In ropenscilabs/spplit: Combine Species Occurrence Data and Literature

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Geospatial Queries

spplit allows you query species occurrence data sources in a variety of ways. One of them is via a geospatial definition. This geospatial definition can be a variety of different things:

• Bounding box
• WKT - Well Known Text
• SpatialPolygons/SpatialPolygonsDataFrame

While GBIF allows only WKT submitted to their API, the user here can pass in all the things above, and we internally convert to WKT.

While iDigBio allows only a bounding box submitted to their API, the user here can pass in all the things above, and we internally convert to a bounding box.

Thus, as you can pass a detailed and complex WKT geospatial definition to GBIF and it will get passed directlty to GBIF, that same complex WKT when passed to iDigBio will first be simplified to a bounding box.

Bounding boxes

A bounding box is a simple numeric vector of length 4, with the following format:

[min-longitude, min-latitude, max-longitude, max-latitude]

An example in R:

c(-120, 40, -100, 45)

where -120 is the min longitude, 40 is the min latitude, -100 is the max longitude and 45 is the max latitude.

You can pass a bounding box to the geometry parameter in sp_occ_gbif(), or sp_occ_idigbio().

WKT

WKT is a text string, and is defined by a set of spatial classes. Check out the Wikipedia entry on WKT for more info (https://en.wikipedia.org/wiki/Well-known_text).

The only type of WKT class you can use here is POLYGON. Other classes are defined in WKT, but GBIF doesn't support any other class.

A simple example of a WKT string of a POLYGON class is:

POLYGON ((30 10, 40 40, 20 40, 10 20, 30 10))

You can pass a WKT string for a POLYGON to the geometry parameter in sp_occ_gbif(), or sp_occ_idigbio().

An easy to use website for getting WKT after drawing a shape on a map is http://arthur-e.github.io/Wicket/sandbox-gmaps3.html.

You can get WKT from within R using the wellknown package https://cran.r-project.org/package=wellknown. With wellknown you can get WKT from R objects, and convert GeoJSON to WKT as well. For example:

df <- us_cities[2:5,c('long','lat')]
df <- rbind(df, df[1,])
polygon(df, fmt=2)
#> [1] "POLYGON ((-81.52 41.08, -122.26 37.77, -84.18 31.58, -73.80 42.67, -81.52 41.08))"

SpatialPolygons/SpatialPolygonsDataFrame

SpatialPolygons and SpatialPolygonsDataFrame are two classes of object defined in the package sp (https://cran.r-project.org/package=sp). There are other object types defined in sp, but only these two are supported here. We take those inputs internally and convert to a WKT for GBIF or a bounding box for iDigBio.

You can create a SpatialPolygons object like:

library("sp")
poly <- SpatialPolygons(list(Polygons(list(Polygon(cbind(
  c(-124.07, -119.99, -119.99, -124.07, -124.07),
  c(41.48, 41.48, 35.57, 35.57, 41.48)
))), "s1")), 1L)
class(poly)

Then use the SpatialPolygons class object for a geometry based search:

library("spplit")
sp_occ_gbif(geometry = poly, limit = 10)

Same goes for SpatialPolygonsDataFrame

ropenscilabs/spplit documentation built on Sept. 29, 2020, 3:05 a.m.