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
Geoprocessing with Geodatabases

Chapter 4. Data Types, Storage, and Conversion

This chapter will focus on the many different data types that exist within GIS and will provide an overview of the major data types in GIS and how to use the previously covered Python code libraries to read and write geospatial data. Apart from reading and writing different geospatial data types, you'll learn how to use these libraries to perform file conversion between different data types and how to download data from geospatial databases and remote sources.

The following vector and raster data types will be covered in this chapter:

  • Shapefiles
  • GeoJSON
  • KML
  • GeoPackages
  • GeoTIFF

The following file actions will also be covered, using Python geospatial data libraries covered in Chapter 2, Introduction to Geospatial Code Libraries:

  • Opening existing files
  • Reading and displaying different attributes (spatial and non-spatial)
  • Creating and writing new geospatial data in different formats
  • Converting one file format to another
  • Downloading geospatial data

We'll provide...