Build your first interactive map and build location-aware applications using cutting-edge examples in Python

About This Book

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

Who This Book Is For

Geospatial Development By Example with Python is intended for beginners or advanced developers in Python who want to work with geographic data. The book is suitable for professional developers who are new to geospatial development, for hobbyists, or for data scientists who want to move into some simple development.

What You Will Learn

Prepare a development environment with all the tools needed for geo-processing with Python

Import point data and structure an application using Python's resources

Combine point data from multiple sources, creating intuitive and functional representations of geographic objects

Filter data by coordinates or attributes easily using pure Python

Make press-quality and replicable maps from any data

Download, transform, and use remote sensing data in your maps

Make calculations to extract information from raster data and show the results on beautiful maps

Handle massive amounts of data with advanced processing techniques

Process huge satellite images in an efficient way

Optimize geo-processing times with parallel processing

In Detail

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.

Much more than simple scripts, you will write functions to import data, create Python classes that represent your features, and learn how to combine and filter them.

With pluggable mechanisms, you will learn how to visualize data and the results of analysis in beautiful maps that can be batch-generated and embedded into documents or web pages.

Finally, you will learn how to consume and process an enormous amount of data very efficiently by using advanced tools and modern computers' parallel processing capabilities.

Style and approach

This easy-to-follow book is filled with hands-on examples that illustrate the construction of three sample applications of how to write reusable and interconnected Python code for geo-processing.