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 Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python Unleash the power of Python 3 with practical techniques for learning GIS and remote sensing

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837639175
Length 432 pages
Edition 4th 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 (18) Chapters Close

Preface 1. Part 1:The History and the Present of the Industry
2. Chapter 1: Learning about Geospatial Analysis with Python FREE CHAPTER 3. Chapter 2: Learning about Geospatial Data 4. Chapter 3: The Geospatial Technology Landscape 5. Part 2:Geospatial Analysis Concepts
6. Chapter 4: Geospatial Python Toolbox 7. Chapter 5: Python and Geospatial Algorithms 8. Chapter 6: Creating and Editing GIS Data 9. Chapter 7: Python and Remote Sensing 10. Chapter 8: Python and Elevation Data 11. Part 3:Practical Geospatial Processing Techniques
12. Chapter 9: Advanced Geospatial Modeling 13. Chapter 10: Working with Real-Time Data 14. Chapter 11: Putting It All Together 15. Assessments 16. Index 17. Other Books You May Enjoy

Working with LiDAR data

LiDAR stands for Light Detection and Ranging. It is similar to radar-based images but uses finite laser beams that hit the ground hundreds of thousands of times per second to collect a huge amount of very fine (x, y, z) locations, as well as time and intensity. The intensity value is what really separates LiDAR from other data types. For example, the asphalt rooftop of a building may be of the same elevation as the top of a nearby tree, but the intensities will be different. Just like remote sensing, radiance values in a multispectral satellite image allow us to build classification libraries. The intensity values of LiDAR data allow us to classify and colorize LiDAR data.

The high volume and precision of LiDAR actually make it difficult to use. A LiDAR dataset is referred to as a point cloud because the shape of the dataset is usually irregular as the data is three-dimensional with outlying points. There are not many software packages that effectively visualize...

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