Table of Contents for
Python Geospatial Development - Third Edition

Version ebook / Retour

Cover image for bash Cookbook, 2nd Edition Python Geospatial Development - Third Edition by Erik Westra Published by Packt Publishing, 2016
  1. Cover
  2. Table of Contents
  3. Python Geospatial Development Third Edition
  4. Python Geospatial Development Third Edition
  5. Credits
  6. About the Author
  7. About the Reviewer
  8. www.PacktPub.com
  9. Preface
  10. What you need for this book
  11. Who this book is for
  12. Conventions
  13. Reader feedback
  14. Customer support
  15. 1. Geospatial Development Using Python
  16. Geospatial development
  17. Applications of geospatial development
  18. Recent developments
  19. Summary
  20. 2. GIS
  21. GIS data formats
  22. Working with GIS data manually
  23. Summary
  24. 3. Python Libraries for Geospatial Development
  25. Dealing with projections
  26. Analyzing and manipulating Geospatial data
  27. Visualizing geospatial data
  28. Summary
  29. 4. Sources of Geospatial Data
  30. Sources of geospatial data in raster format
  31. Sources of other types of geospatial data
  32. Choosing your geospatial data source
  33. Summary
  34. 5. Working with Geospatial Data in Python
  35. Working with geospatial data
  36. Changing datums and projections
  37. Performing geospatial calculations
  38. Converting and standardizing units of geometry and distance
  39. Exercises
  40. Summary
  41. 6. Spatial Databases
  42. Spatial indexes
  43. Introducing PostGIS
  44. Setting up a database
  45. Using PostGIS
  46. Recommended best practices
  47. Summary
  48. 7. Using Python and Mapnik to Generate Maps
  49. Creating an example map
  50. Mapnik concepts
  51. Summary
  52. 8. Working with Spatial Data
  53. Designing and building the database
  54. Downloading and importing the data
  55. Implementing the DISTAL application
  56. Using DISTAL
  57. Summary
  58. 9. Improving the DISTAL Application
  59. Dealing with the scale problem
  60. Performance
  61. Summary
  62. 10. Tools for Web-based Geospatial Development
  63. A closer look at three specific tools and techniques
  64. Summary
  65. 11. Putting It All Together – a Complete Mapping System
  66. Designing the ShapeEditor
  67. Prerequisites
  68. Setting up the database
  69. Setting up the ShapeEditor project
  70. Defining the ShapeEditor's applications
  71. Creating the shared application
  72. Defining the data models
  73. Playing with the admin system
  74. Summary
  75. 12. ShapeEditor – Importing and Exporting Shapefiles
  76. Importing shapefiles
  77. Exporting shapefiles
  78. Summary
  79. 13. ShapeEditor – Selecting and Editing Features
  80. Editing features
  81. Adding features
  82. Deleting features
  83. Deleting shapefiles
  84. Using the ShapeEditor
  85. Further improvements and enhancements
  86. Summary
  87. Index

Recent developments

A decade ago, geospatial development was vastly more limited than it is today. Professional (and hugely expensive) geographical information systems were the norm for working with and visualizing geospatial data. Open-source tools, where they were available, were obscure and hard to use. What is more, everything ran on the desktop—the concept of working with geospatial data across the Internet was no more than a distant dream.

In 2005, Google released two products that completely changed the face of geospatial development: Google Maps and Google Earth made it possible for anyone with a web browser or desktop computer to view and work with geospatial data. Instead of requiring expert knowledge and years of practice, even a four-year-old could instantly view and manipulate interactive maps of the world.

Google's products are not perfect: the map projections are deliberately simplified, leading to errors and problems with displaying overlays. These products are only free for non-commercial use, and they include almost no ability to perform geospatial analysis. Despite these limitations, they have had a huge effect on the field of geospatial development. People became aware of what is possible, and the use of maps and their underlying geospatial data has become so prevalent that even cellphones now commonly include built-in mapping tools.

The Global Positioning System (GPS) has also had a major influence on geospatial development. Geospatial data for streets and other man-made and natural features used to be an expensive and tightly-controlled resource, often created by scanning aerial photographs and then manually drawing an outline of a street or coastline over the top to digitize the required features. With the advent of cheap and readily-available portable GPS units, as well as phones which have GPS built in, anyone who wishes to can now capture their own geospatial data. Indeed, many people have made a hobby of recording, editing, and improving the accuracy of street and topological data, which is then freely shared across the Internet. All this means that you're not limited to recording your own data or purchasing data from a commercial organization; volunteered information is now often as accurate and useful as commercially-available data, and may well be suitable for your geospatial application.

The open source software movement has also had a major influence on geospatial development. Instead of relying on commercial toolsets, it is now possible to build complex geospatial applications entirely out of freely-available tools and libraries. Because the source code for these tools is often available, developers can improve and extend these toolkits, fixing problems and adding new features for the benefit of everyone. Tools such as PROJ.4, PostGIS, OGR, and GDAL are all excellent geospatial toolkits that are benefactors of the open source movement. We will be making use of all these tools throughout this book.

As well as standalone tools and libraries, a number of geospatial application programming interfaces (APIs) have become available. Google has provided a number of APIs that can be used to include maps and perform limited geospatial analysis within a web site. Other sites, such as the OpenStreetMap geocoder we used earlier, allow you to perform various geospatial tasks that would be difficult to do if you were limited to using your own data and programming resources.

As more and more geospatial data becomes available from an increasing number of sources, and as the number of tools and systems that can work with this data also increases, it has become increasingly important to define standards for geospatial data. The Open Geospatial Consortium (http://www.opengeospatial.org) is an international standards organization that aims to do precisely this: provide a set of standard formats and protocols for sharing and storing geospatial data. These standards, including GML, KML, GeoRSS, WMS, WFS, and WCS, provide a shared language in which geospatial data can be expressed. Tools such as commercial and open source GIS systems, Google Earth, web-based APIs, and specialized geospatial toolkits such as OGR are all able to work with these standards. Indeed, an important aspect of a geospatial toolkit is the ability to understand and translate data between these various formats.

As devices with built-in GPS receivers have become more ubiquitous, it has become possible to record your location data while performing another task. Geolocation, the act of recording your location while you are doing something else, is becoming increasingly common. The Twitter social networking service, for example, now allows you to record and display your current location when you enter a status update. As you approach your office, sophisticated to-do list software can now automatically hide any tasks that can't be done at that location. Your phone can also tell you which of your friends are nearby, and search results can be filtered to only show nearby businesses.

All of this is simply the continuation of a trend that started when GIS systems were housed on mainframe computers and operated by specialists who spent years learning about them. Geospatial data and applications have been "democratized" over the years, making them available in more places, to more people. What was possible only in a large organization can now be done by anyone using a handheld device. As technology continues to improve and tools become more powerful, this trend is sure to continue.