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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

Introduction

This chapter will get the grunt work done for you so that you can freely and actively complete all the recipes in this book. We will start off by installing, each of the libraries you will be using, one by one. Once each step is completed, we will test each library installation to make sure it works. Since this book is directed toward those of you already working with spatial data, you can skip this chapter if you have it installed already. If not, you will find the installation instructions here useful as a reference.

The choice of Python libraries is based on industry-proven reliability and functionality. The plethora of functions in Python libraries has led to a flourishing GIS support on many top desktop GIS systems, such as QGIS and ESRI ArcGIS.

Also included in this book is an installer.sh bash file. The installer.sh file can be used to install the Python libraries that are available for your virtual environment from pip and other dependencies via the apt-get command. The installer.sh bash file is executed from the command line and installs almost everything in one go, so please take a look at it. For those of you who are starting with Python for the first time, follow the instructions in this chapter and your machine will be set up to complete different recipes.

Installations can sometimes be tricky even for advanced users, so you will find some of the most common pitfalls and hook-ups described in this chapter.

The development of these recipes was completed on a fresh Linux/Ubuntu 14.04 machine. Therefore, the code examples, if not otherwise specified, are Linux/Ubuntu-specific with Windows notes wherever necessary, unless otherwise specified.

You have been reading a chapter from
Python Geospatial Analysis Cookbook
Published in: Nov 2015
Publisher:
ISBN-13: 9781783555079
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