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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

Visualizing an indoor routing service


With our wonderful API created, it's time now to visualize this indoor route returned as GeoJSON on a map. We will now dive into the Django template components to create the HTML, JS, and CSS for our front-facing web page that displays a simple slippy web map using Openlayers 3.4.0. and Bootstrap CSS.

Our new web map will display the GeoJSON on the map with a nice style alongside a menu bar where we will include later functionality.

Getting ready

We need to build a few new folders and files to store new static and template content for our Django web application. Let's begin doing this by creating the /web_analysis/templates folder followed by the /web_analysis/static folder.

Inside our /static/ folder, we will place the nondynamic content of the JavaScript and CSS files. The /templates/ folder will store the HTML template files used to create our web pages.

Next up, let's tell Django /web_analysis/settings.py about the location of our new templates folder...

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