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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

Extracting image footprints using ChatGPT

Raster images, which are essentially grid-based digital images, provide a wealth of detailed data. However, their format can sometimes limit our ability to interact with and analyze the data they contain. This is where vector footprints come into play. By creating vector footprints of raster images, we essentially create an outline or footprint of the image in a vector format as polygons.

This process allows us to interact with raster data in new and more flexible ways. For instance, vector footprints can be used to quickly identify the geographic extent of raster data, which is particularly useful when dealing with large datasets. They can also be used to index raster data, making it easier to manage and query. Furthermore, vector footprints can be overlaid on other geospatial data layers, enabling more complex spatial analyses.

For our final technique in this chapter, we’ll create a footprint for the swap.tif image that we used...

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