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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

Punching holes in polygons with a symmetric difference operation


Why, oh why would we want to punch holes in polygons and create a donut? Well, this is done for several reasons, for example, you may want to remove a lake polygon from a forest polygon that it overlaps since it sits in the middle of the forest and is, therefore, included in your area calculations.

Another example is where we have a set of polygons representing a golf course's fairways and a second set of polygons representing the greens that overlap these fairways. Our task is to calculate the correct number of square meters of fairways. The greens will create our donuts in a fairway's polygons.

This is translated into spatial operation terminology and means that we need to perform a symmetric difference operation or, in ESRI terminology, an "erase" operation.

Getting ready

In this example, we will create two sets of visualizations to see our results. Our output will generate Well Known Text (WKT) that is displayed in your browser...

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