Michael Diener, "Python Geospatial Analysis Cookbook"
English | ISBN: 1783555076 | 2015 | EPUB/PDF | 310 pages | 8 MB/5 MB
Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python
About This Book
Explore the practical process of using geospatial analysis to solve simple to complex problems with reusable recipes
Concise step-by-step instructions to teach you about projections, vector, raster, overlay, indoor routing and topology analysis
Create a basic indoor routing application with geodjango
Who This Book Is For
If you are a student, teacher, programmer, geospatial or IT administrator, GIS analyst, researcher, or scientist looking to do spatial analysis, then this book is for you. Anyone trying to answer simple to complex spatial analysis questions will get a working demonstration of the power of Python with real-world data. Some of you may be beginners with GIS, but most of you will probably have a basic understanding of geospatial analysis and programming.
What You Will Learn
Discover the projection and coordinate system information of your data and learn how to transform that data into different projections
Import or export your data into different data formats to prepare it for your application or spatial analysis
Use the power of PostGIS with Python to take advantage of the powerful analysis functions
Execute spatial analysis functions on vector data including clipping, spatial joins, measuring distances, areas, and combining data to new results
Create your own set of topology rules to perform and ensure quality assurance rules in Python
Find the shortest indoor path with network analysis functions in easy, extensible recipes revolving around all kinds of network analysis problems
Visualize your data on a map using the visualization tools and methods available to create visually stunning results
Build an indoor routing web application with GeoDjango to include your spatial analysis tools built from the previous recipes
Geospatial development links your data to places on the Earths 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.
Style and approach
Easy-to-follow, step-by-step recipes, explaining from start to finish how to accomplish real-world tasks.