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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

Point cloud data

Point cloud data is any data collected as the (x,y,z) location of a surface point based on some sort of focused energy return. Point cloud data can be created using lasers, radar waves, acoustic soundings, or other waveform generation devices. The spacing between points is arbitrary and is dependent on the type and position of the sensor collecting the data. In this book we will primarily be concerned with LIDAR data and radar data. Radar point cloud data is typically collected on space missions while LIDAR is typically collected by terrestrial or airborne vehicles. But conceptually both types of data are similar.

LIDAR uses powerful laser range-finding systems to model the world with very high precision. The term LIDAR or LiDAR is a combination of the words light and radar. Some people claim it also stands for Light Detection and Ranging. LIDAR sensors can be mounted on aerial platforms including satellites, airplanes, or helicopters. They can also be mounted on vehicles...

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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