SDA_spatialQuery: Query Soil Data Access by spatial intersection with supplied...

In soilDB: Soil Database Interface

Query Soil Data Access by spatial intersection with supplied geometry

Description

Query SDA (SSURGO / STATSGO) records via spatial intersection with supplied geometries. Input can be SpatialPoints, SpatialLines, or SpatialPolygons objects with a valid CRS. Map unit keys, overlapping polygons, or the spatial intersection of geom + SSURGO / STATSGO polygons can be returned. See details.

Usage

SDA_spatialQuery(
  geom,
  what = "mukey",
  geomIntersection = FALSE,
  geomAcres = TRUE,
  db = c("SSURGO", "STATSGO", "SAPOLYGON"),
  byFeature = FALSE,
  idcol = "gid",
  query_string = FALSE,
  as_Spatial = getOption("soilDB.return_Spatial", default = FALSE)
)

Arguments

geom	an sf or ⁠Spatial*⁠ object, with valid CRS. May contain multiple features.
what	a character vector specifying what to return. 'mukey': data.frame with intersecting map unit keys and names, 'mupolygon', 'mupoint', 'muline' overlapping or intersecting map unit polygons, points or lines from selected database, “featpoint'or'featline'‘ for special feature points and lines, ’areasymbol'‘: 'data.frame' with intersecting soil survey areas, '’sapolygon'': overlapping or intersecting soil survey area polygons (SSURGO only)
geomIntersection	logical; FALSE (default): overlapping map unit polygons returned, TRUE: intersection of geom + map unit polygons is returned.
geomAcres	logical; TRUE (default): calculate acres of result geometry in column "area_ac" when what returns a geometry column. FALSE does not calculate acres.
db	a character vector identifying the Soil Geographic Databases ('SSURGO' or 'STATSGO') to query. Option STATSGO works with what = "mukey" and what = "mupolygon".
byFeature	Iterate over features, returning a combined data.frame where each feature is uniquely identified by value in idcol. Default FALSE.
idcol	Unique IDs used for individual features when byFeature = TRUE; Default "gid"
query_string	Default: FALSE; if TRUE return a character string containing query that would be sent to SDA via SDA_query
as_Spatial	Return sp classes? e.g. Spatial*DataFrame. Default: FALSE.

Details

Queries for map unit keys are always more efficient vs. queries for overlapping or intersecting (i.e. least efficient) features. geom is converted to GCS / WGS84 as needed. Map unit keys are always returned when using what = "mupolygon".

SSURGO (detailed soil survey, typically 1:24,000 scale) and STATSGO (generalized soil survey, 1:250,000 scale) 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.

Value

A data.frame if what = 'mukey', otherwise an sf object. A try-error in the event the request cannot be made or if there is an error in the query.

Note

Row-order is not preserved across features in geom and returned object. Use byFeature argument to iterate over features and return results that are 1:1 with the inputs. Polygon area in acres is computed server-side when what = 'mupolygon' and geomIntersection = TRUE.

Author(s)

D.E. Beaudette, A.G. Brown, D.R. Schlaepfer

See Also

SDA_query

Examples

## Not run: 
  if (requireNamespace("aqp") && requireNamespace("sf")) {

    library(aqp)
    library(sf)

    ## query at a point

    # example point
    p <- sf::st_as_sf(data.frame(x = -119.72330,
                                 y = 36.92204),
                      coords = c('x', 'y'),
                      crs = 4326)

    # query map unit records at this point
    res <- SDA_spatialQuery(p, what = 'mukey')

    # convert results into an SQL "IN" statement
    # useful when there are multiple intersecting records
    mu.is <- format_SQL_in_statement(res$mukey)

    # composite SQL WHERE clause
    sql <- sprintf("mukey IN %s", mu.is)

    # get commonly used map unit / component / chorizon records
    # as a SoilProfileCollection object
    # request that results contain `mukey` with `duplicates = TRUE`
    x <- fetchSDA(sql, duplicates = TRUE)

    # safely set texture class factor levels
    # by making a copy of this column
    # this will save in lieu of textures in the original
    # `texture` column
    horizons(x)$texture.class <- factor(x$texture, levels = SoilTextureLevels())

    # graphical depiction of the result
    plotSPC(x,
            color = 'texture.class',
            label = 'compname',
            name = 'hzname',
            cex.names = 1,
            width = 0.25,
            plot.depth.axis = FALSE,
            hz.depths = TRUE,
            name.style = 'center-center')

    ## query mukey + geometry that intersect with a bounding box

    # define a bounding box: xmin, xmax, ymin, ymax
    #
    #         +-------------------(ymax, xmax)
    #         |                        |
    #         |                        |
    #     (ymin, xmin) ----------------+
    b <- c(-119.747629, -119.67935, 36.912019, 36.944987)

    # convert bounding box to WKT
    bbox.sp <- sf::st_as_sf(wk::rct(
      xmin = b[1], xmax = b[2], ymin = b[3], ymax = b[4],
      crs = sf::st_crs(4326)
    ))

    # results contain associated map unit keys (mukey)
    # return SSURGO polygons, after intersection with provided BBOX
    ssurgo.geom <- SDA_spatialQuery(
      bbox.sp,
      what = 'mupolygon',
      db = 'SSURGO',
      geomIntersection = TRUE
    )

    # return STATSGO polygons, after intersection with provided BBOX
    statsgo.geom <- SDA_spatialQuery(
      bbox.sp,
      what = 'mupolygon',
      db = 'STATSGO',
      geomIntersection = TRUE
    )

    # inspect results
    par(mar = c(0,0,3,1))
    plot(sf::st_geometry(ssurgo.geom), border = 'royalblue')
    plot(sf::st_geometry(statsgo.geom), lwd = 2, border = 'firebrick', add = TRUE)
    plot(sf::st_geometry(bbox.sp), lwd = 3, add = TRUE)
    legend(
      x = 'topright',
      legend = c('BBOX', 'STATSGO', 'SSURGO'),
      lwd = c(3, 2, 1),
      col = c('black', 'firebrick', 'royalblue'),
    )

    # quick reminder that STATSGO map units often contain many components
    # format an SQL IN statement using the first STATSGO mukey
    mu.is <- format_SQL_in_statement(statsgo.geom$mukey[1])

    # composite SQL WHERE clause
    sql <- sprintf("mukey IN %s", mu.is)

    # get commonly used map unit / component / chorizon records
    # as a SoilProfileCollection object
    x <- fetchSDA(sql)

    # tighter figure margins
    par(mar = c(0,0,3,1))

    # organize component sketches by national map unit symbol
    # color horizons via awc
    # adjust legend title
    # add alternate label (vertical text) containing component percent
    # move horizon names into the profile sketches
    # make profiles wider
    aqp::groupedProfilePlot(x,
                            groups = 'nationalmusym',
                            label = 'compname',
                            color = 'awc_r',
                            col.label = 'Available Water Holding Capacity (cm / cm)',
                            alt.label = 'comppct_r',
                            name.style = 'center-center',
                            width = 0.3
    )

    mtext(
      'STATSGO (1:250,000) map units contain a lot of components!',
      side = 1,
      adj = 0,
      line = -1.5,
      at = 0.25,
      font = 4
    )
  }

## End(Not run)

soilDB documentation built on Sept. 11, 2024, 8:28 p.m.