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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
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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

Geospatial data quality

Imagine that you are writing a program where you need to display the location of each city and town on top of a raster basemap. You dutifully obtain a nice raster datasource to use for the basemap, and then search the Internet for a source of city and town data. You choose the National Geospatial Intelligence Service (NGIS) website to download a database of place names, which you then draw onto your map. This database includes, among other things, the latitude and longitude of each place name:

Location

Latitude

Longitude

Abache

7.3551

7.6407

Abacheke

5.50372

6.729519

Abacher

13.816667

20.816667

Abacheri

14.183333

41.5

Abachi

7.3551

7.6407

...and so on

  

So far so good, but when your program is complete, the locations look suspiciously regular when the user zooms in on your map:

If you were to draw a grid on top of this map, you can see exactly what the problem is:

As you can see, the locations are regularly spaced—despite there being lots of precision...

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Tech Concepts
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Programming languages
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Python GeoSpatial Analysis Essentials
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