Learning Geospatial Analysis with Python

Joel Lawhead

• Publisher: Packt Publishing
• Year: 2013
• eBook ISBN: 9781783281138
• Topic: Technology & Engineering
• Subtopic: Computer Science General
• Index: Technology & Engineering

In Detail

Geospatial analysis is used in almost every field you can think of from medicine, to defense, to farming. It is an approach to use statistical analysis and other informational engineering to data which has a geographical or geospatial aspect. And this typically involves applications capable of geospatial display and processing to get a compiled and useful data.

"Learning Geospatial Analysis with Python" uses the expressive and powerful Python programming language to guide you through geographic information systems, remote sensing, topography, and more. It explains how to use a framework in order to approach Geospatial analysis effectively, but on your own terms.

"Learning Geospatial Analysis with Python" starts with a background of the field, a survey of the techniques and technology used, and then splits the field into its component speciality areas: GIS, remote sensing, elevation data, advanced modelling, and real-time data.

This book will teach you everything there is to know, from using a particular software package or API to using generic algorithms that can be applied to Geospatial analysis. This book focuses on pure Python whenever possible to minimize compiling platform-dependent binaries, so that you dont become bogged down in just getting ready to do analysis.

"Learning Geospatial Analysis with Python" will round out your technical library with handy recipes and a good understanding of a field that supplements many a modern day human endeavors.

Approach

This is a tutorial-style book that helps you to perform Geospatial and GIS analysis with Python and its tools/libraries. This book will first introduce various Python-related tools/packages in the initial chapters before moving towards practical usage, examples, and implementation in specialized kinds of Geospatial data analysis.

Who this book is for

This book is for anyone who wants to understand digital mapping and analysis and who uses Python or another scripting language for automation or crunching data manually.This book primarily targets Python developers, researchers, and analysts who want to perform Geospatial, modeling, and GIS analysis with Python.

Learning Geospatial Analysis with Python

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Table of Contents

Learning Geospatial Analysis with Python

Credits

About the Author

About the Reviewers

www.PacktPub.com

Support files, eBooks, discount offers and more

Why Subscribe?

Free Access for Packt account holders

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. Learning Geospatial Analysis with Python

Geospatial analysis and our world

Beyond politics

History of geospatial analysis

Geographic Information Systems

Remote sensing

Elevation data

Computer-aided drafting

Geospatial analysis and computer programming

Object-oriented programming for geospatial analysis

Importance of geospatial analysis

Geographic Information System concepts

Thematic maps

Spatial databases

Spatial indexing

Metadata

Map projections

Rendering

Raster data concepts

Images as data

Remote sensing and color

Common vector GIS concepts

Data structures

Buffer

Dissolve

Generalize

Intersection

Merge

Point in polygon

Union

Join

Geospatial rules about polygons

Common raster data concepts

Band math

Change detection

Histogram

Feature extraction

Supervised classification

Unsupervised classification

Creating the simplest possible Python GIS

Getting started with Python

Building SimpleGIS

Summary

2. Geospatial Data

Data structures

Common traits

Geo-location

Subject information

Spatial indexing

Indexing algorithms

Quad-Tree index

R-Tree index

Grids

Overviews

Metadata

File structure

Vector data

Shapefiles

CAD files

Tag and markup-based formats

GeoJSON

Raster data

TIFF files

JPEG, GIF, BMP, and PNG

Compressed formats

ASCII GRIDS

World files

Point cloud data

Summary

3. The Geospatial Technology Landscape

Data access

GDAL

OGR

Computational geometry

PROJ.4

CGAL

JTS

GEOS

PostGIS

Other spatially-enabled databases

Oracle spatial and graph

ArcSDE

Microsoft SQL Server

MySQL

SpatiaLite

Routing

Esri Network Analyst and Spatial Analyst

pgRouting

Desktop tools

Quantum GIS

OpenEV

GRASS GIS

uDig

gvSIG

OpenJUMP

Google Earth

NASA World Wind

ArcGIS

Metadata management

GeoNetwork

CatMDEdit

Summary

4. Geospatial Python Toolbox

Installing third-party Python modules

Installing GDAL

Windows

Linux

Mac OS X

Python networking libraries for acquiring data

Python urllib module

FTP

ZIP and TAR files

Python markup and tag-based parsers

The minidom module

ElementTree

Building XML

WKT

Python JSON libraries

json module

geojson module

OGR

PyShp

dbfpy

Shapely

GDAL

NumPy

PIL

PNGCanvas

PyFPDF

Spectral Python

Summary

5. Python and Geographic Information Systems

Measuring distance

Pythagorean theorem

Haversine formula

Vincenty formula

Coordinate conversion

Reprojection

Editing shapefiles

Accessing the shapefile

Reading shapefile attributes

Reading shapefile geometry

Changing a shapefile

Adding fields

Merging shapefiles

Splitting shapefiles

Subsetting spatially

Performing selections

Point in polygon formula

Attribute selections

Creating images for visualization

Dot density calculations

Choropleth maps

Using spreadsheets

Using GPS data

Summary

6. Python and Remote Sensing

Swapping image bands

Creating histograms

Performing a histogram stretch

Clipping images

Classifying images

Extracting features from images

Change detection

Summary

7. Python and Elevation Data

ASCII Grid files

Reading grids

Writing grids

Creating a shaded relief

Creating elevation contours

Working with LIDAR

Creating a grid from LIDAR

Using PIL to visualize LIDAR

Creating a Triangulated Irregular Network (TIN)

Summary

8. Advanced Geospatial Python Modelling

Creating an NDVI

Setting up the framework

Loading the data

Rasterizing the shapefile

Clipping the bands

Using the NDVI formula

Classifying the NDVI

Additional functions

Loading the NDVI

Creating classes

Creating a flood inundation model

The flood fill function

Making a flood

Least cost path analysis

Setting up the test grid

The simple A* algorithm

Generating the test path

Viewing the test output

The real-world example

Loading the grid

Defining the helper functions

The real-world A* algorithm

Generating a real-world path

Summary

9. Real-Time Data

Tracking vehicles

Nextbus agency list

Nextbus route list

Nextbus vehicle locations

Mapping Nextbus locations

Storm chasing

Summary

10. Putting It All Together

A typical GPS report

Working with GPX-Reporter.py

Stepping through the program

Initial setup

Working with utility functions

Parsing the GPX

Getting the bounding box

Downloading OpenStreetMap images

Creating the hillshade

Creating maps

Measuring elevation

Measuring distance

Retrieving weather data

Summary

Index

Learning Geospatial Analysis with Python

Copyright © 2013 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: October 2013

Production Reference: 1181013

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78328-113-8

www.packtpub.com

Cover Image by Jarek Blaminsky (<[email protected]>)

Credits

Author

Joel Lawhead

Reviewers

Jorge Samuel Mendes de Jesus

Athanasios Tom Kralidis

Alessandro Pasotti

Acquisition Editor

Joanne Fitzpatrick

Lead Technical Editor

Balaji Naidu

Technical Editors

Pooja Arondekar

Anita Nayak

Anusri Ramchandran

Project Coordinator

Angel Jathanna

Proofreader

Bernadette Watkins

Indexer

Hemangini Bari

Graphics

Abhinash Sahu

Production Coordinator

Shantanu Zagade

Cover Work

Shantanu Zagade

About the Author

Joel Lawhead is a PMI-certified Project Management Professional (PMP) and the Chief Information Officer (CIO) for NVisionSolutions.com, an award-winning firm specializing in geospatial technology integration and sensor engineering.

He began using Python in 1997 and began combining it with geospatial software development in 2000. He has been published in two editions of the Python Cookbook by O'Reilly. He is also the developer of the widely used open source Python Shapefile Library (PyShp) and maintains the geospatial technical blog GeospatialPython.com and Twitter feed @SpatialPython discussing the use of the Python programming language within the geospatial industry.

In 2011, he reverse engineered and published the undocumented shapefile spatial indexing format and assisted fellow geospatial Python developer, Marc Pfister, in reversing the algorithm used, allowing developers around the world to create better-integrated and more robust geospatial applications involving shapefiles.

He has serv...

Table of contents

• Learning Geospatial Analysis with Python