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Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python If you know Python and would like to use it for Geospatial Analysis this book is exactly what you've been looking for. With an organized, user-friendly approach it covers all the bases to give you the necessary skills and know-how.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781783281138
Length 364 pages
Edition 1st 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 (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python 2. Geospatial Data FREE CHAPTER 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 Modelling 9. Real-Time Data 10. Putting It All Together Index

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. 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:

Swapping image bands

Most of the vegetation appears red, and water appears almost black. This image is one type of "false color" image meaning the color of the image is not based on RGB light. However we can change the order of the bands or swap out certain bands to create another type...

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