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  • Book Overview & Buying Python GeoSpatial Analysis Essentials
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Python GeoSpatial Analysis Essentials

Python GeoSpatial Analysis Essentials

By : Westra
4 (2)
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Python GeoSpatial Analysis Essentials

Python GeoSpatial Analysis Essentials

4 (2)
By: Westra
Buy this Book

Overview of this book

If you are an experienced Python developer and wish to get up-to-speed with geospatial programming, then this book is for you. While familiarity with installing third-party Python libraries would be an advantage, no prior knowledge of geospatial programming is required.
Table of Contents (8 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Geospatial Analysis and Techniques
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1. Geospatial Analysis and Techniques
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About geospatial analysis
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Understanding geospatial data
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Setting up your Python installation
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Obtaining some geospatial data
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Unlocking the shapefile
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Analyzing the data
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A program to identify neighboring countries
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Summary
2
2. Geospatial Data
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2. Geospatial Data
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Geospatial data quality
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Types of geospatial data
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Sources of freely available geospatial data
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Reading and writing geospatial data using Python
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Dealing with spatial reference systems
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Geospatial data errors and how to fix them
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Summary
3
3. Spatial Databases
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3. Spatial Databases
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Spatial database concepts
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Installing a spatial database
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Accessing PostGIS from Python
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Setting up a spatial database
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Importing spatial data
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Querying spatial data
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Manipulating spatial data
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Exporting spatial data
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Summary
4
4. Creating Maps
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4. Creating Maps
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Introducing Mapnik
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Learning Mapnik
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A working example
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Next steps
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Summary
5
5. Analyzing Geospatial Data
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5. Analyzing Geospatial Data
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Libraries for spatial analysis
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Spatial analysis recipes
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Summary
6
6. Building a Complete Geospatial Analysis System
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6. Building a Complete Geospatial Analysis System
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Matching GPS data against a map
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An overview of the GPS Heatmap system
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Obtaining the necessary data
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Implementing the GPS Heatmap system
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Further improvements
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Summary
7
Index
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Index

Libraries for spatial analysis

You already have a couple of libraries that are useful for analyzing geospatial data: the OGR library includes methods for comparing and manipulating geometries, and Shapely is a wonderful library for working with and analyzing geometry data. There are, however, two other libraries that you will want to become familiar with: PyProj, which is a powerful library for calculating distances and locations on the Earth's surface, and NetworkX, which can build abstract mathematical models out of geospatial data and then analyze those models to solve various problems.

Let's take a closer look at these two libraries and install them both onto your computer.

PyProj

PyProj (https://pypi.python.org/pypi/pyproj) is a powerful tool for working with spatial reference systems using Python. PyProj itself is simply a Python interface to the PROJ.4 cartographic projection library, which is written in C. So, to install PyProj, you typically need to install the PROJ.4...

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Python GeoSpatial Analysis Essentials
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