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 Learning Geospatial Analysis with Python

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

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837639175
Length 432 pages
Edition 4th 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 (18) Chapters Close

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 17. Other Books You May Enjoy

Creating images for visualization

Now, we’re moving from calculations and data editing to something we can see! We’ll begin by creating different types of maps. In Chapter 1, Learning about Geospatial Analysis with Python, we visualized our SimpleGIS program using the Tkinter module that’s included with Python. In Chapter 4, Geospatial Python Toolbox, we examined a few other methods for creating images. Now, we’ll examine these tools in more depth by creating two specific types of thematic maps. The first is a dot density map and the second is a choropleth map.

First, let’s start with the dot density map.

Dot density calculations

A dot density map shows concentrations of subjects within a given area. If an area is divided up into polygons containing statistical information, you can model that information using randomly distributed dots within that area using a fixed ratio across the dataset. This type of map is commonly used for population...

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