geoknife (version 1.6.11)

webgeom: create webgeom object

Description

A class representing a web available feature geometry.

Usage

webgeom(.Object, ...)
# S4 method for missing
webgeom(.Object, ...)
# S4 method for ANY
webgeom(.Object, ...)

Value

the webgeom object representing a dataset and parameters

Arguments

.Object

any object that can be coerced into webgeom

...

additional arguments passed initialize method (e.g., url). See the named slots above for arguments for ...

Slots

url

value of type "character", the web location for the web feature service

geom

value of type "character", the feature for webgeom

attribute

the attribute (e.g., "State")

values

the values of the attribute, (e.g., "Wisconsin") or NA (all)

Author

Jordan S Read

Details

slots can be accessed or set with methods of the same names (e.g., url(webgeom()))

See Also

url, geom, attribute, values

Examples

wg <- webgeom(geom = "sample:CONUS_states", 
 attribute = "STATE",
 values = "New Hampshire")
#-- use available state datasets:
wg <- webgeom('state::New Hampshire')
wg <- webgeom('state::New Hampshire,Wisconsin,Alabama')
#-- use available Level III Ecoregion datasets:
wg <- webgeom('ecoregion::Colorado Plateaus,Driftless Area')
#-- use available simplified HUC8s:
wg <- webgeom('HUC8::09020306,14060009')
wg <- webgeom()

if (FALSE) {
## Steps to find data on Howard County in Texas:
#1) locate the \code{geom} for counties by looking at the options for geoms
query(webgeom(), 'geoms') # discover sample:Counties
#2) locate the \code{attribute} for county names by looking at the options for attributes
query(webgeom(geom='sample:Counties'), 'attributes') # discover FIPS
#3) find the appropriate fip code for the county:
howard.fips <- "48227"
#4) create a webgeom for the Howard County in Texas
stencil <- webgeom(geom='sample:Counties', attribute='FIPS', values=howard.fips)
#5) get data for Howard County
fabric <- webdata(url = 'https://cida.usgs.gov/thredds/dodsC/stageiv_combined', 
variables = "Total_precipitation_surface_1_Hour_Accumulation", 
times = c(as.POSIXct("2016-06-06 05:00:00"), 
          as.POSIXct("2016-06-07 05:00:00")))
job <- geoknife(stencil, fabric, wait = TRUE)
precipData <- result(job)
head(precipData)
}