General information

Open Source Software Tools for Soil Scientists from the California Soil Resource Lab is a fantastic resource for many open source spatial projects, including R, PostGIS, GRASS, QGIS, and more.

Software development

Using the extensibility of QGIS (see below), I have developed several python based ’spatial analysis’ plugins to extend its functionality to include spatial analysis, geoprocessing, geometry manipulation, both spatial and aspatial statistics, as well as general data management tools.

You can go to my  QGIS python plugin page, or go straight to my repository of plugins. If you are using an older versions of QGIS, you should download the plugins from this alternate repository.

Quantum GIS

Quantum GIS (QGIS) is a free, user friendly Open Source Geographic Information System (GIS) that runs on Linux, Unix, Mac OSX, and Windows.  It supports vector, raster, and spatial database formats (e.g. ESRI ShapeFile, geotiff, PostGIS, etc.), and is licensed under the GNU General Public License.

QGIS Features

  • Ability to view and overlay vector and raster data in different formats (PostGIS, most OGR vector formats, all GDAL raster formats, GRASS mapsets, and WMS layers) and projections without conversion to an internal or common format.
  • Ability to create maps and interactively explore spatial data with a friendly graphical user interface.
  • Ability to create, edit, and export spatial data to various different formats.
  • Ability to publish maps on the internet using the export to Mapfile capability (requires a webserver with UMN MapServer installed)
  • Ability to create, edit, and use GRASS layers directly within QGIS, as well as the ability to use most GRASS tools through the GRASS plugin (available as part of the standard QGIS install).
  • Ability to adapt QGIS to specific needs through the extensible plugin architecture, allowing developers to extend the functionality of QGIS through python and C++ plugins. This allows more complex operations such as spatial analysis, geoprocessing functions, data management, as well as coupling QGIS with additional softare, such as R.

R Spatial

Spatial data anlaysis in R is evolving, and there are now a large number of packages that provide spatial statistical methods or interfaces to GIS. The sp package provides classes and methods for spatial data (points, lines, polygons, grids), and is now the ’standard’ package for handeling spatial data, with several other packages (maptools, rgdal, splancs, spgrass6, gstat, spgwr, ..) dependant on it.

R Spatial Resources