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Python Geospatial Analysis Cookbook

Python Geospatial Analysis Cookbook

By : Diener
4.4 (5)
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Python Geospatial Analysis Cookbook

Python Geospatial Analysis Cookbook

4.4 (5)
By: Diener

Overview of this book

Geospatial development links your data to places on the Earth’s surface. Its analysis is used in almost every industry to answer location type questions. Combined with the power of the Python programming language, which is becoming the de facto spatial scripting choice for developers and analysts worldwide, this technology will help you to solve real-world spatial problems. This book begins by tackling the installation of the necessary software dependencies and libraries needed to perform spatial analysis with Python. From there, the next logical step is to prepare our data for analysis; we will do this by building up our tool box to deal with data preparation, transformations, and projections. Now that our data is ready for analysis, we will tackle the most common analysis methods for vector and raster data. To check or validate our results, we will explore how to use topology checks to ensure top-quality results. This is followed with network routing analysis focused on constructing indoor routes within buildings, over different levels. Finally, we put several recipes together in a GeoDjango web application that demonstrates a working indoor routing spatial analysis application. The round trip will provide you all the pieces you need to accomplish your own spatial analysis application to suit your requirements.
Table of Contents (15 chapters)
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12
A. Other Geospatial Python Libraries
13
B. Mapping Icon Libraries
14
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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