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Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python Understand GIS fundamentals and perform remote sensing data analysis using Python 3.7

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Product type Paperback
Published in Sep 2019
Publisher
ISBN-13 9781789959277
Length 456 pages
Edition 3rd 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 (15) Chapters Close

Preface 1. Section 1: The History and the Present of the Industry FREE CHAPTER
2. Learning about Geospatial Analysis with Python 3. Learning Geospatial Data 4. The Geospatial Technology Landscape 5. Section 2: Geospatial Analysis Concepts
6. Geospatial Python Toolbox 7. Python and Geographic Information Systems 8. Python and Remote Sensing 9. Python and Elevation Data 10. Section 3: Practical Geospatial Processing Techniques
11. Advanced Geospatial Python Modeling 12. Real-Time Data 13. Putting It All Together 14. Other Books You May Enjoy

Real-Time Data

A common saying among geospatial analysts is: A map is outdated as soon as it's created. This saying reflects the fact that the Earth and everything on it are constantly changing. For most of the history of geospatial analysis and through most of this book, geospatial products are relatively static. Raw datasets are typically updated anywhere from a few months to a few years. The age of geospatial data in a map is referred to as data currency.

Data currency has traditionally not been the primary focus because of the time and expense needed to collect data. Web mapping, wireless cellular modems, and low-cost GPS antennas have changed that focus. It is now logistically feasible and even quite affordable to monitor a rapidly changing object or system and broadcast those changes to millions of people online. This change is revolutionizing geospatial technology...

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