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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

Creating an indoor web routing service


Let's take all the effort we put into Chapter 8, Network Routing Analysis, out onto the World Wide Web. Our routing service will simply accept a starting point location, an x, y coordinate pair, a floor level, and a destination location. The indoor routing service will then calculate the shortest path and return a complete route in the form of a GeoJSON file.

Getting ready

To layout the tasks ahead, let's list out what we need to accomplish at a high level so that we're clear about where we are going:

  1. Create a URL pattern to call a route service.

  2. Build a view to handle an incoming URL request and deliver the appropriate GeoJSON route web response:

    1. Accept incoming request parameters.

      Start x coordinate.

      Start y coordinate.

      Start floor number.

      End x coordinate.

      End y coordinate.

      End floor number.

    2. Return GeoJSON LineString.

      Route geometry.

      Route length.

      Route walk time.

    We also need to let our new database user named saturn in order to have access to the tables located...

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Python Geospatial Analysis Cookbook
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