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Mastering Geospatial Analysis with Python

You're reading from   Mastering Geospatial Analysis with Python Explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788293334
Length 440 pages
Edition 1st Edition
Languages
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Authors (3):
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Silas Toms Silas Toms
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Silas Toms
Paul Crickard Paul Crickard
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Paul Crickard
Eric van Rees Eric van Rees
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Eric van Rees
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Table of Contents (18) Chapters Close

Preface 1. Package Installation and Management 2. Introduction to Geospatial Code Libraries FREE CHAPTER 3. Introduction to Geospatial Databases 4. Data Types, Storage, and Conversion 5. Vector Data Analysis 6. Raster Data Processing 7. Geoprocessing with Geodatabases 8. Automating QGIS Analysis 9. ArcGIS API for Python and ArcGIS Online 10. Geoprocessing with a GPU Database 11. Flask and GeoAlchemy2 12. GeoDjango 13. Geospatial REST API 14. Cloud Geodatabase Analysis and Visualization 15. Automating Cloud Cartography 16. Python Geoprocessing with Hadoop 17. Other Books You May Enjoy

Introduction to Geospatial Code Libraries

This chapter will introduce the major code libraries used to process and analyze geospatial data. You will learn the characteristics of each library, how they are related to each other, how to install them, where to find additional documentation, and typical use cases. These instructions assume that the user has a recent (2.7 or later) version of Python on their machine, and do not cover installing Python. Next, we'll discuss how all of these packages fit together and how they are covered in the rest of this book.

The following libraries will be covered in this chapter:

  • GDAL/OGR
  • GEOS
  • Shapely
  • Fiona
  • Python Shapefile Library (pyshp)
  • pyproj
  • Rasterio
  • GeoPandas
You have been reading a chapter from
Mastering Geospatial Analysis with Python
Published in: Apr 2018
Publisher: Packt
ISBN-13: 9781788293334
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