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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

Chapter 6. Python and Remote Sensing

In this chapter, we will discuss Remote Sensing. This field grows more exciting every day as more satellites are launched and the distribution of data becomes easier. The high availability of satellite and aerial images, as well as interesting new types of sensors launching each year is changing the role remote sensing plays in understanding our world.

And in this field, Python is quite capable. However, in this chapter we will rely more on Python bindings to C libraries than we have in the previous chapters, where the focus was more on using pure Python. The only reason for this change is the size and complexity of remotely sensed data. In remote sensing, we step through each pixel in an image and perform some form of query or mathematical process. An image can be thought of as a large numerical array. And in remote sensing these arrays can be quite large on the order of tens of megabytes to several gigabytes. While Python is fast, only C...

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