Python Geospatial Development - Third Edition

Erik Westra

• Publisher: Packt Publishing
• Year: 2016
• eBook ISBN: 9781782174981
• Edition: 3
• Topic: Computer Science
• Subtopic: Programming in Python
• Index: Computer Science

Develop sophisticated mapping applications from scratch using Python 3 tools for geospatial developmentAbout This Book• Build web applications based around maps and geospatial data using Python 3.x• Install and use various toolkits and obtain geospatial data for use in your programs• This practical, hands-on book will teach you all about geospatial development in PythonWho This Book Is ForThis book is for experienced Python developers who want to learn about geospatial concepts, obtain and work with geospatial data, solve spatial problems, and build sophisticated map-based applications using Python.What You Will Learn• Access, manipulate, and display geospatial data from within your Python programs• Master the core geospatial concepts of location, distance, units, projections, and datums• Read and write geospatial data in both vector and raster format• Perform complex, real-world geospatial calculations using Python• Store and access geospatial information in a database• Use points, lines, and polygons within your Python programs• Convert geospatial data into attractive maps using Python-based tools• Build complete web-based mapping applications using PythonIn DetailGeospatial development links your data to locations on the surface of the Earth. Writing geospatial programs involves tasks such as grouping data by location, storing and analyzing large amounts of spatial information, performing complex geospatial calculations, and drawing colorful interactive maps. In order to do this well, you'll need appropriate tools and techniques, as well as a thorough understanding of geospatial concepts such as map projections, datums, and coordinate systems.This book provides an overview of the major geospatial concepts, data sources, and toolkits. It starts by showing you how to store and access spatial data using Python, how to perform a range of spatial calculations, and how to store spatial data in a database. Further on, the book teaches you how to build your own slippy map interface within a web application, and finishes with the detailed construction of a geospatial data editor using the GeoDjango framework.By the end of this book, you will be able to confidently use Python to write your own geospatial applications ranging from quick, one-off utilities to sophisticated web-based applications using maps and other geospatial data.Style and approach This book is a comprehensive course in geospatial development. The concepts you need to know are presented in a hands-on fashion with example code to help you to solve real-world problems right away. Larger programs are built up step by step while guiding you through the process of building your own sophisticated mapping applications.

Python Geospatial Development Third Edition

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Table of Contents

Python Geospatial Development Third Edition

Credits

About the Author

About the Reviewer

www.PacktPub.com

eBooks, discount offers, and more

Why subscribe?

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 Development Using Python

Python

Python 3

Geospatial development

Applications of geospatial development

Analysing geospatial data

Visualizing geospatial data

Creating a geospatial mash-up

Recent developments

Summary

2. GIS

Core GIS concepts

Location

Distance

Units

Projections

Cylindrical projections

Conic projections

Azimuthal projections

The nature of map projections

Coordinate systems

Datums

Shapes

GIS data formats

Working with GIS data manually

Obtaining the data

Installing GDAL

Installing GDAL on Linux

Installing GDAL on Mac OS X

Installing GDAL on MS Windows

Testing your GDAL installation

Examining the Downloaded Shapefile

Summary

3. Python Libraries for Geospatial Development

Reading and writing geospatial data

GDAL/OGR

Installing GDAL/OGR

Understanding GDAL

GDAL example code

Understanding OGR

OGR example code

GDAL/OGR documentation

Dealing with projections

pyproj

Installing pyproj

Understanding pyproj

Proj

Geod

Example code

Documentation

Analyzing and manipulating Geospatial data

Shapely

Installing Shapely

Understanding Shapely

Shapely example code

Shapely documentation

Visualizing geospatial data

Mapnik

Installing Mapnik

Understanding Mapnik

Mapnik example code

Mapnik documentation

Summary

4. Sources of Geospatial Data

Sources of geospatial data in vector format

OpenStreetMap

The OpenStreetMap data format

Obtaining and using OpenStreetMap data

The OpenStreetMap APIs

Planet.osm

Mirror sites and extracts

Working with OpenStreetMap data

TIGER

The TIGER data format

Obtaining and using TIGER data

Natural Earth

The Natural Earth data format

Obtaining and using Natural Earth vector data

The Global Self-consistent, Hierarchical, High-resolution Geography Database (GSHHG)

The GSHHG data format

Obtaining the GSHHG database

The World Borders Dataset

The World Borders Dataset data format

Obtaining the World Borders Dataset

Sources of geospatial data in raster format

Landsat

The Landsat data format

Obtaining Landsat imagery

Natural Earth

The Natural Earth data format

Obtaining and using Natural Earth raster data

Global Land One-kilometer Base Elevation (GLOBE)

The GLOBE data format

Obtaining and using GLOBE data

The National Elevation Dataset (NED)

The NED data format

Obtaining and using NED data

Sources of other types of geospatial data

The GEOnet Names Server

The GEOnet Names Server data format

Obtaining and using GEOnet Names Server data

The Geographic Names Information System (GNIS)

The GNIS data format

Obtaining and using GNIS data

Choosing your geospatial data source

Summary

5. Working with Geospatial Data in Python

Pre-requisites

Working with geospatial data

Task – calculate the bounding box for each country in the world

Task – calculate the border between Thailand and Myanmar

Task – analyze elevations using a digital elevation map

Changing datums and projections

Task – changing projections to combine shapefiles using geographic and UTM coordinates

Task – changing the datums to allow older and newer TIGER data to be combined

Performing geospatial calculations

Task – identifying parks in or near urban areas

Converting and standardizing units of geometry and distance

Task – calculating the length of the Thai-Myanmar border

Task – finding a point 132.7 kilometers west of Shoshone, California

Exercises

Summary

6. Spatial Databases

Spatially-enabled databases

Spatial indexes

Introducing PostGIS

Installing PostgreSQL

Installing PostGIS

Installing psycopg2

Setting up a database

Creating a Postgres user account

Creating a database

Allowing the user to access the database

Spatially enable the database

Using PostGIS

PostGIS documentation

Advanced PostGIS features

Recommended best practices

Best practice: use the database to keep track of spatial references

Best practice: use the appropriate spatial reference for your data

Option 1: Using GEOGRAPHY fields

Option 2: Transforming features as required

Option 3: Transforming features from the outset

When to use unprojected coordinates

Best practice: avoid on-the-fly transformations within a query

Best practice: don't create geometries within a query

Best practice: use spatial indexes appropriately

Best practice: know the limits of your database's query optimizer

Summary

7. Using Python and Mapnik to Generate Maps

Introducing Mapnik

Creating an example map

Mapnik concepts

Data sources

Shapefile

PostGIS

Gdal

MemoryDatasource

Rules, filters, and styles

Filters

"Else" rules

Styles

Symbolizers

Drawing points

Drawing lines

Drawing polygons

Drawing text

Drawing raster images

Maps and layers

Map rendering

Summary

8. Working with Spatial Data

About DISTAL

Designing and building the database

Downloading and importing the data

The World Borders Dataset

The GSHHG shoreline database

US place names

Non-US place names

Implementing the DISTAL application

The "select country" script

The "select area" script

Calculating the bounding box

Calculating the map's dimensions

Rendering the map image

The "show results" script

Identifying the clicked-on point

Identifying matching place names

Displaying the results

Using DISTAL

Summary

9. Improving the DISTAL Application

Dealing with the anti-meridian line

Dealing with the scale problem

Performance

Finding the problem

Improving performance

Calculating the tiled shorelines

Using the tiled shorelines

Analyzing the performance improvement

Summary

10. Tools for Web-based Geospatial Development

Tools and techniques for geospatial web development

Web applications

A bare-bones approach

Web application stacks

Web application frameworks

User interface libraries

Web services

An example web service

Map rendering using a web service

Tile caching

The "slippy map" stack

Geospatial web protocols

A closer look at three specific tools and techniques

The Tile Map Service protocol

OpenLayers

GeoDjango

Learning Django

GeoDj...

Table of contents

• Python Geospatial Development Third Edition