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Python Coding of Geospatial Processing in Web-based Mapping Applications

James A. Kuiper
Argonne National Laboratory

Andrew J. Ayers
Argonne National Laboratory

Michael E. Holm
Argonne National Laboratory

Michael J. Nowak
Argonne National Laboratory

Abstract

Python has powerful capabilities for coding elements of Web-based mapping applications. This paper highlights examples of analytical geospatial processing services that we have implemented for several Open Source-based development projects, including the Eastern Interconnection States' Planning Council (EISPC) Energy Zones Mapping Tool (http://eispctools.anl.gov), the Solar Energy Environmental Mapper (http://solarmapper.anl.gov), and the Ecological Risk Calculator (http://bogi.evs.anl.gov/erc/portal). We used common Open Source tools such as GeoServer, PostGIS, GeoExt, and OpenLayers for the basic Web-based portal, then added custom analytical tools to support more advanced functionality. The analytical processes were implemented as Web Processing Services (WPSs) running on PyWPS, a Python implementation of the Open Geospatial Consortium (OGC) WPS. For report tools, areas drawn by the user in the map interface are submitted to a service that utilizes the spatial extensions of PostGIS to generate buffers for use in querying and analyzing the underlying data. Python code then post-processes the results and outputs JavaScript Object Notation (JSON)-formatted data for rendering. We made use of PyWPS's integration with the Geographic Resources Analysis Support System (GRASS) to implement flexible, user-adjustable suitability models for several renewable energy generation technologies. In this paper, we provide details about the processing methods we used within these project examples.

Keywords

GIS, web-based mapping, PyWPS, PostGIS, GRASS, spatial modeling

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