Mastering Geospatial Analysis with Python

Explore GIS processing and learn to work with various tools and libraries in Python

Key Features

• Read, analyze, and present geospatial data programmatically
• Understand the powerful geoprocessing tools of Python
• Automate your Geospatial workflows using Python

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. As geospatial programming is a specialized subset of Python programming, 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. From here, you will move on to working with rasters and vector analysis. 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. In the last module, you will work with machine learning Python libraries and also perform geospatial analysis using distributed servers.

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 these libraries for data conversion, data management, web map 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.
• Explore the use of machine learning and cluster computing with geospatial data..

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.

Silas Toms is a certified GIS Professional and the author of the first edition of ArcPy and ArcGIS. President and founder of Loki Intelligent Corporation, a location information firm located in San Francisco, California, he is an expert in real-time geographic information systems and analysis automation. Along with Dara O'Beirne and Arini Geographics, he developed the real-time common operational picture used at Super Bowl 50 and all other events at Levi's Stadium in Santa Clara, California. This dynamic system was recognized by the White House and ESRI President, Jack Dangermond, as a unique and powerful application of GIS, allowing the federal, state, and local government to coordinate and communicate in real time, for the first time ever.

As the President of Loki Intelligent, Silas is focused on unique applications of GIS that will power the future of location information. The sheer amount of data collected through sensors and mobile reporting demands automation and data processing improvements to turn the raw input into location intelligence. He believes that correct application of geospatial analysis, web mapping, and mobile data collection will improve the decision-making processes within the government and business. Loki is location information, and information is power.

Eric van Rees is a geospatial professional and the author of instructionals on the ArcGIS API for Python and on Jupyter Notebooks.

Paul Crickard author of a great book on the Leaflet JavaScript module.

Paul Crickard III 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, and built web-based GIS applications to display and modify architectural data. He has given presentations to the New Mexico Public School Facilities Authority on BIM and GIS integration and on the use of GIS for Facility Planning, and the BIM505 Users Group on GIS as an interactive frontend to BIM and editing BIM data via web applications. Currently, Paul works as a programmer analyst in Albuquerque, specializing in the design, maintenance, and the implementation of geospatial applications. He has written plugins and extensions for ArcMap and ArcGIS Explorer Desktop to utilize NoSQL databases and send data using the Advanced Message Queuing Protocol (AMQP). Paul has built applications using OpenLayers and Leaflet.js and is currently utilizing the ESRI JavaScript API in production. Paul tries to incorporate Python in geospatial development wherever possible. From building plugins, toolboxes, and the Field Calculator functions in ArcMap to coding standalone desktop and web applications, pyshp is his favorite library for geospatial Python applications. When he is not coding, Paul enjoys relaxing with his wife and son, cooking, and brewing beer.