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Book Description

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.

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

  • Work with vector data

  • 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. Copyright
    2. Brief Table of Contents
    3. Table of Contents
    4. Preface
    5. Acknowledgments
    6. About this Book
    7. About the Author
    8. About the Cover Illustration
    9. Chapter 1. Introduction
    10. Chapter 2. Python basics
    11. Chapter 3. Reading and writing vector data
    12. Chapter 4. Working with different vector file formats
    13. Chapter 5. Filtering data with OGR
    14. Chapter 6. Manipulating geometries with OGR
    15. Chapter 7. Vector analysis with OGR
    16. Chapter 8. Using spatial reference systems
    17. Chapter 9. Reading and writing raster data
    18. Chapter 10. Working with raster data
    19. Chapter 11. Map algebra with NumPy and SciPy
    20. Chapter 12. Map classification
    21. Chapter 13. Visualizing data
    22. Appendix A. Installation
    23. Appendix B. References
    24. Index
    25. List of Figures
    26. List of Tables
    27. List of Listings
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