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Python Geospatial Analysis Cookbook

Python Geospatial Analysis Cookbook

By : Diener
4.4 (5)
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Python Geospatial Analysis Cookbook

Python Geospatial Analysis Cookbook

4.4 (5)
By: Diener

Overview of this book

Geospatial development links your data to places on the Earth’s surface. Its analysis is used in almost every industry to answer location type questions. Combined with the power of the Python programming language, which is becoming the de facto spatial scripting choice for developers and analysts worldwide, this technology will help you to solve real-world spatial problems. This book begins by tackling the installation of the necessary software dependencies and libraries needed to perform spatial analysis with Python. From there, the next logical step is to prepare our data for analysis; we will do this by building up our tool box to deal with data preparation, transformations, and projections. Now that our data is ready for analysis, we will tackle the most common analysis methods for vector and raster data. To check or validate our results, we will explore how to use topology checks to ensure top-quality results. This is followed with network routing analysis focused on constructing indoor routes within buildings, over different levels. Finally, we put several recipes together in a GeoDjango web application that demonstrates a working indoor routing spatial analysis application. The round trip will provide you all the pieces you need to accomplish your own spatial analysis application to suit your requirements.
Table of Contents (15 chapters)
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12
A. Other Geospatial Python Libraries
13
B. Mapping Icon Libraries
14
Index

Introduction


Routing has become commonplace on navigation devices for road networks across the world. If you want to know how to drive from point A to point B, simply enter the start address and end address into your navigation software and it will calculate the shortest route for you in seconds.

Here's a scenario you may come across: Route me to Prof. Dr. Smith's office in the Geography Department for my meeting at any university anywhere. Hmm, sorry, there's no routing network available on my navigation software. This is a reminder for you to not to forget to ask for directions on campus for your meeting location.

This chapter is all about routing and, specifically, routing inside large building complexes from office A33, first floor in building E01 to office B55, sixth floor in building P7.

We will explore the powerful routing capabilities of pgRouting, an extension of PostgreSQL. With pgRouting, we can calculate the shortest path using either the Dijkstra, A*, and/or K shortest path algorithms...

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