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Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python Understand GIS fundamentals and perform remote sensing data analysis using Python 3.7

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Product type Paperback
Published in Sep 2019
Publisher
ISBN-13 9781789959277
Length 456 pages
Edition 3rd Edition
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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 (15) Chapters Close

Preface 1. Section 1: The History and the Present of the Industry
2. Learning about Geospatial Analysis with Python FREE CHAPTER 3. Learning Geospatial Data 4. The Geospatial Technology Landscape 5. Section 2: Geospatial Analysis Concepts
6. Geospatial Python Toolbox 7. Python and Geographic Information Systems 8. Python and Remote Sensing 9. Python and Elevation Data 10. Section 3: Practical Geospatial Processing Techniques
11. Advanced Geospatial Python Modeling 12. Real-Time Data 13. Putting It All Together 14. Other Books You May Enjoy

Understanding computational geometry

Computational geometry encompasses the algorithms that are 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 about 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 this category, but they also serve a wide range of uses, from spatial selection to rendering. It should be noted that some features of GDAL that were described previously move it beyond the category of data access, and into the realm of computational...

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