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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 FREE CHAPTER
2. Learning about Geospatial Analysis with Python 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

Swapping image bands

Our eyes can only see colors in the visible spectrum as combinations of red, green, and blue (RGB). Air and space-borne sensors can collect wavelengths of the energy outside of the visible spectrum. To view this data, we move images representing different wavelengths of light reflectance in and out of the RGB channels to make color images.

These images often end up as bizarre and alien color combinations that can make visual analysis difficult. An example of a typical satellite image is shown in the following Landsat 7 satellite scene near the NASA Stennis Space Center in Mississippi along the Gulf of Mexico, which is a leading center for remote sensing and geospatial analysis in general:

Most of the vegetation appears red and water appears almost black. This image is a type of false-color image, meaning the color of the image is not based on the RGB light...

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