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THE POTENTIAL USES OF QGIS-GRASS IN TOWN AND COUNTRY PLANNING by Abbas Abdul Wahab Federal Department of Town and Country Planning Peninsular Malaysia 1.0

INTRODUCTION QGIS1 is being promoted by the Federal Department of Town and Country Planning, Peninsular Malaysia since 20092 and 20103 as a suitable desktop Geographical Information System (GIS) for adoption by all government agencies. If exploited to the hilt, it will be an enormous saving for the government in terms of millions ringgits since proprietary GIS are not cheap. The hallmark of this multi-platform software is its user-friendliness 4 making it easy to use in a subject as complex as GIS. Meanwhile, the established GRASS 5 software is well known for its wide range of analytical commands and since both QGIS and GRASS are open source, a QGIS-GRASS concept equals the best of both worlds: a marriage between the slick, user-friendly QGIS with the mature analytical comprehensiveness of GRASS.


USES JPBD found that to optimize the QGIS-GRASS package, it is best to use each software for what they excel in: QGIS as the mapping tool and GRASS as the analytical tool. When used as a package, QGIS plays the role of the interface. This is not to say that users should jump straight into the QGIS-GRASS package. Why? Firstly, there are already 124 plugins6 for QGIS Ver. 1.7 some requiring less procedure. Roma01047 stated that “The Road Graph plugin is 10 steps shorter and less cryptic then messing with GRASS to get similar results.” Secondly, potential uses in the field of town and country planning with QGIS alone are many including though not limited to:           

The development of a town planning colour tempate for .tab and .shp file; The preparation of landuse and zoning maps; The distribution of public open space; The distribution of fire hydrants; The distribution of schools by adminstrative boundary and unique value; The response time catchment area for existing and propose fire stations; Comparative site and hinterland analysis integrating aerial photo by Georeferencing. The integration of development plans on a macro scale using Google Mercator projection; The monitoring of conformity between zoning and existing landuse maps; The filtering of attributes by SQL query; The intersect of maps, filter and sub-filter of attributes by geoprocessing tools and SQL query; and

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Acronym for Quantum GIS Malaysian Government Open Source Software Conference (MyGOSSCON), Putrajaya, 2009 4th National GIS Conference & Exhibition, NRE, Putrajaya, 28 Jun 2010


Mesyuarat perbincangan data digital pewartaan tanah lapang awam, Bhg. Penyelidikan dan Pembangunan, Kuala Lumpur, 8 Julai 2011; Acronym for Geographic Resources Analysis Support System (GRASS GIS) QGIS homepage

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The integration of spatial and non-spatial data by data management tools;

Thirdly, working with GRASS requires native files to be imported into a GRASS format. At first, this may be seen as a hassle however it really a non-issue because it actually improves analytical performance once all attributes are automatically indexed. Thus when the use of QGIS is facing its threshold limits, partnership with GRASS modules is recommended. In fact, the sophistication and flexibity of QGIS as an analytical geospatial tool is greatly enhanced when GRASS commands are accessable by QGIS. Both QGIS and GRASS work seamlessly together and there are over than 400 GRASS commands 8 to choose from the curent stable GRASS GIS Ver 6.4.2. This will surely make the QGIS-GRASS package a powerful GIS setup to reckon with. GRASS modules cover:          

File management; Regional setting; Projection management; Raster; Vector; Imagery; Database; 3-d Visualization; Postscript; and Miscellaneous command.

A point in favour of the QGIS-GRASS package is that GRASS commands not only are many but also come in a wide variety of specialization. Town planning too, being a multi-disciplinary field is dependent on a wide range of modules to cover its scope, thus, the QGIS-GRASS package should be a good GIS tool for town planning. Another point in favour of GRASS commands is that it allows the user to customize value inputs over the default value inputs which may be adequate for non-critical cases but inadequate when range classficiation requires unequal values9 e.g. JPBD slope gradient classification. This flexibility makes the QGIS-GRASS package adaptable to different user requirements. This capability helped JPBD realize a site suitability analytical solution for hilly areas and highlands through interpolation, slope and elevation analysis, user define inputs and terrain parameters. A strong point supporting the QGIS-GRASS package is GRASS's many cleaning topology commands and the ability to process quickly, for example, a case study involving a Johore Bahru district local plan landuse map with 25,000+ gaps was auto-cleaned in about 3 minutes and cross-check inspections with ArcGIS confirmed topology errors were rectified. However, the question of how accurate GRASS auto-cleaning is could not be ascertained as that dissection was not clear. Then again, the same could probably be said of auto-cleaning techiques by other GIS software. A solution would be to carry out a 10% random sampling to assess the viability of the a GIS software's capability. Although 3 statistics plugins are available in QGIS, it is modest when compared to the 7 existing GRASS vector and raster commands. This is an area where the QGIS-GRASS package has a strong advantage because the scope of statistical analysis now widens and that does not even include supporting GRASS commands which may have indirectly bearing. As research and development (R&D) on the QGIS-GRASS package by JPBD has been recent, there is still much unexplored terittory. The ability for QGIS Ver 1.7 to import secondary geospatial data by OpenMapLayers (e.g. Google Physical, Google Hybrid, Google Satellite) and even download geospatial features by OpenStreetMap must be highly commended because this appears only available in the latest proprietary GIS e.g. Mapinfo Ver 10.4. It is hoped that further research will shed light on how the QGIS-GRASS package can capitalize this asset. JPBD has suggested to the cyber QGIS community that geospatial 8

GRASS GIS homepage


Mesyuarat penyelarasan Garispanduan Kawasan Berbukit dan Tanah Tinggi, eKawalselia dan QGIS slope analysis plugin, Ibu Pejabat JPBD, Kuala Lumpur, 11 Julai 2011;


data acquisition be extended to include Wikimapia and has already been acknowledged “as a great idea”10. It highlights that R&D is a continous process and solutions are only limited by the creativity of the mind. 4.0

ISSUES The decision to go for the QGIS-GRASS package is a step in the right move as it appears that basic GIS software irrespective of marque offers basic features which eventually become a hinderance when user needs become more demanding. This decision also marks the move by JPBD to enter uncharted territory but with no basic training in GRASS neither having a solid comprehension of GRASS commands. However, the deeper the research, the more it became clear that use of the QGIS-GRASS package does not require dependency on a system analyst or programmer to successfully run GRASS commands. What is really needed are lots of common sense, simple logic, a large dosage of comittment, many trial and errors and much heavy discussions to brainstorm how to go about getting things done. Early R&D produced fruitful results and were shown to the top management where subsequently the directive was to strive on in the hope that knowledge gained can be extended later to assist many local planning authorities whom are not technically well verse with GIS mapping and analytical techniques as well as may need future assistance in open source GIS to overcome their tight budget. R&D on QGIS and GRASS also has its issue. For starters, the general interest and support in this specialized field is not so enthuastic. Then, there was also no technical expert to advise in the use of QGIS-GRASS package so progress is much the initiative of the study team of two. Next, as the Open Source community actively discuss matters of concern at their respective forum and Mailing-List, hence, there is a need to seek guidance through Google search and be a forumer too. Forthly, a a good command of English Language does a lot to make it easier to go by as English is the main medium of communication on the Internet. Lastly, a strong comprehension of mathematical logic is important to appreciate the beauty of GIS and the spark of creativity is needed to help problem solving. But what happens when things (analytical results) go wrong? Will people quickly put the blame on the QGIS-GRASS package. The reality is that, more often than not, things go wrong due to:     

Topology error e.g. gaps, overlaps, breaks, overshoot and undershoots; Attribute error e.g. did not follow JPBD GIS Manual on landuse classification, landuse colour code, database structure and metadata; Human error e.g. typo error, blanks; overlooked cases; Prerequisite values were not provided; Inconclusive parameters.

In the first place, spatial data should not even be value-added with new inputs until topology errors have been cleaned and verified failing which data cleaning will be very messy. In some cases, this unfortunately did not takes place because monitoring was not given full attention by the relevant parties. Complications are further added when the consultant already left the project. A side issue is that GIS analysis in town and country planning is very demanding on the computer because it involves a large volume of data. Thus, the lack of a powerful computer is very frustrating and data analysis can become very time-consuming. To those unfamiliar, GIS analysis in development control can be complex because inconformity does not necessarily mean not allowable development. To exemplify, a landuse zoned as “development” yet currently “agriculture” does not make it an offence in town planning but to the GIS eye, it is recognized as inconformity between zoning and existing landuse. Thus, effective monitoring of landuse development for conformity even with the QGIS-GRASS package requires more fine-tuning. 10



CONCLUSION Quantum GIS Ver 1.7 is still in its youth but has already possess many qualities of a proprietary GIS. In some cases, it excels better than proprietary GIS whereas in others, not as advance. Still, there are no rules to say a user cannot employ an external modules in the form of GRASS commands to further assist GIS analysis. It is here that the QGIS-GRASS package transforms a new kid on the block into a sophisticated mature GIS with growing muscle to silence hardcore critics. Given the rapid popularity of QGIS and frequent update of versions, it is anticipated that it will not be long before QGIS will be in the same league with proprietary GIS especially when backed by a strong local QGIS community, an area much needed in any open source software. When that happens, the QGIS-GRASS package will be an outstanding GIS tool confident enough for the average QGIS user to say “Sayonara to proprietary GIS�. REFERENCE

1. 2. 3. 4. 5. 6. 7. 8.

Quantum GIS homepage Quantum GIS; GRASS GIS homepage GRASS GIS; Malaysian Government Open Source Software Conference (MyGOSSCON), JPM, Putrajaya, 2-3 November 2009; 4th National GIS Conference & Exhibition, NRE, Putrajaya, 28 Jun 2010; Mesyuarat perbincangan data digital pewartaan tanah lapang awam, Bhg. Penyelidikan dan Pembangunan, Kuala Lumpur, 8 Julai 2011; Mesyuarat penyelarasan Garispanduan Kawasan Berbukit dan Tanah Tinggi, eKawalselia dan QGIS slope analysis plugin, Ibu Pejabat JPBD, Kuala Lumpur, 11 Julai 2011;


Development of a town planning colour template for .tab and .shp files.

QGIS is suitable for the preparation of landuse and zoning maps.

QGIS road graph plugin was used to develop the 10min response time catchment area for fire stations.

Google Satellite serves a background for the distribution of fire hydrants.

Google Hybrid serves a background for the distribution of public open space.

GRASS offers many vector commands for cleaning topology.

Geoprocessing tools were used to identify lots in conformity between zonng and existing landuse maps.

Data management tools were used to integrate spatial and non-spatial data.

SQL query was used to filter attribute data.

Geoprocessing tools and SQL query were used to filter data.


GRASS raster commands and user-defined inputs were used to develop slope-elevation analysis.

GRASS offers vector and raster statistic commands.

Google Physical offers a good base for digitizing contour lines.

GRASS buffer identifies lots affected by land acquisition under a road expansion project.

Google Hybrid offers a good supply of secondary data

GRASS vizualisation suite transforms data into 3d output.

Importing native file into GRASS also cleans topology

OpenStreetMap offers a good supply of secondary data

GRASS offers a variety of analytical command.

OpenStreetMap makes it possible to download features



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