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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

Introduction


Discovering how two datasets spatially relate to each other when they are placed over one another is called overlay analysis. An overlay can be compared to a sheet of tracing paper. For example, you could overlay the tracing paper on top of your base map and see what areas overlap each other. This process is and was a game changer in spatial analysis and modeling. Computer-aided GIS computations can therefor automatically identify where two geometry sets spatially touch for example.

The goal of this chapter is to give you a feel for the most common overlay analysis functions, such as unions, intersects, and symmetrical differences. These are based on the Dimensionally Extended nine intersection model (DE-9IM), which can be found at http://en.wikipedia.org/wiki/DE-9IM, and describes our list of possible overlays. All processes that we use or name here are derived using a combination of these nine predicates.

We will explore these topology rules in depth in Chapter 9, Topology Checking...

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