Geoprocessing with Python

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9781617292149: Geoprocessing with Python
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Geospatial data is hard to ignore. Nearly every car, phone, or camera has a GPS sensor, and aerial photos, satellite imagery, and data representing political boundaries, roads, rivers, and streams are available for free download from many websites. Geoprocessing is the science of reading, analyzing, and presenting geospatial data programmatically. The Python language, along with dozens of open source libraries and tools, makes it possible to take on professional geoprocessing tasks without investing in expensive proprietary packages like ArcGIS and MapInfo.

Geoprocessing with Python teaches how to use the Python programming language along with free and open source tools to read, write, and process geospatial data. It shows how to access available data sets to make maps or perform analyses using free and open source tools like the GDAL, Shapely, and Fiona Python modules. Readers will master core practices like handling multiple vector file formats, editing and manipulating geometries, applying spatial and attribute filters, working with projections, and performing basic analyses on vector data. They'll also learn how to create geospatial data, rather than just consuming it. The book also covers how to manipulate and analyze raster data, such as aerial photographs, satellite images, and digital elevation models.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Über den Autor:

Chris Garrard has worked as a developer for the Remote Sensing / GIS Laboratory at Utah State University for over a decade. She teaches a graduate level course on Python programming for GIS and enjoys helping students see the power that comes with writing their own code.

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Chris Garrard
Verlag: Manning Mai 2016 (2016)
ISBN 10: 1617292141 ISBN 13: 9781617292149
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Buchbeschreibung Manning Mai 2016, 2016. Taschenbuch. Buchzustand: Neu. 233x187x25 mm. Neuware - KEY SELLING POINTS 400 pp. Englisch. Artikel-Nr. 9781617292149

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