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Python Geospatial Analysis Cookbook

You're reading from   Python Geospatial Analysis Cookbook Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781783555079
Length 310 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (15) Chapters Close

Preface 1. Setting Up Your Geospatial Python Environment FREE CHAPTER 2. Working with Projections 3. Moving Spatial Data from One Format to Another 4. Working with PostGIS 5. Vector Analysis 6. Overlay Analysis 7. Raster Analysis 8. Network Routing Analysis 9. Topology Checking and Data Validation 10. Visualizing Your Analysis 11. Web Analysis with GeoDjango A. Other Geospatial Python Libraries
B. Mapping Icon Libraries
Index

Converting an OpenStreetMap (OSM) XML to a Shapefile

OpenStreetMap (OSM) has a wealth of free data, but to use it with most other applications, we need to convert it to other formats, such as Shapefile or PostgreSQL PostGIS databases. This recipe will use the ogr2ogr tool to perform the conversion for us within a Python script. The benefit of this is, again, simplicity.

Getting ready

To get started, you will need to download the OSM data at http://www.openstreetmap.org/export#map=17/37.80721/-122.47305 and save the file (.osm) to your /ch03/geodata directory. The download button is located on the left-hand side bar and, when pressed, it should immediately start the download (refer to the following screenshot). The area we are testing is in San Francisco, just before the Golden Gate Bridge.

Getting ready

If you choose to download another area from OSM, feel free but make sure you take a small area similar to my example. If you select a larger area, the OSM web tool will give you a warning and disable the...

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