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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 3. Combining Multiple Data Sources

Geographic data tends to be heterogeneous. Just to cite a few factors that contribute to this heterogeneity, it may come from different sources, have been produced at different times, or even have different languages. Given this fact, writing programs that can combine multiple sources of data is a fundamental topic in geoprocessing.

Data sources may come in different formats, such as shapefiles, text files, Google KML files, GPX files from GPS, and so on. They may also vary in their contents; for example, they may have different types of geometries, coordinate systems, and attributes.

In this chapter, we will enhance our application by adding the capability to combine multiple sources of data from both different sites and different file formats. In order to achieve this, we will write code capable of identifying the type of data, and depending on this, we will make transformations to obtain a homogeneous set of data.

By extending OGR capabilities...

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