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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

Introducing the ArcGIS API for Python and ArcGIS Online


Esri, the geospatial software company known for its ArcGIS platform, adopted and integrated Python into their ArcGIS desktop software, as well as its successor ArcGIS Pro. The first Python site package developed by Esri was the ArcPy site package, which is a collection of Python modules that offers all existing, as well as extended, ArcMap and ArcGIS Pro functionality. Python can now be used as a scripting and programming language to automate repetitive tasks that involve a lot of interaction with the Graphical User Interface (GUI). With ArcPy, these tasks could be carried out through a Python script, add-on, or toolbox.

Python was introduced successfully with ArcGIS desktop, while GIS itself was moving into the cloud—not only geospatial data but also the software itself. Esri offered organizations the possibility to do this through a variety of cloud environment offerings, using either public, private, or hybrid cloud services. In this...

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