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Learning Geospatial Analysis with Python-Second Edition

You're reading from   Learning Geospatial Analysis with Python-Second Edition An effective guide to geographic information systems and remote sensing analysis using Python 3

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Product type Paperback
Published in Dec 2015
Publisher Packt
ISBN-13 9781783552429
Length 394 pages
Edition 1st Edition
Languages
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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 (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python FREE CHAPTER 2. Geospatial Data 3. The Geospatial Technology Landscape 4. Geospatial Python Toolbox 5. Python and Geographic Information Systems 6. Python and Remote Sensing 7. Python and Elevation Data 8. Advanced Geospatial Python Modeling 9. Real-Time Data 10. Putting It All Together Index

Swapping image bands


Our eyes can see colors only in the visible spectrum as combinations of Red, Green, and Blue (RGB). Air- and space-borne sensors can collect wavelengths of the energy outside the visible spectrum. In order 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 seen 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 that the color of the image is not based on RGB light. However, we can change the order of the bands or swap certain bands to create another type of false-color...

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