Difference between revisions of "About GRASS"

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(Soil Science)
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===== Archaeology =====
===== Archaeology =====
GIS is of growing importance in this domain. Therefore GRASS has been widely used in archaeology to support the survey of excavation areas or to simulate the behaviour of ancient agents. GRASS has been used to model the most suitable place to conduct a survey \cite{Brandt1992} in the netherlands. Following the assumption that the settlement actions of the ancient people shows regional patterns, locations most suitable for archaeologic sites can be derived. \cite{Lake1998} extented GRASS to automate cumulative viewshed analysis. They also shows how the potential of GIS increase when the software is modified for specific needs. How much archaeological surveys can benefit from the incoorporation of GRASS is shown by \cite{Brandon1999}. \cite{Merlo2005} proposed how a GRASS basedmultidimensional GIS framework for archaeological excavations can be developed.
* Benjamin Ducke
* Mark Lake
===== Biology =====
===== Biology =====

Revision as of 01:33, 13 December 2006

This wiki page is initially for organizing the writing of a GRASS entry for the "Springer Encyclopedia of GIS", in future this wiki page will contain the article itself.

The entry structure

The Structure of the entry is given by springer. I received a .tex file which I fill with the text when this text is reviewd by the community (and my wife because she's an english teacher :-)).



  • Who owns the copyright for the article? Springer? The author(s)?

The Contract says: The author hereby grants and assigns to Springer- Verlag the sole right to publish, distribute and sell... the contribution and parts thereof...

Springer verlag will take ... either in his own name or in that of the author any necessary steps to protect these rights against infringement by third parties. It will have the copyright notice inserted into all editions of the work according to the provisions of the Universal Copyright Convention and dutifully take care of all formalities in this connections, either in its own name or in that of the author.

  • Should the article be wholly original or can it be derived (cut and pasted) from existing GRASS texts (e.g. the GRASS logo; website content)?

I supose we should write something new and shouldn't cut & paste because of the following point.

  • If cut&pasted, does that put the existing GRASS website text etc at risk? (let's avoid a Eric Weisstein's MathWorld vs. CRC Press style nightmare [1])

see above

  • Can we reuse the text? (e.g. publish it here on the wiki or as an article in a future GRASSNews newsletter)

I will ask the people at springer

What needs to be done?

The deadline is something about 'late december, after Christmas'

the entry should be 8-12 pages - here is an example: http://refworks.springer.com/mrw/fileadmin/pdf/GIS/VoronoiEncy

Here is some additional information: http://refworks.springer.com/geograph/

Here are the templates: http://refworks.springer.com/geograph/

And here is a list of other entries (as of 2006-11-21) http://www.carto.net/neumann/temp/gis_encyclopedia_toc.pdf

The Entry

  • screenshots needed? if so, how many?
  • no limit, but I think we shouldn't include more than 3
  • I would suggest some screenshots with 3d vector and 3d raster




Malte Halbey-Martin, Inst. of Geogr. Sciences, Free University Berlin, Germany

Please put your name here when you have written something


Geographic Resources Analysis Support Software, GRASS- GIS (Geographic Information System)

Definition (fewer than 250 words)

GRASS- GIS (Geographic Resources Analysis Support Software) is a GIS- software for geospatial analyses and modelling which has the capability to manage raster and vectordata. Additionally it supports three dimensional modelling with 3D raster voxel or 3D vector data and contains several image processing modules to manipulate remote sensing data. It comes along with visualization tools and interacts with other related software packages e. g. R- language, gstat and Quantum GIS. GRASS supports a variety of GIS formats due to the usage of the GDAL/OGR library. It also supports the OGC- conformal Simple Features.It can connect to databases via ODBC and supports spatial databases like PostGIS. GRASS datasets can be published on the internet with the UMN Mapserver.

The software is published under the conditions of the GNU General Public Licence (GPL) so anyone can see the source code, the internal structure of the program and the algorithms which are used. Every user can improve, modify, or extend GRASS for his own needs. A striking advantage of the program is that no licence fees have to be paid because of the terms of the GPL. Programmers all over the world contribute to the software. It is one of the biggest Open Source projects in the world (more than one million lines of source code). GRASS runs on a variety of platforms like GNU/Linux, MS- Windows, MacOS X and POSIX compliant systems. It is completly written in C although a Java version also exist (JGRASS).

Historical Background (fewer than 500 words)

The history of GRASS reaches back until the early eighties. Initially GRASS was developed by the U.S. Army Construction Engineering Research Laboratory (CERL), Champaign, Illinois since 1982 due to the need of new landmanagement and environmental planing tools for military installations. The emphasis was taken on raster analyses and image processing, because the aim of the analyses were the estimatation of the impact of actions on continous surfaces like elevation or soils(Neteler & Mitasova 2004) and there were no adequate raster GIS software on the market at that time. Modules for vector processing were added later.

The first version of GRASS was released in 1984 (Vanderfelt 1994). The source code was completely published on the Internet during the late eighties which brought a significant input into the development of GRASS. The CERL withdrew from GRASS development in 1995. An international developer team overtook this task and in 1997 GRASS 4.2 was published by the Baylor University, Waco Texas, USA and GRASS 4.2.1 from the Institute of Physical Geography and Landscape Ecology, University of Hannover, Germany in 1999 under the terms of the GPL. In 1999 the work at version 5.0 were started and the headquarter of the "GRASS Developer Team" moved to the Instituto Trentino di Cultura (ITC-irst), Trento, Italy. GRASS 5.0 was released in 2002, version 6.0 in March 2005. The current stable version is 6.2 which was released at the end of October 2006 (http://grass.itc.it/devel/grasshist.html).

Tabelle Vanderfelt 1994???

maybe we should add some mayor steps of the development...

see GRASS history page: http://grass.itc.it/devel/grasshist.html

Scientific fundamentals

Philosophy of GRASS

The most distinguishing feature of GRASS in comparison to other GIS- software is that the source code can be explored without any restrictions so everyone can study the algorithms which are used. This open structure allows everybody to contribute to the source code to improve GRASS or to extend it for his own needs. For this purpose GRASS provides a GIS- library and a free Programming Manual, which can be downloaded from the GRASS- project site (www.grass-irc.it). Therefore the user has full control of the analyses he does. Besides this point the GPL protects the contributing people of using their code in proprietary software where no free access to the source code is granted. Following the terms of the GPL all code which is based on GPL licensed code must be published again under the GPL (cite GPL?).

GRASS offers the user the whole range of GIS functions and together with other (free) software tools it provides a complete and powerful GIS software infrastructure for low costs.

Programming and extending GRASS

I wonder if I'm the right person to write that because of the lack of programming skills

GRASS is written in C and comes along with a sophisticated and well documented C / C++ API (Cite Programming Manual). As a side effect of the open source philosophy the user has the ability to learn how to develope own applications from existing modules by exploring their source code.

Besides that options GRASS owns the possibility to call the functions already implememented in GRASS with high level programming languages like Python. For that purpose a GRASS-SWIG interface is available which translates ANSI C / C++ declarations into multiple languages (Python, Perl). It contains also an integrated parser for scripting languages.

For easy creation of GRASS extensions it comes along with a extension manager so no source code is needed to build additional GRASS modules. To automate repeating tasks in GRASS shell scripts can be written.

Interoperability: GIS and Analysis Toolchain

GRASS is designed the way that it offers a highly and robust interoperability with outside applications, giving the user tremendous flexibility and efficiency for accomplishing analyses.

Relational Database Systems

GRASS can directly connect to relational database management systems (RDBMS) like SQlite, MySQL and PostgreSQL. It even supports PostGIS, the spatial extension of PostgreSQL. To other external RDBMS GRASS offers the connection via the ODBC driver (cite GRASS Manual). A way to connect to an Oracle (? / Spatial ?) database is described by Mitasova, Neteler & Holl (http://www.oracle.com/technology/pub/articles/mitasova-grass.html).

  • Oracle (there is no direct Oracle driver in GRASS)

I thought it would be important for GIS users to know, that there's the possibility to connect to oracle... is this accomplished through GDAL ? when I got it right from the article above one has to compile GDAL/ogr from source with OCI bindings...

Statistical Analysis

For statistic analyses of geodatasets R (a statistic environment, further explanation see www.r-project.org) can be called within a GRASS session. Another software to perform geostatic procedures is gstat. For both software packages GRASS interfaces exist. Therefore gstat and R can directly use GRASS raster- and vector datasets and will do their calculations in the spatial region definied in GRASS. This combination offers a high potential for geostatistic analysis as shown by Bivand (2000) and Bivand & Neteler (2000). GRASS can import and export Matlab binary (.mat) files (version 4) for processing numeric calculations outside GRASS.

Interoperability with other GIS Software

GRASS supports nearly all common GIS file formats to allow the user to use other GIS applications or external datasources because of its binding to the GDAL/OGR library and the support of the OGC Simple Features. Therefore the data excange between various applications and between several user is easy. The database (clarify differences between RDBMS) structure implemented in GRASS, coupled with UNIX-style permissions and file locks, allows concurrant access to any given project. In this way, several individuals can share the resources of a single machine and dataset. GRASS works closly together with Quantum GIS. GRASS modules are accessible through a GRASS plugin in Quantum GIS.

2D and 3D Visualization

While GRASS comes with fully functional 2D cartography and 3D visualization software (NVIZ), it interacts with other software tools to produce maps or to visualize geographic data sets. GRASS contains exportfilter for Generic Mapping Tool (GMT) files and various image formats so maps can be generated with external image manipulating programs.

For 3D visualization of 3D vector and raster datasets GRASS can export them in VTK (Visualization ToolKit) files which can be viewed in Paraview and script files for Povray, a raytracer to design 3D graphics. Aditional VRML (Virtual Reality Modeling Language) files can be created. Animations can be build with NVIZ or the external programs mentioned above.

Web Mapping

The UMN Mapserver can connect to GRASS and can read GRASS geodatasets directly. With the help of PyWPS (Python Web Processing Service, an implementation of the Web Processing Service standard from the Open Geospatial Consortium) GRASS modules are accessible via web interfaces easily. Thereby GRASS can serve as a backbone in WebGIS applications.

Key applications

GRASS is currently used around the world in academic and commercial settings as well as by many govermental agencies and environmental consulting companies. Due to the variety of spatial data and application fields this selection just gives an overview of applications where GRASS was adopted.


GIS is of growing importance in this domain. Therefore GRASS has been widely used in archaeology to support the survey of excavation areas or to simulate the behaviour of ancient agents. GRASS has been used to model the most suitable place to conduct a survey \cite{Brandt1992} in the netherlands. Following the assumption that the settlement actions of the ancient people shows regional patterns, locations most suitable for archaeologic sites can be derived. \cite{Lake1998} extented GRASS to automate cumulative viewshed analysis. They also shows how the potential of GIS increase when the software is modified for specific needs. How much archaeological surveys can benefit from the incoorporation of GRASS is shown by \cite{Brandon1999}. \cite{Merlo2005} proposed how a GRASS basedmultidimensional GIS framework for archaeological excavations can be developed.


Tucker et al (1997) used GRASS to model the bird distribution of three bird species in north-east England using a Bayesian rule-based approach. They linked data about habitat preferences and life-histry of the birds against physiogeographic and satellite data using GRASS.

For the Iberian Peninsula Garzon et al 2006 have used GRASS to model the potential area of Pinus Sylvestris. They predict the habitat suitability with a machine learning software suite in GRASS GIS. They incorporated three machine learning technics (Tree-based Classification, Neural Networks and Random Forest). All three models show a larger potential area of P. sylvestris as the present one. In the Rocky Mountains National Park tree population parameters have been modeled by Baker et al 1997 for the forest-tundra ecotone.

Environmental Modelling
Geography (Human / Physical)
Geology / Planetary Geology

Kajiyama et al 2004 and Masumoto et al used GRASS to derive 3D geological models in Japan. Kajiyama et al used a Digital elevation model (DEM) and a logical model of the geological structure to derive the surface boundaries of each geologic structure in the study area. From these data they built a 3D geological model.

GRASS has been also used in planetary geology. Frigeri et al identified Wrinkle Ridges on Mars which can be an evidence of existing subsurface ice on the planet. They used Mars MGS and data from the Viking Mission. The mapping of geologic features from Mars data is done by Deuchler et al (2004). The ability to import the raw data from various Mars datasets and to reproject them in easy way is seen as a great benefit by the authors of this survey. The authors detected tectonic surface faults and assigned them to a geologic Mars region.

Geomorphology \ Geomorphometry
  • Analysis of mountainous terrain (Carlos Henrique Grohmann Computers & Geosciences, 30 (9-10):1055-1067)
  • Landscape / landform classification (Bivand, R. Integrating GRASS 5.0 and R: GIS and modern statistics Computers & Geosciences, 2000, 26, 1043–1052.)
  • gstat
  • R (see article in GRASS Newsletter vol 3)
Hydrologic Modelling
Hydrographic Surveys (nautical)
Landscape epidemiology and public health
Network analysis
Precision Farming
  • Haverland
  • Goddard et al
Remote Sensing
Soil Science
  • Three-dimensional Rule-based Continuous Soil Modelling (Martin Ameskamp PhD thesis)
  • Landscape scale modeling of soil properties (Dylan Beaudette [in progress])
  • Numerical evaluation of aspect effect with r.sun (Dylan Beaudette [in progress])

Future directions

The development of GRASS as a native Windows application and the building of a new unified Graphical User Interface for Linux, Mac, Windows and Unix using WxWidgets and Python will certainly rise the distribution of the program. The prototype code is already working. Its advantages in modelling, price and extending makes GRASS a strong alternative to other GIS software. The increasing popularity will lead into an increasing development of the software. More people will contribute to the source code, bugtracking and documentation. GRASS has some innovative functions already implemented (e. g. functions for network analysis like shortest path, route planing), waiting for new applications to be developed on top. For 3D modelling the infrastructure and moduls are in place for raster, vector and site data leading to an increasing usage in spatial modelling.

Cross References

1. Quantum GIS ?

2. PostGIS?

3. UMN Map Server ?

4. Open GIS Consortium

Recommended Reading (5 - 15 entries)

  • Neteler, M. & Mitasova, H. (2004): Open Source GIS: A Grass GIS Approach. 2nd Edition. Boston.
    (of course)
  • GRASS Newsletters [2]
  • Lo, C.P. & Yeung, A.K.W. Concepts and Techniques of Geographic Information Systems Prentice Hall, 2006
  • Robinson, A.H.; Morrison, J.L.; Muehrcke, P.C. & Guptil, S.C. Elements of Cartography John Wiley and Sons, 1995
  • Haverland, G. (1999): Precision Farming and Linux: An Expose. Linux Journal.

Aditional definitions

If there are some definition in our text which would be worse mentioned in the Encyclopaedia...

Contact & Coordination

Malte Halbey-Martin
Free University Berlin
Dept. of Geosciences
Inst. of Geogr. Sciences
Malteserstr. 74-100
D-12249 Berlin, Germany
tel: +49.30.83870409
fax: +49.30.83870755
email: malte at geog.fu-berlin.de
online: www.geog.fu-berlin.de/~malte

Springer contact

Jennifer Carlson / Andrea Schmidt
Development Editors
233 Spring Street
New York, NY 10016
tel: 212.460.1666
fax: 212.460.1594
email: jennifer.carlson at springer.com
online: www.springer.com
Andreas Neumann <neumann at karto.baug.ethz.ch>
Institute of Cartography
ETH Zurich
Wolfgang-Paulistrasse 15
CH-8093  Zurich, Switzerland

Phone: ++41-44-633 3031, Fax: ++41-44-633 1153
e-mail: neumann at karto.baug.ethz.ch
www: http://www.carto.net/neumann/
SVG.Open: http://www.svgopen.org/
Carto.net: http://www.carto.net/