20 Working with Web Feature Services#

In computing, the Open Geospatial Consortium Web Feature Service (WFS) Interface Standard provides an interface allowing requests for geographical features across the web using platform-independent calls. One can think of geographical features as the “source code” behind a map, whereas the WMS interface or online tiled mapping portals like Google Maps return only an image, which end-users cannot edit or spatially analyze. The XML-based GML furnishes the default payload-encoding for transporting geographic features, but other formats like shapefiles can also serve for transport.

Source: https://en.wikipedia.org/wiki/Web_Feature_Service

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Set File Paths and download Tutorial Data#

If you downloaded the latest GemGIS version from the Github repository, append the path so that the package can be imported successfully. Otherwise, it is recommended to install GemGIS via pip install gemgis and import GemGIS using import gemgis as gg. In addition, the file path to the folder where the data is being stored is set. The tutorial data is downloaded using Pooch (https://www.fatiando.org/pooch/latest/index.html) and stored in the specified folder. Use pip install pooch if Pooch is not installed on your system yet.

[1]:
import gemgis as gg

file_path ='data/20_working_with_web_feature_services/'
WARNING (theano.configdefaults): g++ not available, if using conda: `conda install m2w64-toolchain`
C:\Users\ale93371\Anaconda3\envs\test_gempy\lib\site-packages\theano\configdefaults.py:560: UserWarning: DeprecationWarning: there is no c++ compiler.This is deprecated and with Theano 0.11 a c++ compiler will be mandatory
  warnings.warn("DeprecationWarning: there is no c++ compiler."
WARNING (theano.configdefaults): g++ not detected ! Theano will be unable to execute optimized C-implementations (for both CPU and GPU) and will default to Python implementations. Performance will be severely degraded. To remove this warning, set Theano flags cxx to an empty string.
WARNING (theano.tensor.blas): Using NumPy C-API based implementation for BLAS functions.

Loading the WFS Service#

For this example, we are downloading a WFS Service provided by the Landesamt für Bergbau, Energie und Geologie - Niedersachsen. It contains Polygon, Line and Point data about seismic surveys and wells in Northern Germany.

[3]:
wfs = gg.web.load_wfs("https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=476&Service=WFS&")
wfs
[3]:
<owslib.feature.wfs100.WebFeatureService_1_0_0 at 0x19260e21340>
[3]:
type(wfs)
[3]:
owslib.feature.wfs100.WebFeatureService_1_0_0

Checking the version of the WFS#

[4]:
wfs.version
[4]:
'1.0.0'

Checking the version of the WFS#

[5]:
wfs.identification.version
[5]:
'1.0.0'

Checking the identification type of the WFS#

[6]:
wfs.identification.type
[6]:
'Geophysik und Tiefohrungen'

Checking the title of the WFS#

[7]:
wfs.identification.title
[7]:
'Geophysik und Tiefohrungen'

Checking the abstract of the WFS#

[8]:
wfs.identification.abstract
[8]:
'Geophysik und Tiefohrungen'

Checking the contents of the WFS#

[9]:
list(wfs.contents)
[9]:
['iwan:L383']

Checking the title of the WFS layer#

[10]:
wfs['iwan:L383'].title
[10]:
'Gravimetrie'

Checking the bounding box of the WFS layer#

[11]:
wfs['iwan:L383'].boundingBoxWGS84
[11]:
(5.395175801132899, 47.16510247399335, 17.002272548448747, 54.85398076006902)

Checking the operations for the WFS#

[12]:
[op.name for op in wfs.operations]
[12]:
['GetCapabilities', 'DescribeFeatureType', 'GetFeature']

Checking the format for getting the feature#

[13]:
wfs.getOperationByName('GetFeature').formatOptions
[13]:
['{http://www.opengis.net/wfs}GML2']

Checking the format for describing the feature#

[14]:
wfs.getOperationByName('DescribeFeatureType').formatOptions
[14]:
[]

Checking the format for getting the capabilities#

[15]:
wfs.getOperationByName('GetCapabilities').formatOptions
[15]:
[]

Requesting data from the WFS#

The features can be loaded with the function load_as_gpd(..).

[16]:
feature = gg.web.load_as_gpd("https://nibis.lbeg.de/net3/public/ogc.ashx?NodeId=476&Service=WFS&")

Checking the head of the data#

[17]:
feature.head()
[17]:
gml_id OBJECTID ID SURVEYNAME ARCHIV MESSJAHR OPERATOR OP_NACHFOL MESSFIRMA MESSPUNKTE UP_DATE geometry
0 1541 1541 112 Jemgum 2007 0127494 2007 GdF Produktion Exploration Deutschland GmbH Neptune Energy Deutschland GmbH Geophysik und Geotechnik Leipzig GmbH 1340 2020-01-20T00:00:00+01:00 MULTIPOLYGON (((32395246.839 5907777.660, 3239...
1 1542 1542 111 Sagermeer 2005 0125831 2005 ExxonMobil Production Deutschland GmbH ExxonMobil Production Deutschland GmbH Comp. Generale Geophysique 2803 2020-01-20T00:00:00+01:00 MULTIPOLYGON (((32446717.522 5856710.088, 3244...
2 1543 1543 120 Hümmling 2013 0131520 2013 GDF SUEZ E&P DEUTSCHLAND GMBH Neptune Energy Deutschland GmbH Deutsche Montan Technologie GmbH 342 2020-01-20T00:00:00+01:00 MULTIPOLYGON (((32416592.825 5852885.544, 3241...
3 1544 1544 49 Rotenburg/Wümme (1984) 0112162 1984 Deutsche Texaco AG Aufschluss und Gew. Wintershall Dea Deutschland AG Prakla Seismos 2184 2020-01-20T00:00:00+01:00 POLYGON ((32545955.921 5896473.525, 32544536.2...
4 1545 1545 102 Odisheim 1989/90 0112092 1989 BEB Erdgas und Erdöl GmbH BEB Erdgas und Erdöl GmbH & Co. KG Prakla Seismos 2824 2020-01-20T00:00:00+01:00 POLYGON ((32504255.640 5967591.298, 32503387.8...

Plotting the data#

[18]:
import matplotlib.pyplot as plt

feature.plot()
plt.grid()
../../_images/getting_started_tutorial_20_working_with_web_feature_services_35_0.png