Geospatial.Development.By.Example.with.Python下载

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. Table of Contents Chapter 1. Preparing the Work Environment Chapter 2. The Geocaching App Chapter 3. Combining Multiple Data Sources Chapter 4. Improving the App Search Capabilities Chapter 5. Making Maps Chapter 6. Working with Remote Sensing Images Chapter 7. Extract Information from Raster Data Chapter 8. Data Miner App Chapter 9. Processing Big Images Chapter 10. Parallel Processing