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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
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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

Vector data

Vector data is by far the most common geospatial format because it is the most efficient way to store spatial information, and in general requires less computer resources to store and process than raster data. The Open Geospatial Consortium (OGC) has over 16 formats directly related to vector data. Vector data stores only geometric primitives including points, lines, and polygons. But only the points are stored for each type of shape. For example, in the case of a simple straight vector line shape, only the end points would be necessarily stored and defined as a line. Software displaying that data would read the shape type, and then connect the end points with a line dynamically.

Geospatial vector data is similar to the concept of vector computer graphics with some notable exceptions. Geospatial vector data contains positive and negative Earth-based coordinates, while vector graphics typically store computer screen coordinates. Geospatial vector data is also usually linked to...

You have been reading a chapter from
Learning Geospatial Analysis with Python
Published in: Oct 2013
Publisher: Packt
ISBN-13: 9781783281138
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