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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
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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
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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
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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

Types of geospatial data

In the previous chapter, we looked briefly at some of the more common formats used to store and transfer raster and vector geospatial data. Let's now look at some of the more important types of geospatial data you are likely to encounter.

Shapefiles

As we saw in the previous chapter, a shapefile is a collection of files on disk, which together hold a set of geospatial features along with their attributes and geometries. For example, the following illustration shows the data stored in a typical shapefile:

Shapefiles

Because the shapefile format has been around for many years, and dates back to the dBase days, a single shapefile is made up of several individual files. Typically, these files are combined into a ZIP archive for distribution.

Shapefiles are hugely popular because they make it so easy to store and distribute geospatial data. Practically every GIS system and library that works with geospatial data is able to understand the shapefile format.

Shapefiles, however, do...

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Python GeoSpatial Analysis Essentials
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