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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

Product type Paperback

Published in Apr 2018

Publisher Packt

ISBN-13 9781788293334

Length 440 pages

Edition 1st Edition

Languages

Python

Tools

Anaconda

Concepts

Geospatial Analysis

Authors (3):

Toms

Paul Crickard

Eric van Rees

View More author details

Table of Contents (23) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

1. Package Installation and Management FREE CHAPTER

2. Introduction to Geospatial Code Libraries

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

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Index

Summary

In this chapter, we introduced the major code libraries used to process and analyze geospatial data. You learned the characteristics of each library, how they are related or are distinct to each other, how to install them, where to find additional documentation, and typical use cases. GDAL is a major library that includes two separate libraries, OGR and GDAL. Many other libraries and software applications use GDAL functionality under the hood, examples are Fiona and Rasterio, which were both covered in this chapter. These were created to make it easier to work with GDAL and OGR in a more Pythonic way.

The next chapter will introduce spatial databases. These are used for data storage and analysis, with examples being SpatiaLite and PostGIS. You will also learn how to use different Python libraries to connect to these databases.

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Authors (3)

Toms

Toms

Silas Toms is a long-time geospatial professional and author who has previously published ArcPy and ArcGIS and Mastering Geospatial Analysis with Python. His career highlights include developing the real-time common operational picture used at Super Bowl 50, building geospatial software for autonomous cars, designing computer vision for next-gen insurance, and developing mapping systems for Zillow. He now works at Volta Charging, predicting the future of electric vehicle adoption and electric charging infrastructure.

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Paul Crickard

Paul Crickard

Paul Crickard authored a book on the Leaflet JavaScript module. He has been programming for over 15 years and has focused on GIS and geospatial programming for 7 years. He spent 3 years working as a planner at an architecture firm, where he combined GIS with Building Information Modeling (BIM) and CAD. Currently, he is the CIO at the 2nd Judicial District Attorney's Office in New Mexico.

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Eric van Rees

Eric van Rees

Eric van Rees was first introduced to Geographical Information Systems (GIS) when studying Human Geography in the Netherlands. For 9 years, he was the editor-in-chief of GeoInformatics, an international GIS, surveying, and mapping publication and a contributing editor of GIS Magazine. During that tenure, he visited many geospatial user conferences, trade fairs, and industry meetings. He focuses on producing technical content, such as software tutorials, tech blogs, and innovative new use cases in the mapping industry.

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