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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

Advanced Geospatial Python Modeling

In this chapter, we'll build on the data processing concepts that we've learned in order to create some full-scale information products. The previously introduced data processing methods rarely provide answers to questions by themselves. You combine these data processing methods to build a geospatial model from multiple processed datasets. A geospatial model is a simplified representation of some aspect of the real world, which helps us answer one or more questions about a project or problem. In this chapter, we will introduce some important geospatial algorithms that are commonly used in agriculture, emergency management, logistics, and other industries.

The products that we will create are as follows:

  • A crop health map
  • A flood inundation model
  • A colorized hillshade
  • A terrain routing map
  • A street routing map
  • A shapefile with links...
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