Pablo Carreira (2016)
From Python programming good practices to the advanced use of analysis packages, this book teaches you how to write applications that will perform complex geoprocessing tasks that can be replicated and reused.
- Learn the full geo-processing workflow using Python with open source packages
- Create press-quality styled maps and data visualization with high-level and reusable code
- Process massive datasets efficiently using parallel processing
Chris Garrard (2016)
Geoprocessing with Python teaches you how to use the Python programming language along with free and open source tools to read, write, and process geospatial data. You’ll learn how to access available data sets to make maps or perform your own analyses using free and open source tools like the GDAL, Shapely, and Fiona Python modules. You’ll master core practices like handling multiple vector file formats, editing and manipulating geometries, applying spatial and attribute filters, working with projections, and performing basic analyses on vector data. You’ll also learn how to create geospatial data, rather than just consuming it. The book also covers how to manipulate and analyze raster data, such as aerial photographs, satellite images, and digital elevation models.
- Geoprocessing from the ground up
- Using OGR, Fiona, and Shapely to work with vector data
- Using GDAL to read and write raster data efficiently
- Processing and analyzing raster data with NumPy and SciPy
- Visualizing data with Matplotlib
- Write your own custom geoprocessing tools
Michael Diener (2015)
Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python.
- Explore the practical process of using geospatial analysis to solve simple to complex problems with reusable recipes
- Concise step-by-step instructions to teach you about projections, vector, raster, overlay, indoor routing and topology analysis
- Create a basic indoor routing application with geodjango
Erik Westra (2015)
Process, analyze, and display geospatial data using Python libraries and related tools
- Learn to build a complete geospatial application from scratch using Python
- Create good-looking maps based on the results of your analysis
- This is a fast-paced guide to help you explore the key concepts of geospatial to obtain high quality spatial data
Karim Bahgat (2015)
Utilize Python with open source libraries to build a lightweight, portable, and customizable GIS desktop application.
- Develop a GIS application that you can easily modify and customize
- Optimize your GIS application for user productivity and efficiency
- Discover Python’s many geospatial libraries and learn how they can work together
Joel Lawhead (2013)
If you know Python and would like to use it for Geospatial Analysis this book is exactly what you’ve been looking for. With an organized, user-friendly approach it covers all the bases to give you the necessary skills and know-how.
- Construct applications for GIS development by exploiting Python
- Focuses on built-in Python modules and libraries compatible with the Python Packaging Index distribution system- no compiling of C libraries necessary
- This is a practical, hands-on tutorial that teaches you all about Geospatial analysis in Python
Erik Westra (2013)
If you’re experienced in Python here’s an opportunity to get deep into Geospatial development, linking data to global locations. No prior knowledge required – this book takes you through it all, step by step.
- Build your own complete and sophisticated mapping applications in Python.
- Walks you through the process of building your own online system for viewing and editing geospatial data.
- Practical, hands-on tutorial that teaches you all about geospatial development in Python