Title: Python Geospatial Analysis Cookbook
Publisher: Packt Publishing
Publication Date: 2015
Language: English
ISBN 10: 1783555076
ISBN 13: 9781783555079
Binding: Taschenbuch
Condition: Neu
Dimensions: 235 millimeters width by 191 millimeters height by 17 millimeters depth
Weight: 582 grams

About this title

Synopsis

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.

About the Author

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 technologies ever since. In 2008, he founded a company called GOMOGI that is focused on building web and mobile GIS application with open source tools. In 2011, the focus changed to indoor wayfinding and navigation solutions and building the indrz platform that Michael had envisioned. From time to time, Michael also holds seminars for organizations wanting to explore or discover the possibilities of how GIS can increase productivity and help better answer spatial questions. He is also the creative head of new product development in his company. His technical skills include working with Python to solve a wide range of spatial problems on a daily basis. Through the years, he has developed many spatial applications with Python, including indrz and golfgis, which are two of the products built by his company, GOMOGI. 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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