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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 FREE CHAPTER 2. The Geocaching App 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

Getting the basic statistics


As we have previously seen, images or raster data are arrays containing numerical values representing a given real world space. So, they are by consequence statistical samples and they can be used in statistical analysis.

When we import the data, it is converted into NumPy arrays. These arrays are packed with methods for basic statistical calculations. In this topic, we are going to obtain the results from these calculations and save them in a file.

At the end of the previous chapter, we made an image processing pipeline by combining steps that can be saved on the disk. Here, we will follow the same pattern. The statistical computation will be added as another step. Maintaining the same kind of organization allows the user to generate statistics at any point on the processing pipeline. It will be possible to save statistics from all the substeps if needed.

Let's start by organizing our code:

  1. As we do at the beginning of every chapter, we will copy the code from the...

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