Mastering Geospatial Analysis with Python: Explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter

Silas Toms · Paul Crickard · Eric van Rees

Apr 2018 · Packt Publishing Ltd

About this ebook

Explore GIS processing and learn to work with various tools and libraries in Python. Key Features Analyze and process geospatial data using Python libraries such as; Anaconda, GeoPandas Leverage new ArcGIS API to process geospatial data for the cloud. Explore various Python geospatial web and machine learning frameworks.Book Description

Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis.

You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.

What you will learn Manage code libraries and abstract geospatial analysis techniques using Python 3. Explore popular code libraries that perform specific tasks for geospatial analysis. Utilize code libraries for data conversion, data management, web maps, and REST API creation. Learn techniques related to processing geospatial data in the cloud. Leverage features of Python 3 with geospatial databases such as PostGIS, SQL Server, and SpatiaLite.Who this book is for

The audience for this book includes students, developers, and geospatial professionals who need a reference book that covers GIS data management, analysis, and automation techniques with code libraries built in Python 3.

About the author

Author Bio: Silas Toms Silas Toms is a geographer and geospatial developer from California. Over the last decade, Silas has become an expert in the use of Python programming for geospatial analysis, publishing two books on the use of ArcPy. Now, as a President of Loki Intelligent Corporation, Silas develops ETL automation tools, interactive web maps, enterprise GIS, and location data for businesses and governments. Silas teaches classes on programming for GIS with BayGeo, and co-hosts The Mappyist Hour podcast. Author Bio: 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. Author Bio: 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.