Book Image

Mastering Geospatial Analysis with Python

By : Silas Toms, Paul Crickard, Eric van Rees
Book Image

Mastering Geospatial Analysis with Python

By: Silas Toms, Paul Crickard, Eric van Rees

Overview of this book

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.
Table of Contents (23 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
7
Geoprocessing with Geodatabases
Index

Cloud geodatabase solutions


Cloud storage of geospatial data has become a common part of many GIS architectures. Whether it is used as a backup to an on-premises solution, replaces an on-premises solution, or is combined with a local solution to provide internet support for an intranet-based system, the cloud is a big part of the future of GIS. 

With ArcGIS Online, CARTO, MapBox, and now MapD, the options for a cloud data store that support geospatial data are more numerous than ever. Each offers a visualization component and a different type of data storage and each will integrate with your data and software in different ways.

ArcGIS Online, while also offering stand-alone options (that is, direct data upload), integrates with ArcGIS Enterprise (formerly ArcGIS Server) to consume enterprise REpresentational State Transfer (REST) web services that are stored on a local geodatabase. ArcGIS Online is built on top of Amazon Web Services (AWS) and all of the server architecture is hidden from...