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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 a rule – only one point inside a polygon


A long time ago in GIS history, not having more than one point present in a polygon was super important because one point per polygon was the standard way to demonstrate a topologically clean polygon with its associated attribute and ID. Today, it is still important for many other reasons, such as assigning attributes to polygons based on points inside a polygon. We must perform a spatial join between the polygon and point to assign these valuable attributes. If two points are located in one polygon, which attributes do you use? This recipe is about creating a rule to check your data beforehand to ensure that only one point is located in each polygon. If this test fails, you will get a list or errors; if it passes, the test returns True.

Getting ready

Data again plays the central role here, so check that your /ch09/geodata/ folder is ready with two input Shapefiles containing topo_polys.shp and topo_points.shp. The Shapely library performs...

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