubgrp FROM legend INNER JOIN mapunit ON mapunit.lkey = legend.lkey LEFT OUTER JOIN component ON component.mukey = mapunit.mukey WHERE legend.areasymbol = 'CA113' ;" res <- SDA_query(q) str(res) ## get tabular data based on result from spatial query # there is no need to filter STATSGO because # SDA_Get_Mukey_from_intersection_with_WktWgs84() implies SSURGO # # requires raster and rgeos packages because raster is suggested # and rgeos is additional if(require(raster) & require(rgeos)) { # text -> bbox -> WKT # xmin, xmax, ymin, ymax b <- c(-120.9, -120.8, 37.7, 37.8) p <- writeWKT(as(extent(b), 'SpatialPolygons')) q <- paste0("SELECT mukey, cokey, compname, comppct_r FROM component WHERE mukey IN (SELECT DISTINCT mukey FROM SDA_Get_Mukey_from_intersection_with_WktWgs84('", p, "')) ORDER BY mukey, cokey, comppct_r DESC") x <- SDA_query(q) str(x) } }
#> single result set, returning a data.frame
#> single result set, returning a data.frame
#> 'data.frame': 54 obs. of 3 variables: #> $ cokey : int 21097183 21588783 21108405 21128710 21139862 21622626 21830881 21156654 21097182 21096537 ... #> $ compname : chr "Amador" "Amador" "Amador" "Amador" ... #> $ comppct_r: int 25 10 3 3 1 10 85 5 7 45 ... #> - attr(*, "SDA_id")= chr "Table"
#> single result set, returning a data.frame
#> 'data.frame': 608 obs. of 9 variables: #> $ mukey : int 459208 459208 459208 459208 459209 459209 459209 459209 459209 459210 ... #> $ cokey : int 21463250 21463251 21463252 21463253 21463254 21463255 21463256 21463257 21463258 21463259 ... #> $ comppct_r : int 85 5 5 5 85 2 5 5 3 5 ... #> $ compname : chr "Balcom" "Positas" "Sehorn" "Corning" ... #> $ taxclname : chr "Fine-loamy, mixed, thermic Calcixerollic Xerochrepts" NA NA NA ... #> $ taxorder : chr "Inceptisols" NA NA NA ... #> $ taxsuborder: chr "Ochrepts" NA NA NA ... #> $ taxgrtgroup: chr "Xerochrepts" NA NA NA ... #> $ taxsubgrp : chr "Calcixerollic Xerochrepts" NA NA NA ... #> - attr(*, "SDA_id")= chr "Table"
#> Loading required package: raster
#> #> Attaching package: 'raster'
#> The following objects are masked from 'package:aqp': #> #> metadata, metadata<-
#> Loading required package: rgeos
#> rgeos version: 0.5-8, (SVN revision 679) #> GEOS runtime version: 3.9.1-CAPI-1.14.2 #> Please note that rgeos will be retired by the end of 2023, #> plan transition to sf functions using GEOS at your earliest convenience. #> GEOS using OverlayNG #> Linking to sp version: 1.4-5 #> Polygon checking: TRUE
#> single result set, returning a data.frame
#> 'data.frame': 337 obs. of 4 variables: #> $ mukey : int 462527 462527 462527 462541 462541 462541 462541 462554 462554 462554 ... #> $ cokey : int 21830875 21830876 21830877 21831125 21831126 21831127 21831128 21830903 21830904 21830905 ... #> $ compname : chr "Madera" "Alamo" "San Joaquin" "Chualar" ... #> $ comppct_r: int 10 85 5 85 5 5 5 5 10 85 ... #> - attr(*, "SDA_id")= chr "Table"
# }