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Open Source geocomputation: using the R data
analysis language integrated with GRASS GIS and
PostgreSQL data base systems.
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of Economics and Business
Administration, Breiviksveien 40, N-5045 Bergen, Norway
E-mail: Roger.Bivand@nhh.no
Markus Neteler
Institute of Physical Geography and Landscape Ecology, University of Hannover, Schneiderberg 50,
D-30167 Hannover, Germany
E-mail: neteler@geog.uni-hannover.de
Abstract
We report on work in progress on the integration of the GRASS GIS, the R data analysis programming
language and environment, and the PostgreSQL database system. All of these components are released under
Open Source licenses. This means that application programming interfaces are documented both in source
code and in other materials, simplifying insight into the workings of the respective systems. Current versions
of this note and accompanying code are to be found at the Hannover GRASS site, together with earlier papers
on related topics.
Open Source geocomputation
Open Source geocomputation: using the R data analysis language integrated with GRASS GIS and PostgreSQL data base systems.1

1 Introduction
The practice of geocomputation is evolving to take advantage of the peer-review qualities brought to software
development by access to source code. The progress reported on in this paper covers recent advances in the
GRASS geographical information system, in particular the introduction of floating point raster cell values and
an enhanced sites data format, in the R data analysis language environment, and in their interfacing both
directly and through the PostgreSQL data base system.
The interactive R language - a dialect of S (Chambers 1998) - is eminently extensible, providing both for
functions written by users, for the dynamic loading of compiled code into user functions, and the packaging of
libraries of such functions for release to others. R, unlike S-PLUS, another dialect of S, conducts all
computation in memory, presenting a potential difficulty for analysis of very large data sets. One way to
overcome this is to utilize a proxy mechanism through an external data base system, such as PostgreSQL;
others will be forthcoming as the Omega project matures.
While R is a general data analysis environment, it has been extensively used for modelling and simulation,
and for comparison of modern statistical classification methods with for example neural nets, and is well
suited to assist in unlocking the potential of data held in GIS. Over and above classical, graphical, and modern
statistical techniques in the base R library and supplementary packages, packages for point pattern analysis,
geostatistics, exploratory spatial data analysis and spatial econometrics are available. The paper is illustrated
with worked examples showing how open source software development can benefit geocomputation. Previous
work on the use of R with spatial data is reported by Bivand and Gebhardt (forthcoming), and on interfacing R
and GRASS by Bivand (1999, 2000).
2 Open Source Development and GeoComputation
One of the most striking innovations to emerge with full vigour in the late 1990’s, but building on earlier
precedent, is Open Source software. While there are good technical reasons for releasing the source code of
computer programs to anyone connected to the Internet, or willing to spend little more than the cost of a bottle
of beer on a CDROM, the trend profoundly affects the measurement of research and technological
development expenditure and investment. Since the software tools are not priced, knowledge, the practice of
winning new knowledge, and the style in which new knowledge is won are sharply focused.
This style is of key importance, and involves the honing of ideas in open collaboration and competition
between at least moderately altruistic peers. The prime examples are the conception of the world wide web
and its fundamental protocols at CERN, by an errant scientist simply interested in sharing research results in
an open and seamless way, the transport mechanism for about 80% of all electronic mail sendmail - written
from California but now with a world cast of thousands of contributors, and the Linux operating system,
developed by a Finnish student of undoubted organisational talent, but - perhaps luckily - no training in the
commercialisation of innovations, nor in business strategy.
For these innovators, it has been important not to be hindered by institutional barriers and hierarchies.
Acceptance and esteem in Open Source communities is grounded in the quality of contributions and
interventions made by individuals in a completely flat structure. Asking the right question leading to a
perverse bug being identified or solved immediately confers great honour on the person making the
contribution. In money terms, probably no commercial organisation could afford to employ problem chasers
or consultants to solve such problems - they are simply too costly. The entry into the value chain is later, in
the customisation, packaging and reselling of software, in software services rather than in the production and
sale of software itself.
Open Source geocomputation
1 Introduction 2