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Learning Geospatial Analysis with Python

You're reading from   Learning Geospatial Analysis with Python Understand GIS fundamentals and perform remote sensing data analysis using Python 3.7

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Product type Paperback
Published in Sep 2019
Publisher
ISBN-13 9781789959277
Length 456 pages
Edition 3rd Edition
Languages
Tools
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Author (1):
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Joel Lawhead Joel Lawhead
Author Profile Icon Joel Lawhead
Joel Lawhead
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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: The History and the Present of the Industry FREE CHAPTER
2. Learning about Geospatial Analysis with Python 3. Learning Geospatial Data 4. The Geospatial Technology Landscape 5. Section 2: Geospatial Analysis Concepts
6. Geospatial Python Toolbox 7. Python and Geographic Information Systems 8. Python and Remote Sensing 9. Python and Elevation Data 10. Section 3: Practical Geospatial Processing Techniques
11. Advanced Geospatial Python Modeling 12. Real-Time Data 13. Putting It All Together 14. Other Books You May Enjoy

Python JSON libraries

JavaScript Object Notation (JSON) is rapidly becoming the number one data exchange format across a lot of fields. The lightweight syntax and its similarity to existing data structures in both the JavaScript that Python borrows some data structures from, as well as JavaScript itself, make it a perfect match for Python.

The following GeoJSON sample document contains a single point:

{
"type": "Feature",
"id": "OpenLayers.Feature.Vector_314",
"properties": {},
"geometry": {
"type": "Point",
"coordinates": [
97.03125,
39.7265625
]
},
"crs": {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:OGC:1.3:CRS84"
}
}
}
...
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