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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

Reading and writing geospatial data using Python

Since we will be using the GDAL/OGR library to access geospatial data, let's take a closer look at how you can read and write both vector-format and raster-format data using this library.

Reading vector data

In the previous chapter, we wrote a simple program that reads the features out of a shapefile. Here is a copy of that program:

import osgeo.ogr
shapefile = osgeo.ogr.Open("TM_WORLD_BORDERS-0.3.shp")
layer = shapefile.GetLayer(0)
for i in range(layer.GetFeatureCount()):
    feature = layer.GetFeature(i)
    feature_name = feature.GetField("NAME")
    geometry = feature.GetGeometryRef()
    geometry_type = geometry.GetGeometryName()
    print i, feature_name, geometry_type

Let's take a closer look at how this program works, and more generally, how to read vector-format data using the OGR library.

When reading geospatial data, the osgeo.ogr.Open() function takes just a single parameter: the name of the dataset to...

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Python GeoSpatial Analysis Essentials
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