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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

Least cost path analysis


Calculating driving directions is the most commonly used geospatial function in the world. Typically these algorithms calculate the shortest path between point A and B or they may take into account the speed limit of the road or even current traffic conditions to choose a route by drive time.

But what if your job is to build a new road? Or what if you are in charge of deciding where to run power transmission lines or water lines across a remote area? In a terrain-based setting, the shortest path might cross a difficult mountain or run through a lake. In this case we need to account for obstacles and avoid them if possible. However, if avoiding a minor obstacle takes us too far out of our way, the cost of implementing that route may be more expensive than just going over a mountain.

This type of advanced analysis is called Least Cost Path analysis. We search an area for the route that is the best compromise of distance versus the cost of following the route. The algorithm...

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