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Python Geospatial Analysis Cookbook

You're reading from   Python Geospatial Analysis Cookbook Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781783555079
Length 310 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (15) Chapters Close

Preface 1. Setting Up Your Geospatial Python Environment FREE CHAPTER 2. Working with Projections 3. Moving Spatial Data from One Format to Another 4. Working with PostGIS 5. Vector Analysis 6. Overlay Analysis 7. Raster Analysis 8. Network Routing Analysis 9. Topology Checking and Data Validation 10. Visualizing Your Analysis 11. Web Analysis with GeoDjango A. Other Geospatial Python Libraries
B. Mapping Icon Libraries
Index

Visualizing DEM data with Three.js

You have a great 3D Digital Elevation Model (DEM) that you may want to view on a web page, so your choices are limited only to your imagination and programming skills. In this little example based on the great work of Bjorn Sandvik, we will explore the methods needed to manipulate a DEM to load a Three.js HTML-based web page.

Tip

A great plugin that I would highly recommend for QGIS is the qgis2threejs plugin, written by Minoru Akagi. The Python plugin code is available on GitHub at https://github.com/minorua/Qgis2threejs where you can find a nice gdal2threejs.py converter.

The resulting 3D DEM mesh can be viewed in your browser:

Visualizing DEM data with Three.js

Getting ready

We need Jinja2 as our template engine (installed in the first section of this chapter) to create our HTML. The remaining requirements include JavaScript and our 3D DEM data. Our DEM data is from Chapter 7, Raster Analysis, and is located in the /ch07/geodata/dem_3857.dem folder, so if you have not already downloaded all...

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