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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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Toc

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

Summary

In this chapter, you learned how to use spatial queries to perform geoprocessing tasks. You also learned how to map and chart the results of your queries using ipyleaflet and data frames. You learned how to modify the maps and queries using interactive widgets in Jupyter. Lastly, you learned about how triggers work, and were shown a quick example of data checking using trigger. 

In the next chapter, you will learn how to perform geoprocessing tasks using QGIS. You will learn how to use toolboxes that are already included in QGIS. You will learn how to write your own toolboxes that you can use and share with other QGIS users, and you will learn how to use QGIS to map the results. The results can be saved as a QGIS project, or as one of many spatial data formats from QGIS.

 

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