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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

Working with projections, in my opinion, is not too exciting but they're very important, and your ability to deal with them in any application is crucial.

The goal of this chapter is to provide some common predata screening or transformation steps to get your data in shape or, better yet, in position for geospatial analysis. We cannot always perform analysis on multiple datasets that are in different coordinate systems without the risk of achieving inconsistent results, such as data positional inaccuracies. Therefore, it is a best practice to work on data in the same coordinate system, such as EPSG:4326, when working on a global scale, or use a local coordinate system for your region that will provide you the most accurate results.

European Petroleum Survey Group or EPSG codes have decided to give all coordinate systems a number code to simplify finding and sharing projection information. Coordinate systems are described by their definitions, which are stored in text files...

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