Announcing an opportunity to learn about the leading edge free and open-source technologies for desktop and web-based mapping and data analysis. This is a two day Masterclass focusing on introducing participants to the wonderful world of open source geospatial software. Check out the announcement from the Postgraduate Statistics Centre at Lancaster University.
- Fri 25 September 2009 cfarmer
Journal of Spatial Information Science
Thu 10 September 2009 cfarmerCheck out the Journal of Spatial Information Science, a new, peer-reviewed, open-access journal with a range of well established geospatial academics on the editorial board.
FOSS4G and teaching GIS
Mon 20 July 2009 cfarmerTwo quicks notes to share:
Firstly, please check out this excellent introduction to GIS by Tim Sutton, Otto Dassau, and Marcelle Sutton in partnership with the Chief Directorate for Spatial Planning & Information, Department of Land Affairs, Eastern Cape, South Africa, and the Spatial Information Management Unit, Office of the Premier, Eastern Cape, South Africa. They use QGIS to present some basic GIS concepts and skills, and I particularly like their section on Coordinate Reference Systems.
Secondly, don’t forget to checkout the FOSS4G 2009 Free and open source software for geospatial conference in Sydney in October. There will be loads ...
Open up your online maps with OpenStreetMap
Mon 26 January 2009 cfarmerOpenStreetMap (OSM) is a project designed to create and provide free spatial data (street maps) to anyone and everyone who wants them. It is based on an open-source philosophy, and combines wiki-like user generated data, with free access, allowing users to create, edit, download, and use OSM data to their hearts content. According to the OSM website, “the project was started because most maps you think of as free actually have legal or technical restrictions on their use, holding back people from using them in creative, productive or unexpected ways.” There are now tones of websites and open-source software projects that incorporate OSM data, and the growing popularity of the site means that the data is only going to get better (more accurate) and bigger (more data).
Understanding spatial reference systems
Mon 12 January 2009 cfarmerFor those of you who are still unclear about what exactly a spatial reference system is, how it is used, and what it means for your data, I found a pretty good quick guide to spatial references, coordinate systems, projections, datums and ellipsoids. This article was written by Morten Nielsen (who works for ESRI), and it does a good job of quickly and simply describing what makes up a spatial reference system, and some of the errors that people make when talking about their spatial data.
Having a good grasp of this stuff is important when working with spatial data ...
Quick guide to setting up a PostGIS database
Fri 28 November 2008 cfarmerRecently I decided to seriously start using PostGIS to manage my spatial data. As I have several projects on the go, organizing and managing my data effectively has become extremely important, and PostGIS is by far the most convenient way to do this. There is lots of documentation out there that explains in detail how to set up PostGIS, but by far the best reference I’ve found is from Tim Sutton’s blog, mainly because he uses Ubuntu, and sudo-apt gets everything you need to have PostGIS working in minutes.
View spatial data attribute tables in R
Tue 14 October 2008 cfarmerMany GIS offer the ability to view the attribute table of a vector layer. While this is perhaps less obvious in the R environment, it is not impossible. The following command allows you to visually inspect, and change any data.frame (or other vector, matrix, etc.), including Spatial*DataFrames.
R spatial indentify tool
Tue 23 September 2008 cfarmerThis is useful for visually exploring R spatial data such as
SpatialPointDataFrames
orSpatialGridDataFrames
. By clicking on various features, the value at that point will be displayed.library(rgdal) y = readGDAL(system.file("pictures/Rlogo.jpg", package="rgdal")[1], band=1) y.grid = y@grid y.coords = coordinates(y.grid) image(y) identify(x=y.coords, y=NULL, n=1)
where
x
andy
refer to coordinates (in this case becausey.coords
contains bothx
andy
coordinates,y
can be set toNULL
), andn
is the number of features to identify.