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Learning Geospatial Analysis with Python-Second Edition

You're reading from   Learning Geospatial Analysis with Python-Second Edition An effective guide to geographic information systems and remote sensing analysis using Python 3

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Product type Paperback
Published in Dec 2015
Publisher Packt
ISBN-13 9781783552429
Length 394 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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Toc

Table of Contents (12) Chapters Close

Preface 1. Learning Geospatial Analysis with Python FREE CHAPTER 2. Geospatial Data 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 Modeling 9. Real-Time Data 10. Putting It All Together Index

Metadata


As discussed in Chapter 1, Learning Geospatial Analysis with Python, metadata is any data that describes the associated dataset. Common examples of metadata include basic elements such as the footprint of the dataset on the Earth as well as more detailed information such as spatial projection and information describing how the dataset was created. Most data formats contain the footprint or bounding box of the data on the Earth. Detailed metadata is typically stored in a separate location in a standard format such as the U.S. Federal Geographic Data Committee (FGDC) Content Standard for Digital Geospatial Metadata (CSDGM), ISO, or the newer European Union initiative, which includes metadata requirements, called the Infrastructure for Spatial Information in the European Community (INSPIRE).

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