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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

Remote sensing concepts

Most of the GIS concepts we've described also apply to raster data. However, raster data has some unique properties as well. Earlier in this chapter, when we went over the history of remote sensing, the focus was on Earth imaging from aerial platforms. It is important to note that raster data can come in many forms, including ground-based radar, laser range finders, and other specialized devices to detect gases, radiation, and other forms of energy in a geographic context.

For the purpose of this book, we will focus on remote sensing platforms that capture large amounts of Earth data. These sources included Earth imaging systems, certain types of elevation data, and some weather systems, where applicable.

Images as data

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