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Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python Understand GIS fundamentals and perform remote sensing data analysis using Python 3.7

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Product type Paperback
Published in Sep 2019
Publisher
ISBN-13 9781789959277
Length 456 pages
Edition 3rd 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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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: The History and the Present of the Industry FREE CHAPTER
2. Learning about Geospatial Analysis with Python 3. Learning Geospatial Data 4. The Geospatial Technology Landscape 5. Section 2: Geospatial Analysis Concepts
6. Geospatial Python Toolbox 7. Python and Geographic Information Systems 8. Python and Remote Sensing 9. Python and Elevation Data 10. Section 3: Practical Geospatial Processing Techniques
11. Advanced Geospatial Python Modeling 12. Real-Time Data 13. Putting It All Together 14. Other Books You May Enjoy

OGR

We touched on OGR as a way to handle WKT strings, but its real power is as a universal vector library. This book strives for pure Python solutions, but no single library even comes close to the variety of formats that OGR can process.

Let's read a sample point shapefile using the OGR Python API. The sample shapefile can be downloaded as a ZIP file here: https://github.com/GeospatialPython/Learn/raw/master/point.zip.

This point shapefile has five points with single digit, positive coordinates. The attributes list the order in which the points were created, making it useful for testing. This simple example will read in the point shapefile and loop through each feature; then, it will print the x and y values of each point, plus the value of the first attribute field:

>>> import ogr
>>> shp = ogr.Open("point.shp")
>>> layer = shp.GetLayer...
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