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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

Creating histograms


A histogram shows the statistical frequency of data distribution within a data set. In the case of remote sensing, the data set 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 3-digit tuple with (0,0,0) being black, and (255,255,255) being white. We can graph the histogram of an image with the frequency of each value along the y-axis and the range of 255 possible pixel values along the x-axis.

Remember in Chapter 1, Creating the Simplest Possible Python GIS, when we used the Turtle graphics engine included with Python to create a simple GIS? Well we can also use it to easily graph histograms. Histograms are usually a one-off product that makes a quick script, like this example, great. Also histograms are typically displayed as a bar graph with the width of the bars representing the size of grouped data bins...

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