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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

Chapter 6. Working with Remote Sensing Images

In this chapter, we will start working with images—images that may come from a variety of sensors carried by satellites, drones, airplanes, and so on. These types of images, the ones collected from remote sensing devices, are images that contain pixels representing a spectral response from a given geographic region.

Besides just adding images to a map, it is important to prepare the images to be presented on the map. You may need to combine, cut, change the resolution, change values, and perform many other transformations in order to produce a visually appealing map or valuable information.

To perform these transformations on the images, we will go through a process of deduction that will result in a versatile and powerful software structure.

The topics covered here are:

  • Understanding how the images are represented
  • The relation of the images with the real world
  • Combining, cropping, and adjusting the values of the images
  • Creating shaded...
Visually different images
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