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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

Geoprocessing with Geodatabases

In Chapter 3, Introduction to Geospatial Databases, you learned how to install PostGIS, create a table, add data, and perform basic spatial queries. In this chapter, you will learn how to work with geospatial databases to answer questions and make maps. This chapter will have you load crime data into tables. Once you have populated your geodatabase with real-world data, you will learn how to perform common crime analysis tasks. You will learn how to map queries, query by date ranges, and perform basic geoprocessing tasks such as buffers, point in polygon, and nearest neighbor. You will learn how to add widgets to your Jupyter Notebooks to allow queries to be interactive. Lastly, you will learn how to use Python to create charts from your geospatial queries. As a crime analyst, you will make maps, but not all GIS-related tasks are map-based. Analysts...

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