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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 a Shapefile to a PostGIS table using ogr2ogr


The simplest way to transform data from one format to another is to directly use the ogr2ogr tool that comes with the installation of GDAL. This powerful tool can convert over 200 geospatial formats. In this solution, we will execute the ogr2ogr utility from within a Python script to perform generic vector data conversions. The Python code is, therefore, used to execute this command-line tool and pass around variables so that you can create your own scripts for data imports or exports.

Using this tool is also recommended if you are not really interested in coding too much and simply want to get the job done to move your data. A pure Python solution is, of course, possible, but it's definitely more orientated to the needs of developers (or a Python purist). Since this book is aimed at developers, analysts, or researchers, this kind of a recipe is simple and yet extensible.

Getting ready

To run this script, you will need the GDAL utilities...

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