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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

PIL


The PIL was originally developed for remote sensing, but has evolved as a general image editing library for Python. Like NumPy, it is written in C for speed, but is designed specifically for Python. In addition to image creation and processing, it also has a useful raster drawing module. PIL is also available via PyPI; however, in Python 3, you may want to use the Pillow module which is an upgraded version of PIL. As you'll see in the example below, we use a Python try statement to import PIL using two possible variations depending on how you installed it.

In this example, we'll combine PyShp and PIL to rasterize the hancock shapefile from previous examples and save it as an image. We'll use a world to pixel coordinate transformation similar to our SimpleGIS from Chapter 1, Learning Geospatial Analysis with Python. We'll create an image to use as a canvas in PIL, and then we'll use the PIL ImageDraw module to render the polygon. Finally, we'll save it as a PNG image, as you can see in...

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