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Geospatial Development By Example with Python

You're reading from   Geospatial Development By Example with Python Build your first interactive map and build location-aware applications using cutting-edge examples in Python

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Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781785282355
Length 340 pages
Edition 1st Edition
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Author (1):
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Pablo Carreira Pablo Carreira
Author Profile Icon Pablo Carreira
Pablo Carreira
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Table of Contents (17) Chapters Close

Geospatial Development By Example with Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Preparing the Work Environment FREE CHAPTER 2. The Geocaching App 3. Combining Multiple Data Sources 4. Improving the App Search Capabilities 5. Making Maps 6. Working with Remote Sensing Images 7. Extract Information from Raster Data 8. Data Miner App 9. Processing Big Images 10. Parallel Processing Index

Working with satellite images


Satellite images are a form of remote sensing data. They are composed of the information collected by satellites and are made available to users as image files. Just like the digital elevation model that we worked on before, these images are made of pixels, each one representing the value of a given attribute for a given geographic extent.

These images can be used to visualize features on Earth using real colors or they can be used to identify a variety of characteristics using parts of the light spectrum invisible to the human eyes.

In order to follow the examples, we will use images from the Landsat 8 satellite. They are available for free on the Internet. Let's take a look at some of the characteristics of this satellite.

Landsat 8 carries two instruments: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS).

These sensors can collect data in a total of 10 different bands processed in a resolution of 4096 possible levels (12-bit). The data...

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