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Python Geospatial Development

Python Geospatial Development

By : Westra
4.3 (4)
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Python Geospatial Development

Python Geospatial Development

4.3 (4)
By: Westra

Overview of this book

Geospatial development links your data to locations on the surface of the Earth. Writing geospatial programs involves tasks such as grouping data by location, storing and analyzing large amounts of spatial information, performing complex geospatial calculations, and drawing colorful interactive maps. In order to do this well, you’ll need appropriate tools and techniques, as well as a thorough understanding of geospatial concepts such as map projections, datums, and coordinate systems. This book provides an overview of the major geospatial concepts, data sources, and toolkits. It starts by showing you how to store and access spatial data using Python, how to perform a range of spatial calculations, and how to store spatial data in a database. Further on, the book teaches you how to build your own slippy map interface within a web application, and finishes with the detailed construction of a geospatial data editor using the GeoDjango framework. By the end of this book, you will be able to confidently use Python to write your own geospatial applications ranging from quick, one-off utilities to sophisticated web-based applications using maps and other geospatial data.
Table of Contents (15 chapters)
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14
Index

Sources of geospatial data in raster format

One of the most enthralling aspects of programs such as Google Earth is the ability to "see" the Earth as you appear to fly above it. This is achieved by displaying satellite and aerial photographs carefully stitched together to provide the illusion that you are viewing the Earth's surface from above.

While writing your own version of Google Earth would be an almost impossible task, it is possible to obtain free satellite imagery in the form of raster-format geospatial data, which you can then use in your own geospatial applications.

Raster data is not just limited to images of the Earth's surface, however; other useful information can be found in raster format—for example, digital elevation maps (DEMs) contain the height of each point on the Earth's surface, which can then be used to calculate the elevation of any desired point. DEM data can also be used to generate two-dimensional images that represent different...

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