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Learning Geospatial Analysis with Python - Second Edition by Joel Lawhead

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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 points 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 be to 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 ...

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