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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
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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
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

Learning Mapnik

Now that you've seen what Mapnik can do and have some idea of how Mapnik works, let's look more deeply at some of the other aspects of the Mapnik library. We will be covering datasources, symbolizers, and map rendering in this section of the chapter.

Datasources

Each map layer is associated with a datasource (a subclass of mapnik.Datasource) that provides the data to be displayed on the map. The various types of datasources are made available through C++ plugins, which are enabled or disabled when Mapnik is compiled. To see if a given type of datasource is available, you check to see if the associated plugin has been installed into your copy of Mapnik. You can see a list of the installed plugins (and therefore, the supported datasources) by typing the following into the Python command prompt:

import mapnik
print list(mapnik.DatasourceCache.plugin_names())

The following datasource plugins are currently supported by Mapnik:

  • csv: This plugin provides the mapnik.CSV datasource...
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Tech Concepts
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Programming languages
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Python GeoSpatial Analysis Essentials
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