Geoscience Reference
In-Depth Information
Chen and Xie (2008) describe the rationale underlying PostGIS* as a library of spatial exten-
sions for the PostgreSQL object-relational database system. Because PostGIS uses the OGC Simple
Features specification for SQL and incorporates the GEOS geometry engine, it makes the underly-
ing database into a powerful spatial data engine and repository, particularly when carefully indexed.
PostGIS 2.0 will offer support for raster data, on which development is continuing actively.
Ter r a L ib is positioned as middleware between a chosen object-relational database system and a
front-end application. It can store and retrieve spatial data, including raster data since its inception,
and apply functions and operations to the data, storing output in the database and passing it to the
front-end application for display (Câmara et al. 2008); it has offered excellent support for research,
exemplified by de Espindola et al. (2011). Its next version, TerraLib 5, will be more tightly integrated
with central OSGeo libraries, will support non-DBMS data sources such as web services and will
permit spatio-temporal data to be represented and queried.
14.3.2 d eSktoP a PPlicationS
The best documented open-source geospatial desktop application appears to be GRASS GIS
(GRASS Development Team 2012). GRASS was already 20 years old when the GRASS develop-
ers collaborated in founding OSGeo, and they have been playing an important role in the broader
OSGeo movement (Neteler et al. 2008). The GRASS book (Neteler and Mitasova 2008) is already
in its third edition, covering the current GRASS 6 release, which is now at 6.4.3, and has advanced
far beyond the topic. From its original shell scripted command-line interface form, GRASS now
has a legacy open-source Tcl/Tk GUI and a modern wxPython GUI using Python as its scripting
language and the wxWidgets open-source cross-platform GUI toolkit. Many of the more recent
developments in GRASS are covered by Neteler et al. (2012). In GRASS 7, Python will replace shell
scripts for scripting, removing the need to emulate Unix in workflows.
Because of its flexibility, GRASS has been customised for very many different platforms;
Sorokine (2007) shows how parallel high-performance visualisation may be made available for
tiled wall displays. Rocchini et al. (2011) customise GRASS to rectify aerial photographs as a
basis for constructing landscape composition indices for tracking climate change. GRASS is used
in compute-intensive research in ecological and environmental studies, such as the simulation of
the management of alien plants by Roura-Pascual et al. (2009) and Krug et al. (2010). Roiz et al.
(2011) analyse the factors potentially driving the invasion of tiger mosquitoes in northern Italy
under climate change scenarios. Finally, GRASS now has a convenient extension mechanism, so
that additional toolsets can be combined with those distributed with the base system; Jasiewicz and
Metz (2011) provide a toolkit for Hortonian analysis of drainage networks. The extension mecha-
nism does not yet support forward-compatibility control checking, so extension authors need to
remember to keep their contributions updated.
The QGIS § desktop application, like open-source Java-based desktop GIS such as gvSIG, uDig**
and OpenJUMP, †† may appear to the user to resemble proprietary desktop GIS. The GUI structure
designs, and in many cases, the names given to menu items, seem aimed to ease the path of the nov-
ice user moving between open-source and proprietary applications. This is also evident in the style
chosen by Sherman (2008) in his book on QGIS, fitting a user guide or manual template rather than
an academic one. Of course, good academic work is done with these systems, such as Robertson
et al. (2009) and Robertson and Farmer (2008), who report on mountain pine beetle infestation in
* http://www.postgis.org.
http://www.terralib.org.
http://grass.osgeo.org/.
§ http://www.qgis.org.
http://www.osgeo.org/gvsig.
** http://udig.refractions.net/.
†† http://www.openjump.org/.
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