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Geospatial Development By Example with Python

Geospatial Development By Example with Python

By : Pablo Carreira
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Geospatial Development By Example with Python

Geospatial Development By Example with Python

5 (4)
By: Pablo Carreira

Overview of this book

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 (12 chapters)
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11
Index

Summary


In this chapter, we saw how to distribute jobs into multiple processor cores, allowing the program to use all the available computing power.

Although parallel processing is a great resource, we found in our examples that it's not applicable for all situations. Specifically, when the bottleneck is not the CPU, multiprocessing may downgrade the program speed.

In the course of our examples, we took low-resolution satellite images and were able to increase their resolution and level of detail through resampling and pan sharpening, obtaining images of much greater value for visual analysis.

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