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Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python If you know Python and would like to use it for Geospatial Analysis this book is exactly what you've been looking for. With an organized, user-friendly approach it covers all the bases to give you the necessary skills and know-how.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781783281138
Length 364 pages
Edition 1st Edition
Languages
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Table of Contents (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python 2. Geospatial Data FREE CHAPTER 3. The Geospatial Technology Landscape 4. Geospatial Python Toolbox 5. Python and Geographic Information Systems 6. Python and Remote Sensing 7. Python and Elevation Data 8. Advanced Geospatial Python Modelling 9. Real-Time Data 10. Putting It All Together Index

Desktop tools

Geospatial analysis requires the ability to visualize output in order to be complete. This fact makes tools, which can visualize data absolutely critical to the field. There are two categories of geospatial visualization tools. The first is geospatial viewers and the second is geospatial analysis software. The first category, geospatial viewers, allows you to access, query, and visualize data but not edit data in any way. The second category allows you to perform those items as well but also edit data. The main advantage of viewers is that they are typically lightweight pieces of software that launch and load data quickly. Geospatial analysis software requires far more resources to be able to edit complex geospatial data, so it loads slower and often renders data more slowly to provide dynamic editing functionality.

Quantum GIS

Quantum GIS, more commonly known as QGIS, is a complete open source geographic information system. QGIS falls well within the geospatial analysis category...

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