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 xml2 packages

See also

Author

D.E. Beaudette

Examples

# \donttest{
if(requireNamespace("curl") & requireNamespace("wk") &
   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
  p <- wk::as_wkt(wk::rct(-120.9, 37.7, -120.8, 37.8))
  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)
 }
#> Loading required namespace: wk
#> 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 21139740 21622626 21830881 21157110 21097182 21096537 ...
#>  $ compname : chr  "Amador" "Amador" "Amador" "Amador" ...
#>  $ comppct_r: int  25 10 3 3 10 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"
#> 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"
# }