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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

Creating histograms


A histogram shows the statistical frequency of the data distribution in a dataset. In the case of remote sensing, the dataset is an image; the data distribution is the frequency of pixels in the range of 0 to 255, which is the range of 8-byte numbers used to store image information on computers. In an RGB image, color is represented as a three-digit tuple with (0,0,0, 0, 0) as black and (255,255,255) as white. We can graph the histogram of an image with the frequency of each value along the y axis and the range of 256 possible pixel values along the x axis.

In Creating the simplest possible Python GIS section of Chapter 1, Learning Geospatial Analysis with Python, we used the turtle graphics engine included with Python to create a simple GIS. Well, we can use it to easily graph histograms as well. Histograms are usually a one-off product that makes a quick script great. Additionally, histograms are typically displayed as a bar graph with the width of the bars representing...

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