You're reading from Learning Geospatial Analysis with Python Unleash the power of Python 3 with practical techniques for learning GIS and remote sensing

Product type Paperback

Published in Nov 2023

Publisher Packt

ISBN-13 9781837639175

Length 432 pages

Edition 4th Edition

Languages

Python

Tools

ChatGPT

Concepts

Geospatial Analysis

Author (1):

Joel Lawhead

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Table of Contents (18) Chapters

Preface

1. Part 1:The History and the Present of the Industry

2. Chapter 1: Learning about Geospatial Analysis with Python FREE CHAPTER

3. Chapter 2: Learning about Geospatial Data

4. Chapter 3: The Geospatial Technology Landscape

5. Part 2:Geospatial Analysis Concepts

6. Chapter 4: Geospatial Python Toolbox

7. Chapter 5: Python and Geospatial Algorithms

8. Chapter 6: Creating and Editing GIS Data

9. Chapter 7: Python and Remote Sensing

10. Chapter 8: Python and Elevation Data

11. Part 3:Practical Geospatial Processing Techniques

12. Chapter 9: Advanced Geospatial Modeling

13. Chapter 10: Working with Real-Time Data

14. Chapter 11: Putting It All Together

15. Assessments

16. Index

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Understanding desktop tools (including visualization)

Geospatial analysis requires the ability to visualize output. This fact makes tools that can visualize data absolutely critical to the field. There are two categories of geospatial visualization tools.

The first is geospatial viewers and the second is geospatial analysis software. The first category – geospatial viewers—allows you to access, query, and visualize data, but not to edit it in any way. The second category allows you to perform those tasks, and edit the data, too. The main advantage of viewers is that they are typically lightweight pieces of software that launch and load data quickly.

Geospatial analysis software requires far more resources to be able to edit complex geospatial data, so it loads more slowly and often renders data more slowly, in order to provide dynamic editing functionality.