Python Geospatial Analysis Cookbook: Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python

Diener

€41.99

4.4 (5 Ratings)

Paperback Nov 2015 310 pages 1st Edition

Diener

€41.99

4.4 (5 Ratings)

Paperback Nov 2015 310 pages 1st Edition

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Description

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.

Who is this book 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

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Learning Geospatial Analysis with Python-Second Edition

€41.99

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Christian S. Dec 14, 2015

Chapter 1 does a good job in getting you up and running with Python and the main libraries used in the following chapters.Chapter 2 explains coordinate systems and introduces Shapefile and GeoJSON file formats. Chapter 3 continues explaining image formats such as raster and vector. Also we setup our PostgreSQL and PostGIS. The instruction are clear and easy to follow. An interesting example is the conversion of an OpenStreeMap to a Shapefile. In Chapter 4 the focus is on PostGIS.Chapter 5, 6 and 7 deal with vector and geometry analysis. There are examples to calculate intersections, distances, and operations between polygons.Chapter 8 explains network analysis. There are very interesting examples on how to calculate the shortest path and an example to calculate indoor route walk time. Definitely this was one of the most interesting chapters.Chapter 9 deals with topology and validations rules. It has several example algorithms to validate rules.Chapter 10 and 11 finalize the implementation of the previous chapters, dealing with the final presentation through visualizations for the web.In summary I would recommend this book, it has enough content to serve as a reference to find examples in which you can dig deeper. This is a more practical book in the sense that you will not find detailed explanations of the algorithms, and it uses several third party libraries in the examples to get the job done.One thing it could have been improved is the layout of the source code.

Amazon Verified review

DC_ Jan 05, 2016

The first chapter regarding getting everything setup is quite thorough regarding setting up the various Python libraries that are needed throughout the book. I found chapter 8 on network analysis very useful and interesting. This books gives a good grounding with code examples on which to build.

Amazon Kunde Jun 04, 2019

A very helpful book, gives practical directions tp script useful applications within the field of geospatial analyses. However, some scripts could be a bit better explained for real beginners.

Amazon Customer Dec 28, 2015

Great introduction to a variety of Python libraries available for geospatial analysis. Both vector and raster analysis is covered with interesting examples. Many of the recipes will act as a base for the reader to take snippets from and build upon to implement into their own workflows. Algorithms and code not heavily explained which might not be great for complete beginners. Overall I recommend this book as it will open your eyes to some of the geospatial analysis techniques that you may not have realised were easy to implement outside of a standard GIS software package.

USHANT SUMAN Dec 07, 2015

Nice book readymade recipes for many day to day work.

Python Geospatial Analysis Cookbook: Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python

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