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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

Building an indoor routing system in 3D


How to route through one or multiple buildings or floors is what this recipe is all about. This is, of course, the most complex situation involving complex data collection, preparation, and implementation processes. We cannot go into all the complex data details of collection and transformation from ACAD to PostGIS, for example; instead, the finished data is provided.

To create an indoor routing application, you need an already digitized routing network set of lines representing the areas where people can walk. Our data represents the first and second floor of a university building. The resulting indoor route, shown in the following screenshot, starts from the second floor and travels down the stairs to the first floor, all the way through the building, heading up the stairs again to the second floor, and finally reaching our destination.

Getting ready

For this recipe, we will need to complete quite a few tasks to prepare for the indoor 3D routing. Here...

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