In HanOostdijk/HOQCwfs: Web Feature Service (WFS) read-only interface

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HOQCwfs

R Web Feature Service (WFS) read-only interface

This package contains functions to retrieve spatial information from a Web Feature Service (WFS) resource. A WFS server supports a number of geospatial output formats, but the package HOQCwfs returns by default the simple features format.
The conversion of the json server data to the sf format is done by the package sf. For more information about the sf package see Simple Features for R.

The sf format has the advantage that non-spatial attributes of the features are contained in a standard data.frame. This data.frame is extended with a column that contains the geometry of the features. Non-spatial manipulation of the data.frame can be done in the normal way by using the dplyr package. For spatial manipulation the functions of the sf package can be used. However spatial filtering can also be done by the WFS server when the user specifies a spatial query.

The HOQCwfs package contains functions :

to create queries to run on the WFS server for use in WFS_getfeature
to find out the capabilities a WFS server (WFS_getcapabities)
to find out which featuretypes a WFS server contains (WFS_featuretypes)
to find out which fields a featuretype contains (WFS_describefeaturetype)

The examples in this package center around featuretype topp:gidw_groenbomen from WFS server https://geoweb.amstelveen.nl/geoserver/topp/wfs. In that case the features are trees with the Point geometry.

Installation

You can install this version from GitHub with:

# install.packages("devtools")
devtools::install_github("HanOostdijk/HOQCwfs",build_vignettes=TRUE)

How to use HOQCwfs

In this README one example is given. See the vignette for more examples.

In this example the trees are retrieved in a rectangular area that has a hole in its interior. After defining the area and the filter (query) the actual WFS_getfeature request is done. The last part of the example displays the area and the selected trees with a Open Street Map background with the aid of the packages tmap and leaflet.

library(HOQCwfs)
# define outer en inner rectangle in WGS 84 coordinates
out_wgs84 <- c( 4.86,  52.31,  4.86, 52.316, 4.88,  52.316, 
                 4.88,  52.31,  4.86, 52.31)
in_wgs84  <- c( 4.87,  52.312, 4.87, 52.314, 4.875, 52.314, 
                 4.875, 52.312, 4.87, 52.312)
# convert coordinates form WGS84 (EPSG:4326) to the Dutch CRS EPSG:28992
out_28992 <- convert_points(out_wgs84,"EPSG:4326","EPSG:28992")
in_28992  <- convert_points(in_wgs84,"EPSG:4326","EPSG:28992")

# define the filter that selects all points that intersect the rectangle with hole
# use EPSG:28992 because that is the default CRS for this WFS server (data set)
xml_query <- build_filter(version='1.1.0',
     spat_xml('geometrie',
              spat_feature('Polygon','EPSG:28992',list(out_28992,in_28992)),
              spat_fun='Intersects')
  )
# set WFS server (not necessary here because this is the default)
WFS_set_url("https://geoweb.amstelveen.nl/geoserver/topp/wfs")
# set typename (dataset) and attributes that will be retrieved
typename  <- 'topp:gidw_groenbomen'
fields    <- 'boom_omschrijf,objec_omschrijf'
# retrieve the data from the WFS server using the filter
wfs1      <-  WFS_getfeature(typename
             ,filter=xml_query
             ,propertyname=fields)
# show number of trees and attributes
dim(wfs1)
# show only the first two features
head(wfs1,2)

# load libraries needed for visualization
library(tmap)
library(leaflet)
# set tmap options
opts         <- tmap_options(basemaps = c(Canvas = "OpenStreetMap"))
current.mode <- tmap_mode("view")
# define the rectangle with hole as a simple features object 
my_poly      <- sf::st_sfc(sf::st_polygon(list(out_28992,in_28992)),
                           crs='EPSG:28992')
# id and title useful in interactive mode
id    <- "boom_omschrijf"
title <- "boom"
# create map with rectangle and dots
`%>%` <-  magrittr::`%>%`
map1  <-
  tm_shape(my_poly) + # rectangle
    tm_polygons(alpha = 0.2, col = "red") +
  tm_shape(wfs1) +    # trees
    tm_dots(size = 0.05,
            id = id,
            title = title)
# add Open Street Map background
map2  <- tmap_leaflet(map1) %>% 
  addTiles(attribution = "(c) Gemeente Amstelveen")
# save map in png format to include in README
mapview::mapshot(map2, file = "./images/trees_in-rectangle_with_hole.png")