Geoprocessing mit Python: Unterschied zwischen den Versionen

Version vom 2. April 2014, 23:12 Uhr

Books:

Buch "Python Geo Spatial Development", by Erik Westra, Packt Publishing (Dec 2010), [Paperback], 508 pages. ISBN-10: 1849511543, ISBN-13: 978-1849511544. [1]
Geoprocessing mit Python und PostGIS.
Geoprocessing mit Python und Open Source GIS: Siehe z.B. Vorlesung "Geoprocessing with Python using Open Source GIS" by Chris Garrard, Utah State University, [2].

Web Processing Services (WPS):

PyWPS Web Processing Service ([3]): PyWPS is a Python program which implements the OGC WPS 1.0.0 standard (with a few omissions). PyWPS has a low footprint, making it easy to install. Python was considered a good choice of implementation language as it is a very easy language to develop in and allows partners to easily integrate existing processing which may have been written in other languages.
WebProcessingServer ([4])

@@ Zeile 1: / Zeile 1: @@
-#redirect[[Python#Geoprocessing_mit_Python]]
+See also [[Python]].
+== Ressourcen ==
+Books:
+* Buch "Python Geo Spatial Development", by Erik Westra, Packt Publishing (Dec 2010), [Paperback], 508 pages. ISBN-10: 1849511543, ISBN-13: 978-1849511544. [http://www.amazon.com/dp/1849511543/ref=rdr_ext_sb_ti_sims_2]
+* Geoprocessing mit Python und PostGIS.
+* Geoprocessing mit Python und Open Source GIS: Siehe z.B. Vorlesung "Geoprocessing with Python using Open Source GIS" by Chris Garrard, Utah State University, [http://www.gis.usu.edu/~chrisg/python/].
+Web Processing Services ([[WPS]]):
+* PyWPS Web Processing Service ([http://pywps.wald.intevation.org/documentation/]): PyWPS is a Python program which implements the OGC [[WPS]] 1.0.0 standard (with a few omissions). PyWPS has a low footprint, making it easy to install. Python was considered a good choice of implementation language as it is a very easy language to develop in and allows partners to easily integrate existing processing which may have been written in other languages.
+* WebProcessingServer ([http://code.google.com/p/webprocessingserver/])
+== Vektor-Daten ==
+* [[OGR]]
+* Rasterio (mit NumPy): http://sgillies.net/blog/2014/02/10/rasterio-0-6.html
+=== OGR mit Python programmieren ===
+* Fiona Library [https://github.com/Toblerity/Fiona] [https://pypi.python.org/pypi/Fiona]
+* tbd.
+== Raster-Daten ==
+* [[GDAL]]
+===  GDAL mit Python programmieren ===
+* tbd.