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Python Geospatial Analysis Cookbook

Python programiranje Python programiranje

Python Geospatial Analysis Cookbook

Autor: Michael Diener
Broj strana: 330
ISBN broj: 9781783555079
Godina izdanja: 2015.

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About This Book

  • Explore the process of using geospatial analysis to solve simple to complex problems with fast, reusable recipes
  • Concise step-by-step instructions to teach you all about vector, overlay, raster, routing, and topology analysis
  • Discover performance enhancing tools for your daily work

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
  • Perform and ensure quality assurance checks with topology rules in Python
  • Find the shortest 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 a web application with GeoDjango to include your spatial analysis tools built from the previous vector, raster, and overlay analysis

In Detail

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. Finally, we put it all together in a GeoDjango web application that demonstrates a final working 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.


Michael Diener

Michael Diener graduated from Simon Fraser University, British Columbia, Canada, in 2001 with a Bachelor of Science degree in Geography. He began working in 1995 with Environment Canada as a GIS (Geographic Information Systems) Analyst and has continued to work with GIS ever since.

Beginning in 2008, he founded a company called GOMOGI focused on performing GIS for mobile and web applications with open source software.

Michael holds seminars for organizations wanting to explore or discover the possibilities of how GIS can increase productivity and better answer spatial questions. He is also the creative head of new product development and a Python developer working with a wide range of spatial software on a daily basis. Developing spatial applications through the years, he has always used Python to get the job done.

He is also lecturer of GIS at the Alpen Adria University, Klagenfurt, where he enjoys teaching students the wonderful powers of GIS and explaining how to solve spatial problems with open source GIS and Python.

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