Geoprocessing with Python

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Manning Publications has a new Python programming book “Geoprocessing with Python“.  As part of of the Manning Early Access Program (MEAP), sections of the books are being made available now. Written by Chris Gerard, a Research Associate for the RS/GIS Lab at the Utah State University for over a decade.  The book covers geoprocessing with Python using open source libraries.  The first introductory chapter is available for free.  

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 you how to use the Python programming language along with free and open source tools to read, write, and process geospatial data. You’ll learn how to access available data sets to make maps or perform your own analyses using free and open source tools like the GDAL, Shapely, and Fiona Python modules. You’ll 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. You’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.



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