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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

Raster data

Raster data consists of rows and columns of cells or pixels, with each cell representing a single value. The easiest way to think of raster data is as images, which is how they are typically represented by software. But raster data sets are not necessarily stored as images. They can also be ASCII text files or Binary Large Objects (BLOBs) in databases.

Another difference between geospatial raster data and regular digital images is resolution. Digital images express resolution as dots-per-inch if printed at full size. Resolution can also be expressed or the total number of pixels in the image defined as megapixels. However, geospatial raster data uses the ground distance each cell represents. For example, a raster data set with two-foot resolution means that a single cell represents two feet on the ground, which also means only objects larger than two feet can be identified visually in the data set.

Raster data sets may contain multiple bands, meaning that different wavelengths...

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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