Geospatial Development By Example with Python
| By: | Pablo Carreira |
| Publisher: | Packt Publishing |
| Print ISBN: | 9781785282355 |
| eText ISBN: | 9781785288340 |
| Edition: | 1 |
| Copyright: | 2016 |
| Format: | Reflowable |
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Details
Table of Contents
Build your first interactive map and build location-aware applications using cutting-edge examples in Python
Key Features
- • 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
Book Description
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.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