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Learning Geospatial Analysis with Python-Second Edition

You're reading from   Learning Geospatial Analysis with Python-Second Edition An effective guide to geographic information systems and remote sensing analysis using Python 3

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Product type Paperback
Published in Dec 2015
Publisher Packt
ISBN-13 9781783552429
Length 394 pages
Edition 1st Edition
Languages
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Table of Contents (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python FREE CHAPTER 2. Geospatial Data 3. The Geospatial Technology Landscape 4. Geospatial Python Toolbox 5. Python and Geographic Information Systems 6. Python and Remote Sensing 7. Python and Elevation Data 8. Advanced Geospatial Python Modeling 9. Real-Time Data 10. Putting It All Together Index

Computational geometry

Computational geometry encompasses the algorithms needed to perform operations on vector data. The field is very old in computer science; however, most of the libraries used for geospatial operations are separate from computer graphics libraries because of geospatial coordinate systems. As described near the end of Chapter 1, Learning Geospatial Analysis with Python, computer screen coordinates are almost always expressed in positive numbers, while geospatial coordinate systems often use negative numbers when they're moving west and south.

Several different geospatial libraries fit into the category but serve a wide range of uses from spatial selection to rendering. It should be noted that some features of the OGR Simple Features Library described previously move it beyond the category of data access and into the realm of computational geometry. But, it was included in the prior category because that is its primary purpose.

Computational geometry is a fascinating...

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