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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
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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
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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

About geospatial analysis

Geospatial analysis is the process of reading, manipulating, and summarizing geospatial data to yield useful and interesting results. A lot of the time, you will be answering questions like the following:

  • What is the shortest drivable distance between Sausalito and Palm Springs?
  • What is the total length of the border between France and Belgium?
  • What is the area of each National Park in New Zealand that borders the ocean?

The answer to these sorts of questions will typically be a number or a list of numbers. Other types of geospatial analysis will involve calculating new sets of geospatial data based on existing data. For example:

  • Calculate an elevation profile for USA Route 66 from Los Angeles, CA, to Albuquerque, NM.
  • Show me the portion of Brazil north of the equator.
  • Highlight the area of Rarotonga likely to be flooded if the ocean rose by 2 meters.

In these cases, you will be generating a new set of geospatial data, which you would typically then display in a chart or on a map.

To perform this sort of analysis, you will need two things: appropriate geospatial analysis tools and suitable geospatial data.

We are going to perform some simple geospatial analysis shortly. Before we do, though, let's take a closer look at the concept of geospatial data.

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Python GeoSpatial Analysis Essentials
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