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Geospatial Development By Example with Python

You're reading from   Geospatial Development By Example with Python Build your first interactive map and build location-aware applications using cutting-edge examples in Python

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Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781785282355
Length 340 pages
Edition 1st Edition
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Author (1):
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Pablo Carreira Pablo Carreira
Author Profile Icon Pablo Carreira
Pablo Carreira
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Table of Contents (12) Chapters Close

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

Chapter 1. Preparing the Work Environment

Working with a programming language as a tool for geoprocessing provides the opportunity to construct a personalized application that can more optimally perform the task required by the user. This means that repetitive tasks can be automated, file inputs and outputs can be customized, and processes can be tuned to perform exactly what you want to be done.

Python is a powerful programming language that is gaining special attention as a tool for geoprocessing and scientific analysis. A number of factors may have contributed to its popularization, and three among them are worth mentioning: it's a scripting language, it's flexible and easy to learn, and it has a wide range of libraries available as open source software.

The number of available libraries and packages allow users to spend less time in programming basic functionalities and more in building processes and workflows to reach their goals.

In this first chapter, we will go through the process of installing all the libraries that you will need to go through the examples; it's likely that these same libraries will also satisfy most of your needs in real-world applications. Then, we will set up an Integrated Development Environment (IDE) that will help organize code and avoid mistakes. Finally, we will write a sample program with one of the libraries. Therefore, here are the topics that will be covered:

  • Installing Python and the packages that you need for the examples in this book
  • Learning the basics of the packages that you will use
  • Installing an IDE to write and organize your code
  • Creating a project for this book
  • Writing your first code
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