Python Geospatial Analysis Essentials电子书

Python Geospatial Analysis Essentials

Table of Contents

Python Geospatial Analysis Essentials

Credits

About the Author

About the Reviewers

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Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Errata

Piracy

Questions

1. Geospatial Analysis and Techniques

About geospatial analysis

Understanding geospatial data

Setting up your Python installation

Installing GDAL

Installing Shapely

Obtaining some geospatial data

Unlocking the shapefile

Analyzing the data

A program to identify neighboring countries

Summary

2. Geospatial Data

Geospatial data quality

Types of geospatial data

Shapefiles

Well-known text

Well-known binary

Spatial databases

Geospatial microformats

GeoJSON

GML

Digital elevation models

Raster basemaps

Multiband raster files

Sources of freely available geospatial data

Natural Earth Data

OpenStreetMap

US Census Bureau

World Borders Dataset

GLOBE

National Elevation Dataset

Reading and writing geospatial data using Python

Reading vector data

Writing vector data

Reading raster data

Writing raster data

Dealing with spatial reference systems

WGS84

Universal Transverse Mercator

Describing spatial reference systems

Transforming coordinates

Calculating lengths and areas

Geospatial data errors and how to fix them

Points

LineStrings

Linear Rings

Polygons

MultiPolygons

Fixing invalid geometries

Summary

3. Spatial Databases

Spatial database concepts

Installing a spatial database

Installing PostgreSQL

Installing PostGIS

Installing psycopg2

Accessing PostGIS from Python

Setting up a spatial database

Importing spatial data

Querying spatial data

Manipulating spatial data

Exporting spatial data

Summary

4. Creating Maps

Introducing Mapnik

Installing Mapnik

A taste of Mapnik

Building a map

Styling a map

Learning Mapnik

Datasources

Symbolizers

PointSymbolizer

LineSymbolizer

PolygonSymbolizer

TextSymbolizer

RasterSymbolizer

Map rendering

A working example

Next steps

Summary

5. Analyzing Geospatial Data

Libraries for spatial analysis

PyProj

NetworkX

Spatial analysis recipes

Calculating and comparing coordinates

Calculating lengths

Calculating areas

Calculating shortest paths

Summary

6. Building a Complete Geospatial Analysis System

Matching GPS data against a map

An overview of the GPS Heatmap system

Obtaining the necessary data

Obtaining GPS data

Downloading the road data

Implementing the GPS Heatmap system

Initializing the database

Importing the road data

Splitting the road data into segments

Constructing a network of directed road segments

Implementing the map matching algorithm

Generating the GPS heatmap

Further improvements

Summary

Index