Geoprocessing with Python

**Summary**__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.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.**About the Technology**This book is about the science of reading, analyzing, and presenting geospatial data programmatically, using Python. Thanks to dozens of open source Python libraries and tools, you can take on professional geoprocessing tasks without investing in expensive proprietary packages like ArcGIS and MapInfo. The book shows you how.**About the Book**__Geoprocessing with Python__ teaches you how to access available datasets to make maps or perform your own analyses using free tools like the GDAL, NumPy, and matplotlib Python modules. Through lots of hands-on examples, you’ll master core practices like handling multiple vector file formats, editing geometries, applying spatial and attribute filters, working with projections, and performing basic analyses on vector data. The book also covers how to manipulate, resample, and analyze raster data, such as aerial photographs and digital elevation models.**What's Inside*** Geoprocessing from the ground up* Read, write, process, and analyze raster data* Visualize data with matplotlib* Write custom geoprocessing tools* Three additional appendixes available online**About the Reader**To read this book all you need is a basic knowledge of Python or a similar programming language.**About the Author****Chris Garrard** works as a developer for Utah State University and teaches a graduate course on Python programming for GIS.**Table of Contents**1. Introduction2. Python basics3. Reading and writing vector data4. Working with different vector file formats5. Filtering data with OGR6. Manipulating geometries with OGR7. Vector analysis with OGR8. Using spatial reference systems9. Reading and writing raster data10. Working with raster data11. Map algebra with NumPy and SciPy12. Map classification13. Visualizing data**Appendixes*** A - Installation* B - References* C - OGR - online only* D - OSR - online only* E - GDAL - online only