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Python GeoSpatial Analysis Essentials

You're reading from   Python GeoSpatial Analysis Essentials Process, analyze, and display geospatial data using Python libraries and related tools

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781782174516
Length 200 pages
Edition 1st Edition
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Author (1):
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 Westra Westra
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Westra
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Summary


Congratulations! You have finished implementing a suite of programs that use a range of geospatial analysis techniques to match recorded GPS data to an existing network of roads. In the process of creating the GPS Heatmap system, you have learned how to convert existing road data into a network, how to represent a network of roads within a database, and how to use this data to implement a sophisticated map matching algorithm. This algorithm was then used to calculate a tally of how often each road segment was used by the recorded GPS data, and the tallies were then used to generate a nice-looking heatmap showing the most commonly used roads.

Even if you are not interested in capturing your own GPS data and matching it against a map, the techniques we have used in this chapter will give you many ideas for your own development efforts. Using a combination of Python, GDAL and OGR, Shapely, PyProj, PostGIS and Mapnik, you now have a fantastic arsenal of tools for processing, analyzing...

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