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Learning Geospatial Analysis with Python-Second Edition

Learning Geospatial Analysis with Python-Second Edition

By : Joel Lawhead
3.8 (4)
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Learning Geospatial Analysis with Python-Second Edition

Learning Geospatial Analysis with Python-Second Edition

3.8 (4)
By: Joel Lawhead

Overview of this book

Geospatial Analysis is used in almost every field you can think of from medicine, to defense, to farming. This book will guide you gently into this exciting and complex field. It walks you through the building blocks of geospatial analysis and how to apply them to influence decision making using the latest Python software. Learning Geospatial Analysis with Python, 2nd Edition uses the expressive and powerful Python 3 programming language to guide you through geographic information systems, remote sensing, topography, and more, while providing a framework for you to approach geospatial analysis effectively, but on your own terms. We start by giving you a little background on the field, and a survey of the techniques and technology used. We then split the field into its component specialty areas: GIS, remote sensing, elevation data, advanced modeling, and real-time data. This book will teach you everything you need to know about, Geospatial Analysis from using a particular software package or API to using generic algorithms that can be applied. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you don’t become bogged down in just getting ready to do analysis. This book will round out your technical library through handy recipes that will give you a good understanding of a field that supplements many a modern day human endeavors.
Table of Contents (12 chapters)
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11
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 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 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...

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