Integration of GIS and Orthophoto to Enhance Road-Network Screening – A 3GR Approach

Mohamed Abdalla
Chartered Member of the Royal Institution of Charter Surveyors (RICS) UK And Americas
Department of Civil Engineering, Ryerson University, Toronto, Ontario, Canada
777 Bay St, P.O Box 46047, Toronto, On., Canada, M5G 2P6
msaad2000@msn.com

Abstract
This paper presents a new road safety analysis technique for verifying and enhancing road-network screening database. The technique is based on the integration of data obtained from a Geographic Information System (GIS), orthophotos and a road-networks database. The integration of the GIS with different road-network database was used to identify illuminated road segments. A cross correlation technique was used to extract the streetlight location and position. The integration of GIS and orthophotos was used to check and update the road-network database. A semi-automatic method was developed to recognize illuminated and un-illuminated road segments by using a specific group of filters and the cross correlation technique. Validation of the procedure showed that the new technique improved the light database, and the semi-automatic method successfully identified street segment types and extracted the streets poles’ positions. Rural and semi-urban areas were targeted in this study. The limitations of the new technique are discussed and future research into the integration of geomatics tools with road safety is highlighted.

Introduction
Fatal collisions are more likely to occur on rural highways than on any other road types. Traffic crashes are a major cause of death and injury in the United States. In 2002, there were 42,815 fatalities and over 2.9 million injuries on the nation’s highways. Crashes on rural roads (roads in areas with populations of less than 5,000) account for over 60 percent of the deaths nationwide, or about 70 deaths each day and the rural fatality rate per vehicle mile traveled on rural roads was over twice the urban fatality rate (General Accounting Office, 2004). Good visibility is essential to the safe operation of motor vehicles. Driving at night can be more challenging than daytime driving, as the distance that a driver can see clearly is reduced at night.

Collisions and lighting conditions are generally classified into eight categories: (1) collisions in daylight, (2) collisions in daylight with artificial light, (3) collisions at dawn, (4) collisions at dawn with artificial light, (5) collisions at dusk, (6) collisions at dusk with artificial light, (7) collisions in darkness, and (8) collisions in darkness with artificial light. There is a clear need to improve the analysis for nighttime collisions and to identify the lighting conditions accurately, but little effort has been done in this area because the collection process is costly and time consuming.

1.1 Scope
The focus of this paper is identifying illuminated and un-illuminated rural highways segments to check the existing data; complete missing records and solves data conflict. This will improve the quality of the data, road safety analysis, and network screening. Since collecting detailed information on street poles is costly and time-consuming, fast and inexpensive methods must be explored.

1.2 Objectives
The purpose of this thesis is to develop a semi-automatic method to identify illuminated and un-illuminated road segments by integrating geomatics tools and road network databases. The specific objectives of this research are:

1. To integrate Geographic Information System (GIS) and collisions data.
2. To integrate GIS and road network data other than collisions data.
3. To integrate GIS and orthophoto images to identify illuminated road segments and to extract the location of street light pole locations and positions from the images.
4. To validate the proposed method by using actual data.
5. To examine the implication of the proposal methodology for the safety performance function.

2 Dataset
Three different sources of data were used in this study: (1) digital orthophoto images for target area, (2) roads database records (e.g. collisions records, traffic volume, etc.) and (3) single line road network (SLRN) in GIS, ArcView, format. The data and images used in this study were obtained from the Regional Municipality of Durham.

3 Methodology

3.1 Challenge
The main challenge in this research is to recognize and extract the streetlight poles, which are narrow, vertical objects that have very limited width in orthophoto images. The poles appear as only a few pixels in the orthophoto. They are very difficult to locate or recognize using direct extracting methods. An indirect method is developed to extract the streetlight poles. The method is based on a unique idea that uses the image’s filters in an unusual way. As streetlight poles cannot be easily recognized on the image, a semi-automatic method has been developed to help users to recognize the streetlight poles types and location. The method is based on observing the streetlight poles and their shadow as the shadow makes the streetlight pole easier to recognize. To make the streetlight poles’ shadow more clear, filters were used.

The technique is designed to be user-friendly for road agencies and safety analysts and achieves accurate results without the need for a strong background in photogrammetry and orthophoto images.

3.2 Semi-Automatic Methodology
The semi-automatic method consists of two main steps: (1) extracting streetlight pole locations (2) identifying the illuminated rural highway road segments and update the GIS database.

3.2 .1 Identifying Pole’s Types and Locations
The Semi-automatic method for extracting streetlight poles locations and types can be summarized as follows (Fig.1):

• The orthophotos are linked with SLRN by using ArcView.
• Template windows for streetlight poles are chosen as signatures. These templates are chosen from the segments where no conflicts are recorded.
• To enhance the shadow of the streetlight poles, a custom filter called the “Minimum Filter” is applied. The “Minimum Filter” changes the brightness value of the pixels. In this study, the brightness value of each pixel is changed in the image according to a predefined mathematical operation. Each pixel is reassigned a value based on the values of the surrounding pixels. The “Minimum Filter” assesses individual pixels in a selection. Within a specified radius, the “Minimum Filter” replaces the current pixel's brightness value with the least brightness value of the surrounding pixels. The “Minimum Filter” has the effect of spreading out black areas and shrinking white areas.
• To enhance the objects in the image, the “Find Edges” filter is applied. The “Find Edge” filter is not applied to find the object edge as normal, but to make the object image more recognizable visually and mathematically when cross correlation is applied.
• The cross correlation technique is applied to identify streetlight pole types and locations. Template windows for each pole type are chosen and used as a signature. To achieve accurate results, the template windows are chosen from the nearest road segments having similar bearing. The area chosen to extract the streetlight poles is limited to a specific distance from the street centerline. In this study, this distance equals the road width plus the road’s 17 meters buffer. Any results obtained form beyond the buffer are discarded. The width of the buffer can be changed depending on the angle of the sun and the length of the pole’s shadow. The buffer is recommended to minimize computation time and to improve the results of the cross correlation operation.
• To improve the result of the cross correlation operation, the cross correlation parameters are pre-determined as follows: First, the clearest target is chosen from the nearest recognised road segment; this target is used as a template. Second, the cross correlation is applied for this segment. The results are evaluated, and the best minimum value of the cross correlation parameter is chosen. This is called supervised selection.
• The results are merged with the GIS system.

3.2.2 Identifying Road Segment Types
In this study, the data were classified into three different types: digital orthophotos, road network database records and SLNR. Each one had its own format and structure. Microsoft Access was used to link the different database files. The ArcView GIS system was used to link the digital images, network screening database, collision database, and SLRN (Fig.2).

The linking procedure was used to identify which road segments are illuminated (Type 1) and un-illuminated (Type 2). Three tasks are required to make this distinction:

• In the first task, the collisions database, accident locations records, and SLRN are linked together using ArcView. Collisions are classified into two main categories: (1) nighttimes collisions in low visibility on roads without illumination, and (2) nighttimes collisions on the roads with illumination. From this classification, “Type 1” and “Type 2” are identified.
• In the second task, road database records other than the collision database and SLRN are linked together. From this new task, the road-segments (Type1/Type2) are also identified.
• The results from the first and second tasks are compared. If there are no conflicts, the results are stored. Parts of these results are used to choose the best comparison template windows for the cross correlation operation. If conflicts are found, the segments are marked for further investigation and checking. The conflicts can be classified into the following groups: (1) the illumination records are missing from the database, (2) the illumination data recodes as unknown, and (3) there are different records for the same segment (e.g. the segment is recorded as un-illuminated and as unknown or illuminated in other database).
• If conflicts are found, the segments are marked for further investigation and checking. The conflicts can be classified into the following groups: (1) the illumination records are missing from the database, (2) the illumination data recodes as unknown, and (3) there are different records for the same segment (e.g. the segment is recorded as un-illuminated and as unknown or illuminated in other database).
• The semi-automatic method, which described in section 3.2.1, is used to identify the streetlight poles and to verify the road segments. To achieve accurate results, comparison windows are chosen from the nearest road segments having a similar bearing. The semi-automatic method is used to clarify the conflicts in the existing database; this can be used to create GIS data for street poles as well.

Fig. 1. General procedure for identifying pole type and location
Fig. 2 Scheme for the proposed methodology to enhance the illumination database and extract the poles location
4 Validation of The Methodology
To evaluate the semi- automatic technique performance, the technique was applied to the route, which consists of 62 different road segments with a total length of 39,886 meters. The site images were explored by using the semi-automatic technique.

The results were recorded in the GIS system. The results were checked on a site trip for the target route, which found that:

• Fifty-seven out of sixty two segments (91 %) had matching results.
• Five segments cannot be identified clearly. Three of the five segments were located in the core of downtown of the target city (Uxbridge city, Greater Toronto Area, Canada) where the view of the street poles was obstructed by the shadows of high buildings. The remaining two segments had illuminated and un-illuminated components. These segments should be subdivided to match the difference in illumination. Road agencies should note changes in road illumination as well carefully as they note physical changes in the road design

5 Implementation on Safety performance Function
The technique developed in this paper to enhance the street lighting database record is applied to the development of safety performance functions (SPFs). the SPFs, calibrated for two-lane rural highways under different lighting conditions. The SPFs calibrated for the raw data without any enhancement and for the data after enhancement. The results shows that the integration of GIS, orthophotos, and the road network database (e.g. collisions database, AADT, and intersection data) enhance the SPFs analysis.

The study how the method might affect road safety analysis, SPFs for two-lane rural highways (300 road segments with a total length 140 km) were calibrated before and after enhancing the data using the thesis technique. The thesis technique was also used to discover and resolve hidden problems in the data record.

The results were as follows:

• 7 % of the raw data was subject to conflicts. The new technique was able to identify and correct 90% of the conflicting records.
• 8 % of the raw data were unknown segments. The technique was able to identify 92 % of the unknown segments.

6 Summery, Conclusions and Recommendations

6.1 Summery
The integration of GIS, orthophotos and road network-screening database was implemented in this paper. Few researchers have worked in this field. The semi -automatic technique, which developed in this research, provides a tool that enables road safety agencies to verify illumination data in their databases and to fill in any gaps. The integration procedure improved the network-screening database.

The semi-automatic method successfully extracted the position of streetlight poles and identified whether road segment types were illuminated or not An important advantage of the semi-automatic method is that its application does not require users to have a strong remote sensing background or image processing skills.

The procedure resolved 90% of the data conflicts found in the data for illumination; and identified 92 % of the unknown segments (illuminated or not) for the targeted highways. The semi-automatic method is ideal for rural and semi-urban areas. The proposed technique is considered to be unique because it improves the data for illumination in the road database (enhancement illumination database is not covered adequately in the field of road safety).

However, the semi-automatic method may not work if high buildings or other obstructions cover the pole’s shadow. For this reason, the method is not recommended in downtown areas or close to high-rise buildings. Nevertheless, if the street poles are unobstructed, it may be possible to determine the segment type even if some poles cannot be located.

6.2 Conclusions
Many researches in road safety field wish to maximize their use of existing databases. Efficient and in-expensive solutions need to be found to check data and to fill gaps in the data. Data improvements and validation will have a direct effect on the quality of any analysis of the data.

The integration of GIS, orthophotos and databases can play a key role in improving the road network-screening database. The integration approach presented and discussed in this thesis offers a new tool to check and improve illumination data in the databases of road safety agencies. The technique can also help road safety agencies to extract additional features from road network data.

In this study, orthophoto images with 0.2m spatial resolutions were used to extract the pole type/positions and to identify the segment types and locations. High-resolution remote sensing images can be used to accomplish the same task, but it is recommended that remote sensing images with 1.0-metre resolution should be used to identify road segment types.

6.3 Recommendations
Orthophoto images can play a key role in extracting illumination data from the street network. Road agencies should give more attention to orthophotos images because the mages have considerable potential for supplying additional data about the road network.

High-resolution remote sensing images can be used to identify the segment type and to improve the street network database. Remote sensing images are widely available at a low cost, which will encourage road agencies to acquire them.

It is recommended that the technique proposed in this thesis should be used to check and examine intersections to identify which intersections are controlled by traffic signals. In addition, this technique can be used to improve collision data records for accidents involving fixed objects.

Illumination can improve road safety especially in rural areas. While it is not practical to illuminate all rural roads, hazardous segments should be identified and illuminated.

Road jurisdiction databases should also benefit from the integration of GIS and network-screening databases.

The integration of GIS, GSM, GPS and remote sensing (3GR) can help road safety analysts to improve the quality and accuracy of their analysis. It can help the road safety analyst to predict annual average daily Traffics (AADT), and vehicles miles travel (VMT). It can improve crashing data analysis and classification.

References

1. AASHTO. A Policy on Geometric Design of Rural Roads. 1994.
2. Abdalla, Mohamed. 3GR for Road Safety. Proceedings of the 9th International conference, Application of Advanced Technologies in Transportation Engineering, ASCE:255-260, 2004.
3. Annual Report File (ARF). Fatality Analysis Reporting System (FARS), National Center for Statistics and Analysis (NCSA), 2002.
4. ERDAS Guide. ERDAS Field Guide Fourth Edition, Revised and Expanded, ERDAS Imagine Ver. 8.3. Part No. SWE-MFG4-8.3.0- ALLP, January 1997.
5. General Accounting Office (GAO), 2004.
6. Guo, G. Negative multinomial regression models for clustered event counts, In A. E. Raftery (ed.), Sociological Methodology, 26: 113-132. San Francisco: Jossey-Bass,1996.
7. Hauer, E .Observational Before-After Studies in Traffic Safety, Elsevier Science,1997

Open Source and free GIS: A way out?


Paolo Cavallini
cavallini@faunalia.it
Faunalia
Piazza Garibaldi 5 - Pontedera (PI)
Italy
Web: www.faunalia.com

OPEN SOURCE AND FREE SOFTWARE
What is free software? What about Open Source? Without going too deep into the legal and philosophical issues (a review can be found at: http://www.gnu.org/philosophy/free-sw.html), we can say that a computer program is free when everybody can use, modify, and redistribute it. This implies that the source code of the program must be available, and that usually no licence fees are requested. We thus usually refer to these programs as FOSS (Free and Open Source Software). One must be careful to distinguish free programs in the restrictive sense of gratuity; there are many proprietary (closed source) programs that are distributed for free, sometimes as demos or runtimes of larger packages (e.g., in our field, ArcExplorer). The distinction is important, because having access to the source code is essential to guarantee that free software will remain free forever.

In recent years, interest on FOSS has grown considerably, both because of budget choices, and because of the ample scope for customization and reuse; also issues of democracy of information and elimination of the digital divide have a place here. Well-known successes include the dominant position of Apache (http://www.apache.org) among web servers, MySQL (http://www.mysql.com) among web databases, etc.

Several elements make FOSS particularly attractive in the developing countries:

• relatively scarce financial resources, both in the private and in the public sector, push towards the adoption of low-cost solutions
• the availability of skilled programmers (notably in the case of India, but also in many other countries) able to exploit effectively the scope for customization and further development of existing or new tools
• resources invested in FOSS development remain in the country, and may help building up a national software industry, whereas money invested in proprietary software (i.e. licences) goes largely abroad.

Several factors hinder a wider and faster adoption of FOSS in many contexts: freedom implies the availability of a wide variety of products, not all of which are mature and fully functional. It may therefore be difficult, at first sight, to identify the best solutions for a specific application; furthermore, the lack of a solid commercial structure (and the advertisement that come with it) does not help “spreading the word”.

This paper aims at giving an overview of GFOSS, and provide you with an evaluation of its strong and weak points, with particular emphasis on its possible use in a professional context. While striving for a maximum objectivity, the paper necessarily reflects my particular point of view, i.e. that of an end user, without an IT background, mainly concerned with geographical analyses. Further information is quite easy to get, especially from the Internet; a good starting point is http://freegis.org.

THE TOOLS

Interoperativity and data conversion
In the GIS sector, pressure for having fully interoperative software has always been strong; as a result, the use of different data sources (with or without the need for conversions) does not pose major obstacles also for free software. The basic tool for this is the library GDL/OGR (hereafter GDAL; http://www.gdal.org), that allows all major free programs to use a wide variety of data, both raster and vectors (Tab.1).

Among the few problems that remain, the most serious is with AutoCAD files (dwg); in this case the conversion requires a library (OpenDWG) available at no cost (for non-commercial use), but non-free (in spite of its name). Although technically easy, this makes it illegal its redistribution when linked to FOSS programs; every user (or group of users) is therefore requested to the necessary programs with the support to OpenDWG).

Reprojection of rasters and vectors among different coordinate systems and datum are managed by the PROJ library (http://www.remotesensing.org/proj). The precision is the same as for major commercial software, and may be increased (thanks to the availability of source code) with slight adaptations of the existing code.

Geodatabase
The killer GFOSS application in this sector is undoubtedly PostGIS (http://postgis.refractions.net), linked to the GEOS library (http://geos.refractions.net). It is a spatial extension of PostgreSQL, the most powerful FOSS relational database. PostGIS allows the storage and management of geographical vector data directly from within the database (thus using standard SQL and its Open Geospatial Consortium [http://www.opengeospatial.org; hereafter OGC] extensions: distance, area, buffer, overlay etc. Every record is associated to a specific projection, thus in the same database data in different projections can coexist, and they'll be correctly overlayed. The data model is non-topological, and fully compliant to Simple Feature specifications of OGC (SFS 1.1, SFS TF 1.1). Importing and exporting ESRI shapefile data is straightforward. Raster geodatabase are not available for now, but there are plans for a future implementation.

Desktop mapping
The vat majority of so-called GIS work is indeed desktop mapping. In this respect, GFOSS had a significant gap compared to commercial applications, because most GFOSS users were IT persons, more inclined toward problem solving than to graphical appearance. In the last few years, thanks also to a larger user base, the situation has vastly improved, especially thanks to the rapid evolution of QuantumGIS, or qgis (http://qgis.org), a point-and-click application not dissimilar from commercial equivalents (see Fig. 1).


Figure 1 QGIS can display and edit various raster and vector geodata, including GRASS layers
Among the strong points are:

• the direct access to a variety of raster and vector data format, including shapefiles and PostGIS geodatabases (with support for editing)
• the integration with GRASS (see below), for which is becoming an effective and easy Graphical User Interface
• the reprojection function, capable of reprojecting on the fly raster and vector data from a variety of projections to a common one, chosen by the user.

Although very usable, it is still a young product, and the coming months will probably see an increase in its stability and functions.

Other desktop GIS are available, including Thuban (http://thuban.intevation.org) and OpenEV (http://openev.sourceforge.net); the first one has strong limitations in the handling of rasters, while the second, powerful in the image analysis, is not as easy for the unexperienced user.

Geographic analysis
The “all purpose” free is GRASS GIS (short for Geographic Resources Analysis Support System: http://grass.itc.it). Historically known as a raster GIS, difficult to use, mainly command-line oriented, since 2002 it has known a heavy development; the 2D and 3D vector section, as well as the database integration, have been completely rewritten, and it is now available as a new (6.0) stable version. It is very complete, with all functions required for a professional use, from management and analysis of geospatial data to image analysis, from chart and maps production to spatial modelling and 2D, 2,5D, and full 3D visualization; a complete list of the >350 modules (many of which with several options, giving a total of more than 600 commands) can be found at: http://grass.itc.it/grass60/manuals/html60_user/index.html; in addition to the command shell, fundamental for automatizing the work flow, it has a simple and effective graphical interface (Fig. 2), although QGIS is becoming the best tool for this. It is very easy to combine existing commands, creating your own scripts, in addition to the possibility of programming more complex tasks in C, C++, Perl etc. Alphanumeric data can be managed with a variety of tools, among which the simple DBF, and the powerful relational database PostgreSQL. Statistical analyses can be run smoothly from within a GRASS session, both with GRASS internal modules, and with R statistical package (http://www.r-project.org).


Figure 2 GRASS and its native graphical interface. Hundreds of modules and commands are accessible trough pull-down menus
When compared to commercial equivalents, GRASS is generally very stable, also in very large and complex applications; its usage may be sometimes a bit tricky for the inexperienced user (thus the importance of the QGIS interface).

Web mapping
The Web is, and it has always been, the domain of free software; no surprise then that the one of the most powerful web mapping application is a free one; Mapserver (also called UMN Mapserver: http://ms.gis.umn.edu) has been developed originally by the University of Minnesota. It is OGC compliant (WMS 1.1.0, WMS 1.0.0, WMC 1.0, WFS 1.0.0, SLD 1.0, GML 2.0, Filter 1.0.0, WMS 1.1.1). The developers have been careful not to overfeature the main engine, that is very stable even in critical applications; a number of applications have been built on to of it, extending its functions by the use of various programming languages: php, perl, python, javascript, etc. Examples include pmapper (http://pmapper.sourceforge.net), Chameleon (http://chameleon.maptools.org) and Cartoweb (http://www.cartoweb.org). With these tools, customized web mapping applications can be built in a very cost-effective way.

GPS
Global Positioning System receivers are very useful and widespread; many free programs are available for interacting with GPS hardware, from single-purpose command-line downloading programs (e.g. gpstrans: http://gpstrans.sourceforge.net) to the more sphisticated ones, with graphical interface and conversion tools (e.g. gpsbabel: http://gpsbabel.sourceforge.net); some have real-time navigation application (e.g. gpsdrive: http://www.gpsdrive.cc) or differential correction (dgpsip: http://www.wsrcc.com/wolfgang/gps/dgps-ip.html). The easy integration among different tools, characteristic of open source programs, allows larger programs like GRASS and QGIS to – and upload points and tracks straight from/to the devices. In the case of GRASS, data are reprojected automatically in the working projection and converted to the GRASS vector format.

Java: another world?
The power of Java programming language has allowed the development of GFOSS applications. The growing computing power of modern PCs makes speed of Java programs sufficient, even for heavy applications. Java, however, is not free as a language, and its proprietary alone (Sun Microsystems, Inc.) has the right to change its specifications; this makes it less attractive for FOSS people (see e.g. http://www.gnu.org/philosophy/java-trap.html). In spite of this, a few Java GFOSS programs are particularly interesting; Deegree (http://deegree.sourceforge.net) is a good MapServer, fully compliant with OGC specifications (WTS 0.5, WMS 1.1.1, WMS 1.1.0, WMS 1.0.0, WMC 1.0, WFS 1.0.0, WCS 1, St Cat 0.06, GML2.1 2.1.2, Gaz 0.8). For desktop mapping ans some analysis, Java Unified Mapping Platform (JUMP: http://www.vividsolutions.com/jump) has attractive features (Fig. 3). For GRASS users, a Java graphical interface is also available (JGRASS:http://www.hydrologis.com/html/jgrass/jgrass_en.html).


Figure 3 GRASS can display and analyse 2,5 and 3D data

IN PRACTICE: HOW TO TRY IT?
The vast majority of the programs outlined here gave been developed on *NIX operating systems (Unix, Linux etc.), and today GNU/Linux is generally the ideal platform for their use; many of them have been ported on other operating systems (including Microsoft Windows and MacOSX), but some of them still suffer from some limitation. Luckily, the installation of Linux is today reasonably easy , and can be done quickly with some help. Various operating systems (Linux, Mac OSX, Windows etc.) can coexist on the same PC without any side effect. The usage of simulators and virtual machines, on the other hand, is rather heavy, and does not offer significant advantages. It is also possible to have a preview of a real Linux system just using a “live” CD-ROM that, without installing anything on the hard disk (therefore not modifying any of the installed applications) starts a complete Linux machine (of course, much slower than a real one, because of the CD accession time). Some examples of GFOSS live CDs are listed at: http://grass.itc.it/download/cdrom.php. When working with GFOSS, one has to keep in mind that the community of users and developers is a fundamental resource: by the use of mailing lists, forums, web sites, chats etc., is very easy to get support. Users are encouraged to find and report bugs, that are often fixed in a very short time. Throughout the web a wide variety of manuals and how-tos are also available.

CONCLUSIONS
Is freeGIS ready to replace commercial software in real applications? The answer is articulated. To compare side by side large and complex applications is an heavy task, and few people have attempted this on a limited scale. Nevertheless, from our experience it is clear that several products are mature and ready for professional use, whereas others, while usable, need further development to be really competitive (setting aside the cost of acquisition):

• UMN Mapserver is fully functional; it does not have significant limitations, and in several respects it is superior to its commercial counterparts
• PostgreSQL+PosGIS as a relational geodatabase is a very reliable and powerful solution, and has already replaced commercial top-end solutions
• for geographic analyses, GRASS is fully functional, stable and very powerful. In many situations (where money is an issue: underfunded universities and public administrations, small or heavily competing companies, etc.) it is the best alternative to the (unfortunately very common) illegal use of (cracked or stolen) proprietary software. Its inherent qualities, however, allow its use also in large and more complex settings
• desktop mapping (and in particular QGIS) is usable, but still young; some more months of development will be necessary to make it more stable and powerful.

In addition to these programs, many others are available that can suit special needs and applications; see a list on http://freegis.org.

Tab. 1. Data formats supported by GDAL (raster) and OGR (vectors)


Figure 4 Java Unified Mapping Platform (JUMP): a free GIS programmed in Java

Community Mapping in Malaysia

Jason W.Y LEE
Department of Multimedia Communications
Faculty of Arts and Social Science
Universiti Tunku Abdul Rahman
wylee@mail.utar.edu.my

Abstract
The availability of open source GIS based software has made it possible for hobbyist access to software that was once accessible by the expert cartographer. However, little attention has been paid to “free’ maps which are often deemed inferior in terms of quality. In this paper, I will review how one particular group of community “mappers”, namely “Malsingmaps” is changing the way maps are distributed in Malaysia. Two methods that are commonly used by community mappers for creating the maps will be demonstrated. The first method is collecting tracks using a handheld GPS unit and second method would be tracing vector images obtained from Google Earth. While the techniques used are not new to the GIS community, the success and power of community mapping is the number of volunteers that contribute to the community map. Community maps are constantly updated with new features added almost every week. Ultimately, community maps cannot replace commercial maps in terms of accuracy but is paving way in making GIS more accessible to the general public.

1.0 Introduction
When the United States military experimented with the Global Positioning System (GPS) in 1978, little did they know that almost 30 years later, the technology can be used from tracking vehicles to trekking for casual hiker. However, accuracy for civilian use was limited as intentional errors between 0 to 100 meters were introduced into public navigational signals by the military to prevent untoward attacks on US interest. This inaccuracy known as Selective Ability (SA) was finally discontinued (The White House, 2000) with an announcement made by then President Bill Clinton on May 1st 2000.

Recent developments in Geographic Information System (GIS) has led the prices of GPS receivers (GPSr) around the world to fall thus making it more accessible to the general public. Mobile devices such as phones and personal digital assistants (PDAs) are also now built-in with GPS capabilities. While GIS technology exists back in 2001, maps for the Asian region, especially South East Asia are often incomplete. GPSr vendors such as Garmin do not offer comprehensive maps for this region except for Singapore (MapSource - City select malaysia, n.d) .This perhaps was one of the main reasons for the low adoption rate of GPS as navigation devices coupled with the high prices of the GPS units in Malaysia.

The availability of open source GIS based software has made it possible for hobbyist access to software that was once for the expert cartographer. However, far too little attention has been paid to “free’ maps which are often deemed inferior in terms of quality. This paper, attempts to demonstrate how one particular group of community “mappers”, namely Malsingmaps is changing the way maps are distributed in Malaysia. A simple proof of concept track that is typically used by this community for creating maps will be reviewed.

2.0 Birth of a community
The lack of proper maps did not deter a group of GPS enthusiast to pursue their interest in this area. As early as mid-2003 a MSN forum was created for GPS enthusiast in Malaysia and Singapore to discuss their interest (Yong, 2005). The lack of proper maps has driven this group of mapping enthusiast to experiment with self mapping. While the growth was slow during the early years, the birth of Malsingmaps has propelled interest in mapping among many GPS enthusiast in Malaysia. Updated maps are released almost every month with the help of other mappers who contribute tracks using their GPSr which will be reviewed later in this paper.

To further improve mapping efficiency, the maps were divided into 9 map tiles covering Peninsular Malaysia (6 tiles), East Malaysia (2 tiles), Singapore (1 tile) covering three countries namely Malaysia, Singapore and Brunei. Several members were selected to be responsible for each tile where updates were to be compiled by them. In the early days, individual map tiles were updated on an irregular basis and maps were only available for Garmin users. However, over the recent years, as the community grew, the maps are now released simultaneously on a variety of format including for the two most popular GPSr format, namely Garmin and Mapking.

2.1 Collaborative Mapping in Malaysia
In order to determine the state of collaborative mapping in Malaysia, Malaysia’s leading community mapping group Malsingmaps was chose. Figure 1 illustrates the map of Klang Valley viewed at various resolutions using Garmin’s Mapsource of the map obtained from Malsingmaps’s official website.


Figure 1: Malsingmap’s Klang Valley Maps on various resolution using Garmin’s Mapsource
At 1km view, the major urban freeways that run along the Klang Valley are clearly visible in dark orange while the tolled highways are visible in dark blue. At the 500 meters, arterials roads are visible in black. Zooming in further reveals various points of interest (POIs) such as bank location, fast food outlets and traffic junctions.

Evidently, the work created by the community is no longer amateur. The maps are fully routable when used with a Gamin GPS unit. While the site was initially created to cater exclusively for Garmin users, the rapid adoption of GPS among Malaysian has lead the group to cater for another set of users, namely Mapking users (Mapking is a software written for the Smartphone and PocketPC platform and is popular in this region).

2.2 Community vs. Commercial Maps
Community maps are by no means perfect. To determine if community maps are on par with commercial maps, a comparison was conducted as illustrated in Figure 2. A visual comparison illustrates the similarities between the roads for both commercial and community map as illustrated in Figure 2. The power of community maps is in the additional POIs such as food stalls and petrol stations contributed by users that do not appear on many commercial maps.


Figure 2: Comparison between Commercial and Community Maps
Closer inspection on the community map reveals that the number of polyline points used are less compared with commercial maps thus making road curves look less smooth and roundabout looking jagged. This can be attributed to the fact that the community maps are drawn from tracks collected from users. However, the purpose of the community maps are for in-car navigation and therefore is not a major issue compared with completeness of the map.

To test the completeness of the community map, 100 roads were selected from around the Klang Valley including newer housing suburbs such as Kota Damansara to older one such as Setapak. A 100% match was found for all the pre-selected roads indicating that the maps were up to date. However, the same test could not be performed for “Commercial Map 1” as it dates back to 2002 and thus does not provide an accurate comparison for this paper.

It should be noted that commercial maps are by no means less superior to community maps. Commercial maps are created with precision and accuracy in mind while community maps are created for their completeness. Completeness in this sense would mean having all the latest roads and important POIs in the base map.

3.0 Authoring Maps
The notion of a group of amateurs creating a complex map of Malaysia could even have been thought as preposterous when not many developed countries around the world have detailed community maps. The availability of GIS freeware and shareware has lowered the barrier of entry to the world of GIS that was once exclusive to the experts. This paper attempts to recreate the two commonly used techniques used by Malsingmaps’s mappers to author these maps. The first method for data collection is done through a handheld GPS unit. The second method uses satellite imagery collected from Google Earth which is then traced to produce tracks.

3.1 Authoring using a GPSr
Using a handheld GPS receiver, a Garmin 60C unit was used to collect tracks around the Klang Valley. To improve trekking accuracy, an external antenna was attached on the roof of the vehicle giving it an average tracking accuracy of ±7 meters. The track logs were set to a 1 second interval to ensure that more road details are captured. The “lock on road” feature was disabled in the Garmin 60C unit to ensure that tracks are not locked to existing roads which renders the tracks useless. When possible, we drove on the far left hand corner of the road at a constant speed.

Once the tracks have been collected, several steps have to be taken before a simple vector map can be produced. Figure 3 illustrates the steps that were taken to produce Garmin’s IMG map format from the tracks that was collected but has no routing capabilities. GPSMapEdit and cGPSmapper are closely integrated thus making the entire conversion process of our proof of concept map from the raw tracks to the IMG Map format in less than 5 minutes.


Figure 3: Authoring using Garmin GPS60C
All the GIS software used in this demonstration such as GPSMapEdit, cGPSmapper and Google Earth are available for free except for Garmin’s Mapsource which comes bundled with the GPS receiver. cGPSmapper is a software that makes it possible to create base maps for Garmin’s close source and proprietary map format called IMG. The developer has created a free version but does not support routing. GPSMapEdit is a visual GPS authoring shareware that provides many advance features in GIS. However, we will mainly use this software to convert our Mapsource data into “Polish format”. Polish format is required by cGPSmapper for converting the collected treks into Garmin readable maps.

3.2 Authoring using Google Earth
The second method in authoring maps is tracing raster images. While this is not a new method for cartographers to create maps, it was not until recently when satellite images became more accessible. This is due to the introduction of Google Earth which has made it possible for almost everyone to obtain high quality satellite imagery for free.

In this paper, an area in the Klang Valley was selected for tracing in Google Earth. It should be noted that the Google Earth images has some offsets that needs to be corrected once the tracing has been done. A screenshot of the selected area is captured with the latitudinal and longitudinal grids enabled for referencing from Google Earth. There are several methods in which the roads can be traced using software such as Garmin’s Mapsource, OziExplorer or GPSMapEdit. Once the roads has been traced, it has to be calibrated approximately 0.00015 west (Mapping with Google earth, 2007). The points traced from the raster image are ready for conversion using a similar process in Figure 3.

4.0 Conclusion
While there is some doubt on the accuracy of community maps, the purpose that the maps were created was simple: to be used as a base map for in-car navigation and recreational purposes. The power of community maps are in the large number of volunteers or mappers as they call themselves who constantly submit updates and corrections back to the community. It is also interesting to note that the community maps also cover many interior areas of Peninsular Malaysia but are limited to major roads.

Undoubtedly, the community maps are not by any means not the most complete maps available. However, in comparison with commercial maps which are very costly, the community maps narrows the digital divide in the GIS community. The efforts taken by the Malsingmap community is indeed commendable. From the birth of the community in 2003, the community is 45,000 members strong and growing by the day as the adoption of GPS increases with inbuilt GPS capabilities in mobile phone handsets

5.0 References

• MapSource - City select malaysia. (n.d). Retrieved 5 May, 2007, from Garmin:
  http://www8.garmin.com/cartography/mapSource/cityselectMalaysia.jsp
• Mapping with Google earth. (2007). Retrieved 20 June 207 from
  http://www.malsingmaps.com/wiki/index.php/Mapping_with_Google_Earth
• The White House. (1 May, 2000). Statement by the president regarding the United States decision to stop degrading global positioning system accuracy. Retrieved 24 April, 2007, from Office of the press secretary: http://www.ostp.gov/html/0053_2.html
• Yong, A. (2005). The history of malsingmaps.com. Retrieved 24 April, 2007, from
  http://www.malsingmaps.com/wiki/index.php/History_%26_Achievements

Public Participatory Geographical Information Systems (PP GIS) in the Gulf Region

Fred Ernst
Development Commission of Makkah
Madinah and the Holy Sites
P.O.Box 55255
Jeddah 21534
Saudi Arabia
fred.ernst@gtz.de

Introduction
Knowledge is power. This old proverb is more meaningful than ever as we are striving towards building knowledge cities. The world's burgeoning cities are a critical fact of the 21st Century - and represent one of the greatest challenges to the future. By the year 2050 cities with populations over three million will more than double from 70 today to over 150. Those of them that will succeed in becoming part of the knowledge city community will have great advantages over those that will fail.

According to Leif Edvinsson knowledge city can defined as “a city that purposefully designed to encourage the nurturing of knowledge”. Characteristics of a knowledge city have been proposed in a position paper titled “Culture, The Motor Of The Knowledge City - Strategic Plan of the Cultural Sector of Barcelona” (Barcelona City Council, 2003) and are listed below:

• A city that has instruments to make knowledge accessible to citizens.
• A network of public libraries that is compatible with the European standards.
• Access to the new communication technologies for all citizens.
• All cultural facilities and services with a central educational strategy.
• A city that has a newspaper- and book-reading level that is similar to the average European level.
• A city that has a network of schools connected with artistic instruction throughout its territory.
• A city that is respectful of the diversity of cultural practices of its citizens.
• A city that places the streets at the service of culture.
• A city that simplifies, through the provision of spaces and resources, the cultural activity of the community collectivities and associations.
• A city with civic centers that are open to diversity and that foster face-to-face relations.
• A city that makes available to citizens from other territories all the tools required for them to express themselves.

In order to fulfill the first criteria powerful information systems have to be put in place that can handle the spatial context of urban information. Geographic Information Systems (GIS) are best suited to store, analyze and display data that have spatial relationships. In the past, whole Municipal Information Systems have been build upon GIS technology whereas nowadays, GIS tends more and more to be integrated into mainstream IT systems.

Public Participatory Geographical Information Systems (PP GIS) is a field of special applications that focuses on the use of GIS by the general public and aims at involving citizens in decision-making processes. PP GIS is an abbreviation which indicates that the public needs to be supported when addressing community based problems, since a variety of perspectives are common in different planning processes. PP GIS seeks to expand the use of GIS to the general public and non-governmental organizations that are not usually represented in traditional top down GIS implementations (Talen, 2000).

In most cases, applications supporting PP GIS use the web as a platform for communication and dissemination of information (Kingston, Carver, Evans, Turton, 1999). Technically and conceptually, these systems allow for novel approaches, for example to organize an online forum where citizens have the possibility to express their opinions, the usage of new image generation systems or augmented reality systems so that the users can walk through a “planned city” (Steinmann, Krek, Blaschke, 2004).

All these applications share the same approach of using GIS as a means to facilitate community participation in a diversity of social and environmental contexts in common. However, applications differ widely in terms of the level of interactivity and the way in which the users communicate with the system as well as in terms of functionality and content. In this paper several examples of online PP GIS applications are compared and evaluated according to their usability, interactivity and spatial visualization. Analysis of some important samples in the Gulf Region are presented and it is discussed how they can stimulate more active participation of the general public in decision-making at the urban and regional level.

Internet Access in the Gulf Region
Usually, PP GIS applications make only sense if Internet access with reasonable speed is provided. According to Madar Research Group, 2006, growth rate of Internet use in Arab countries has substantially risen over 2004 levels, to average at around 55 percent, with few countries where Internet penetration is lowest witnessing three-digit growth.

Nevertheless a huge gap remains between Arab countries in terms of Internet penetration. While Internet use has become so widespread in United Emerites of Arabia, where users are dropping dial-up access in favor of broadband connections, Internet use in Saudi Arabia is still reminiscent of the early years of the advent of public Internet having a penetration rate of only 10.6% (Internet World Stats, 2007).

Even with such low penetration rates according to Al-Saggaf (2004) “There is a radical transformation taking place in KSA. The Saudis are poised on the edge of a significant new social landscape.” This new “frontier” includes not only the creation of new forms of private communication but also online discussion areas where PP GIS applications could fit in. And keeping in mind the high growth rates of Internet access a much higher Internet penetration rate can be anticipated for the near future.

Evaluation of Selected PP GIS applications

Criteria for Evaluation
The evaluation of the selected PP GIS applications will be based on three criteria:

• Interactivity,
• Spatial visualization, and
• Usability.

Interactivity means that some action of the user generates a response either from another person at the other end of the connection or from a application residing on the server side. Generally, PP GIS applications include operations like zoom, pan, copy and paste themes between views, and spatial queries like distance measurements, location and number of occurrences of an entity, attributes of an entity, shortest path, etc. More sophisticated interfaces should be designed in a way that support is given for personal interests and preferences, the exploration of planned alternatives and assessment of these alternatives. Finally, in order to be real “participatory” the interface should allow for expression of a personal opinion about planning alternatives and voting for the favorite one.

Spatial visualization is a powerful method for the representation of spatial data on man made and natural features. These data sets can be further combined with digital elevation models (DEM), aerial photography, satellite images and linked to pictures, video, sound and other documents. The ultimate goal should be the setting up of a virtual reality system for planning purposes, in which the citizen can get a real feeling of the existing and the planned environments. Usually, this includes the presentation of all or selected features in 3D mode and a “walk through” or “fly through”.

Usability: PP GIS applications should be easily usable and understandable by a broad public audience. Although such a general statement applies for any software it is of utmost importance in the case of PP GIS. The target group of PP GIS applications is the general public, which naturally is a very heterogeneous group of users and therefore not easily definable. In addition, it has to be kept in mind that especially in the case of the Gulf Region the potential users have a diverse range of world views, cultural backgrounds and knowledge. These aspects require that PP GIS applications are easy to use (Haklay, 2003).

Selected PP GIS Applications
Four applications from the Gulf Region have been selected: “Explore Dubai” (including related applications), “Kuwait Electronic Guide”, “Explore Qatar” and an application developed for the Ministry of Higher Education of the Kingdom of Saudi Arabia. Although these samples should represent the major developments in the field of PP GIS in the Gulf Region it is not claimed that all ongoing activities have been described.

Dubai
The GIS Center of the Municipality of Dubai developed an interactive online Internet mapping application that targets on the general public, special user groups and the business sector. “Explore Dubai” (http://www.gis.gov.ae) provides the user with a wealth of digital geographic information through a series of pre-defined maps and customized queries.

Main features of “Explore Dubai” are:

• Accurate, detailed and up-to-date geographic, address based information accessible via computers and mobile devices.
• Integration of multiple data sources in real-time.
• Access to high-resolution aerial photography with easy to use tools that allow users to measure areas and distances.
• Integrating of hyperlinks free of charge.

The next figure shows how hyperlinks can be embedded into “Explore Dubai”.

Figure 1: Internet Mapping application “Explore Dubai”

Another step towards PP GIS could be the launch of the first phase of the Engineering Projects Information Management System (EPIMS) by Dubai Municipality's IT department. The system enables all the staff and clients to communicate through an integrated electronic channel, resulting in significant time savings and error-free completion of transactions. It also facilitates easy access to information, leading to better decision-making.

The new project allows various departments in the municipality such as Contracts & Purchasing, General Projects, and Finance, to submit their applications electronically. These applications range from accreditation materials, graphics, plans, programs and reports about the implementation of the engineering projects, in addition to financial requirements. EPIMS facilitates more effective internal communication between all departments of Dubai Municipality and to some extent with external users like contractors and consultants.

Kuwait
Like many other Arab countries the State of Kuwait has put much effort in developing e-Government initiatives. The Ministry of Interior, Public Authority of Civil Information and Kuwait Municipality are playing a key role in such activities. Although three authorities already applied e-Government on different levels, the Information Systems department at Kuwait Municipality is most advanced in the usage of GIS and accompanied databases. A Internet mapping application has been developed called “Kuwait Electronic Guide” (http://gis.baladia.gov.kw/) that enables printing of maps and answering queries on a basis of parcels. In addition, tourist information about the State of Kuwait, can be searched using this application. As a special feature of this application routing using shortest path algorithms can be conducted by the user (see figure below).


Figure 2: Internet Mapping application “Kuwait Electronic Guide”

Qatar
The Center of GIS (CGIS) – State of Qatar is systematically implementing GIS for all agencies, government organizations and the general public of Qatar. Established in 1990, CGIS has been among the most active GIS organizations in the region. Already in 1999, Al Ghanim mentioned the concept of “societal GIS in Qatar”.

CGIS has developed the Internet mapping applications “Explore Qatar” (http://www.gisqatar.org.qa/new/all.html) that can be used o locate addresses, landmarks, nearest schools or clinics or highlight physical features on the live map (see figure below).


Figure 3: Planned Internet Mapping application “Explore Qatar”

Saudi Arabia
The Ministry of Higher Education of KSA has developed a special application to address the availability of facilities of higher education in KSA (http://gis.mohe.gov.sa) showing its spatial context and enabling in-depth analysis of selected attribute data. This is the only application of the ones described in this paper that enables queries with multiple criteria.


Figure 4: Internet Mapping application of Ministry of Higher Education of KSA

Evaluation
An overview of the evaluation of the presented samples in the chapters above in terms of interactivity, spatial visualization and usability is given in the table below. Although in the case of Dubai two different applications have been analyzed they have been considered one because they are all under the umbrella of the Municipality of Dubai and rely partly on the same data sources.

Table 1: Evaluation of presented samples


A thourough interpretation of the table shown above reveals how far the given criteria and sub criteria have been met:

• Interactivity:
• All applications offer basic functions for spatial and attribute query.
• Some more sophisticated functions have also been included in all applications. For example, the EPIMS of Dubai enables a selected target group (construction sector) to view the status of construction projects.
• Participation of the general public in the form of exploration of planning alternatives and voting is not yet foreseen in any of the applications.
• Spatial visualization:
• The amount of themes the user can select to be displayed varies considerably between the analyzed application. Where in some cases only about 5 different themes can be used a lot of other useful data (landmarks, service points) can be viewed in other cases.
• Imagery is available in some of the applications originating from different satellite systems and aerial photography.
• Linkage to other documents is missing in all the applications that were online.
• Usability:
• Although for the criteria interactivity and spatial visualization a whole subset of sub criteria during the evaluation process could be used this proved to be difficult for the criteria usability. A GIS professional would never share the same opinion with someone who even does not very well know how to navigate in the Internet. Therefor, besides some very general sub criteria like language options only an overall evaluation according to “the easier the better” has been carried out. For example, using terms like “SPOT” and “LANDSAT” without indicating that these are satellite data can only understood by a professional GIS user.

Discussion
A total of five (including two for Dubai) applications of PP GIS in the Gulf Region have been described and evaluated by using the criteria of usability, spatial visualization and interactivity. Concerning the first and second criteria most of the applications embed tools to let them work efficiently for the purposes they were designed for. However, if it comes to the criteria of interactivity the picture changes: Whereas in all applications basic functions were included none of them (like most of all web-based GIS) incorporated tools for displaying planned projects or even to give opinions about them. Therefor, the question arises whether these applications can really be considered as “Participatory” GIS?

Definitively, this question can not be answered by yes or no. PP GIS is not just an online voting machine, it should also harbor components like online service delivery and online discussion. In order to enable the general public to participate in any planning process means to present information about its natural and man-made environment have to be put in place. “The right to know” has to be fulfilled first before any participation can start. And it is no secret that participation is only about to start in this region. PP GIS is not something static rather it has to be put into the context of the technological and societal developments taking place. Keeping this in mind, newest developments like EPIMS of Dubai that allows a selected user group to view planned projects indicate that the publication of information has obtained a higher priority than it had in the past.

Realizing how fast technological and societal development is progressing in this region the way to more advanced PP GIS might actually take not so long. Currently, in all the states of the Gulf Region the governments are seeking for ways to let the general public participate more actively in planning processes.

PP GIS offers all what these societies are looking for:

• Possible participation of all different groups in any planning process.
• Participation can be kept anonymous. This would of course require that the PP GIS is designed in a way that does not keep track of participating Internet users and trust has to be created by the owners of the systems.
• Participation can be done without exposing gender. Under the assumption the participation of both sexes is expected, women can participate without being exposed.
• PP GIS is a polling not a voting tool. That means the results of any participation process would not be binding for the respective government.

One fact could give some harm to this nice scenario: The “digital divide” is a reality in all the states of the region. If the access to Internet cannot be provided for a much higher proportion of the population PP GIS will become an anachronism: Instead of enabling all parts of the general public to express their wishes and needs it will be only another mean of the privileged to pursue their own interests.

References

• Al Ghanim, Q. M. A.: Qatar’s GIS - A Unique Model for Next Millennium GIS. ESRI International User Conference 1999, at http://gis2.esri.com/library/userconf/proc99/proceed/papers/pap960/p960.htm.
• Barcelona City Council: Culture, The Motor Of The Knowledge City - Strategic Plan of the Cultural Sector of Barcelona. 2003, at www.bcn.es/accentcultura/angl/webang.doc.
• Edvinsson, L.: Corporate Longitude. Pearson Education Limited, Harlow, 2002. Internet World Stats: Internet Usage in the Middle East. 2007, at http://www.internetworldstats.com/stats5.htm.
• Haklay, M. & C. Tobón: Usability Engineering and PP GIS: towards a Learning-improving Cycle. 2003, online located at: http://www.casa.ucl.ac.uk/muki/pdf/Haklay-Tobon-URISA-PPGIS.pdf.
• Kingston, R., Carver, S., Evans, A., Turton, I.: Virtual Decision Making in Spatial Planning: Web-based Geographical Information Systems for Public Participation in Environmental Decision Making. 1999, at: http://www.geog.leeds.ac.uk/papers/99-9/index.html.
• Madar Research Group: Online population in Arab world exceeds 26 million in 2005. 2006, at http://www.ameinfo.com/96622.html.
• Steinmann, R., Krek, A., Blaschke, T.: Analysis of Online Public Participatory GIS Applications with Respect to the Differences between the US and Europe. 24th Urban Data Management Symposium (UDMS), Chioggia, 2004, at http://www.iapad.org/publications/ppgis/udms%20paper_2004_last.pdf.
• Talen, E: Bottom-Up GIS: A New Tool for Individual and Group Expression in Participatory Planning, Journal of the American Planning Association 66(3), Chicago, 2000, pp. 279-294.

GIS and the Influence of Neogeography

Jim Baumann
ESRI
380 New York Street
Redlands, CA 92373-8100
United States
jbaumann@esri.com

Consumer-oriented map visualization applications, such as Google Earth, Microsoft Virtual Earth, and others, contribute significantly to increasing the general understanding of geography and geographic awareness.

However, GIS methodology takes a map far beyond the simple physical view and provides unique insight by layering information—by drilling down and making visual connections about an area that are impossible to comprehend by conventional means. GIS is a unique tool for synthesizing information because it can correlate data that seemingly has no relationship—data connected by location alone.

The Rise of Volunteered Geographic Information

Digital map viewers provide scenes of the entire planet that have helped reignite an interest in geography worldwide. An aerial view of our home or place of business and the surrounding areas, for example, provides us with an expanded view of our community geography and helps us better understand even those things that are very familiar to us. Other products, like automobile navigation systems and computer-based travel map programs, also play an important role in sustaining our interest and abilities in basic geographic reckoning. The amount of geographic data available from these applications is extensive. And, the variety of users of these applications is equally extensive, ranging from anyone with a little curiosity about a particular location to a professional researcher.

Volunteered geographic information (VGI) is another manifestation of the rising interest of the layperson in compiling georeferenced data. This is considered an assertive method of collecting geospatial information as opposed to the authoritative method that government agencies and private industry employ to collect data. The wiki-genre site Wikimapia is a good example of VGI. It encourages participants to post comments about georeferenced locations. On the Flickr Web site, users can upload photos related to specific locations, while OpenStreetMap is an international effort to create a free source of map data through the efforts of volunteers.

Says Jack Dangermond, president of ESRI, “While much of the current VGI on the Web represents casual observations or assertions about a place (e.g., the neogeography phenomenon), conceptually speaking, VGI can also be data collected by traditional authoritative source organizations and agencies and shared openly on the Web. This is basically the GIS concept of spatial data infrastructure [SDI], where multiple organizations share their data and services with each other across the Web.”

Emerging Technologies Provide Greater Opportunities for Analysis and Understanding

GIS is a sophisticated technology with a rich information model and data management infrastructure. It integrates thousands of tools for cartography, visualization, and spatial analysis and supports many forms of customization for a variety of workflows. The Web mapping/visualization tools developed by Google and Microsoft provide very fast, easy-to-access views of images and maps. These viewers are highly optimized for rapid search and display but are not suited for the more complex work commonly performed by those using a full GIS.

KML, Google’s markup language for geographic data, was adopted by the Open Geospatial Consortium, Inc. as a standard. A wide range of applications can create and consume KML, and these files can be found via Web search. This allows people to easily perform simple mashups for their own interest and use.

ESRI’s new ArcGIS Server 9.3 improves on the ability to author and publish KML-enabled services. The ArcGIS user can now publish data for standard client viewing applications such as Google Earth, Google Maps, and Microsoft Virtual Earth. This allows the mashup of information-rich GIS databases with the extensive basemaps hosted by Google and Microsoft. In addition, ArcGIS Server 9.3 publishes service directories, which store, organize, and provide access to information in HTML that can be indexed by Web search engines, allowing another way to discover and present data. Also, the new ArcGIS Server JavaScript, REST, and Flex APIs released by ESRI allow users to mash up Web content with GIS services.

Engineering the technologies like ArcGIS and Google Earth to leverage each other provides interoperable benefits for both the GIS professional and the occasional viewer. For example, GIS users could use VGI data to supplement their analysis and data compilation efforts or associate the observational information with other data layers for query and enrichment of the GIS. Geotagged photos could be used to enrich the multimedia dimension of a GIS, and local government could include VGI comments in public policy debates.

“Geospatial data and tools are essential in almost everything we do as humans, and over the past few years they have become accessible to virtually all of us on the well-endowed side of the digital divide,” says Michael F. Goodchild, professor of geography at the University of California, Santa Barbara. “We have seen volunteer initiatives such as Map Action and the GIS Corps playing an important role in disaster response, and other volunteer activities are providing open sources of basic map information in communities that have never previously had access.”

The 3D Model and DEM Uncertainty using GIS

Khairul Amirin
Student
Forest Survey and Engineering Laboratory
Malaysia

Mohd Hasmadi
Senior Lecturer
Forest Survey and Engineering Laboratory
Malaysia


Abstract
The demand of GIS capabilities in resource management and planning is emerging, promising a large scale influence on how our geographic features are spatially distributed. The visualizations of the geographical features in three dimensional (3-D) are part of the result of a GIS application available for management and planning purposes. This paper, presents a procedure and results which were obtained from the generation of a 3-D model and estimated uncertainty of an elevation data in creating a DEM of the UPM’s Ayer Hitam Forest Reserve (AHFR). The forest reserve has been granted for 80 years by the Selangor government to be managed by the Faculty of Forestry, UPM since 1996, as an important ‘outdoor laboratory’ for teaching, practical research and extension activities related to forestry and environmental programmes. The databases of AHFR developed by the Faculty were further processed in the ArcGIS 9.0 version in order to make the data format usable, and finally, a 3-D model representation of the area was generated. Based on the 20 m DEM resolution analysis, the RMSE result for uncertainty estimation was 0.33 respectively. On the one hand, the final result was a 3-D model flexible enough to view and render the AHFR from any perspective including the distribution of soil series, hydrological networks, road networks, etc. On the other hand, these results were also useful in supporting the development programme of AHFR as a research forest for UPM.

Introduction
The 3-D GIS refer to geographic information that is viewed in three-dimensional perspectives. The 3-D images represent images in x, y and z (vertical) coordinates, viewed in stereo, and approximating the true Earth’s features. Digital elevation models, also known as DEMs are frequently used by researchers in environmental analyses to create both traditional and unconventional three-dimensional views from real-world data. Nowadays, geographic features displayed from elevation and depth values are widely used to reveal the earth’s surface and expose its features such as hill slopes, terrace, watershed process, etc. In addition, every earth surface can be identified by specifically geometric properties related to its linear, area and relief properties (Mohd Hasmadi and Kamaruzaman, 2006).

The 3-D GIS, with a continuous volumetric data structure and appropriate analytical function, is a tool to integrate a variety of data source, store all available information about a portion of the earth’s crust and operate on solid bodies as discrete entities. But the most important advantage of using 3-D displays is the way they appeal to our brains and eyes so much so that most of current forest management and landscape planning are relying on information system, such as that pertaining to the capacity assessment of the potential location for development of eco-tourism sites. As such, the development of the 3-D GIS does provide a compatible functionality and performance whereby the spatial information services will evolve into the 3-D environment (Zlatanova, et.al, 2002). According to Gonzalo and Antonio (2000), the 3-D visualisations provide some assistance to human information processing, enhancing mental visualisation and the comprehension of 2-D and 3-D spatial relationships and spatial problems. However, scientific research often makes use of sophisticated visualisation techniques in 3-D representations to enhance the interpretation of the content, logic, and sensitivity of natural resource analytical models (David and Joseph, 1997). A 3-D modelling is the creation of 3-D computer graphics based on wire frame modelling via specialized softwares. Computer visualization is spreading fast. Its appeal is obvious where visual information is processed and absorbed by human brains much more efficiently than textual, numerical and even diagrammatic data. The technology of computer graphics has been expanding for decades, but the current race to push the limits of visualization may carry profound implications to GIS users, changing expectations for more realistic and interactive 3-D visualizations.

Currently, Ayer Hitam Forest Reserve (AHFR) maps are only available in 2-D views. Thus, this study is carried out to generate a 3-D model of the AHFR using the Arc GIS software and estimations of the elevation data point in DEM. This way, the whole 1,248 ha. of the forest area is becoming more useful, attractive and easy to understand with the 3-D model for development programmes, such as the allocation of potential recreational area within the AHFR (Lim, 2004). From a hydrological perspective, river flows and catchments areas can also be easily determined from the 3-D map. The scientific value of this study was to provide a basic 3-D model of AHFR for future research purposes such as determining soil erosion factor, water catchments area, eco-physiology of plants as well as the aspect of wind flow through the hilly area. In this exercise several layers such as topography, elevation and soil series maps were developed in 3-D perspectives. Granted that the use of maps and other related information is useful as it is, but with the development of the 3D model, the geographical features can be made more attractive and useful for users to understand better the topography of AHFR. Beside the DEM generation, the uncertainty of DEM was estimated and evaluated in order to determine the differences between a GIS spatial map and actual ground survey data.

Study Area
The Ayer Hitam Forest Reserve (AHFR) is located in the state of Selangor, Peninsular Malaysia (Figure 1) at Latitude of 2°56’N - 3°16’N and Longitude of 101°30’E - 101°46’E. AHFR is a logged over forest and has yet to reach fully rehabilitated state. The forest was allocated as an educational forest by the Selangor State at a Selangor State Council Meeting held on 22nd June 1994 (Kamaruzaman and Mohd Hasmadi, 1999). Being categorized as a research and educational forest, no future logging is permitted in the AHFR. Two years later, the Selangor State Government had awarded the forest to the Faculty of Forestry to be used and managed for 80 years beginning 1996. Classified as a disturbed Kelat-Kedondong-Mixed Dipterocarp type forest (Faridah Hanum, 1999), the forest is the only remaining lowland forest in the State of Selangor. Paiman and Amat Ramsa (2007) reported that 430 species of seed plant taxa in 203 genera and 72 families were found in this forest. The general topography consists of largely rolling, flat areas broken by the two hills of Permatang Kumbang and Sarang Kuang . It has a maximum elevation of 233 meters and is 202.5 meters above sea level.

The AHFR area is about 1,248 hectare. It is divided into 6 compartments namely compartments 1, 2, 12, 13, 14 and 15. The average temperature is 26.6º C and the relative moisture is 83%. The two main rivers flowing here are Sungai Rasau and Sungai Bohol. The geological type in this forest is igneous rock with granite as the main component. Figure 1 shows the study area.

Materials & Methods
The main data used is the digital map of AHFR. Then, the digital map was converted into the Arc GIS format (*.shp). To support the digital data, the topographic map of the scale 1:10 000 from the Department of Survey and Mapping, Malaysia was used as reference to determine the distance, forest road and the boundary. The soil series map was acquired from the Agricultural Department of Malaysia. The scale of the soil series map is also 1:10 000. To create the 3-D view, a DEM was generated in GIS by draping the 2-D topographical map.

Methodology
Draping is often performed solely for purposes of visualization. ArcGIS 9.0 version was used to generate the 3-D model of the forest area. The ArcScene module was used to vary the view of the model. Contour and soil series maps were created by a digitising process which has been done via on-screen digitising. Layers were generated from the selected features. Each layer has been determined as to what it represented and from this separate layer files were generated. In editing and adding values several layers were added such as spot height, road, river networks and forest compartments. A new ArcGIS project was thus created, and the data sets are added later into the ArcMap project file format (.mxd.). For all-features layers the coordinate’s system Universal Transverse Mercator (UTM) projection was set to ensure that they are easily geo-referenced. Prior to this, ArcMap can set the coordinate system for a data frame. Layers added to the map will automatically transform to projection. After that, shapes and attributes of a layer may be edited regardless of the coordinate system it was stored in.

The contour lines were checked to ensure that the height information was accurately linked to the line feature that they represented. The feature of spot height was also checked for its consistency with the height information shown in the attributes table. From these two features a TIN was created. A DEM feature was generated from a 3-dimensional elevation with values (z-values) stored within the feature's geometry. Besides geometry, the feature may have attributes stored in a feature table. The ArcScene was used for generating DEM from TIN. The cell size was 20 m X 20 m. In this case, 3-D map was developed for contour, slope and elevation and soil series layers. After 3-D maps had been created, they were exported from a map document to an industry-standard JPEG file formats. The image was exported to JPEG format because JPEG formats are compressed image files. It can support 24-bit colour and are a good choice for use on the web because it provides control over output quality and size and can be more compact than many other file types.

Estimation of the DEM uncertainty
The topographical contour lines of the map are at 20 m intervals and were digitized into GIS. The contour lines were assigned an attribute value according to their height in meters above the sea level. The DEM was generated using TIN and 30 spot heights and stored in a computer added design (CAD) file. The cell size was 20 by 20 meters. Adding the height information to the contour lines was the most time consuming stage of the process in generating a DEM. The conversion toolset in ArcGIS was used to generate the DEM. Based on the study by Gao (1997), the accuracy of a raster DEM is related to the contour density and the DEM resolution was derived as follows:



where, S stands for resolution in meters; D stands for contour density expressed as km km-2; ? is an error term related to D. Contour density was calculated by dividing the total length of contour by the size of the study area.

The elevation data points and the DEM uncertainty were then compared to estimate the differences between them. The root mean square error or RMSE (Gao, 1997; Weshsler, 1999)) statistical method was used since it was the most common way to describe the elevation accuracy of data point used to generate a DEM. The RMSE is essentially a standard deviation that assumes that the DEM errors are normally distributed, and is expressed in meters. The RMSE equation may be stated as follows:

where, yi is an elevation from the DEM, yj is the "true" known or measured elevation of a test point and N is the number of sample points.

Data collection
The data collection was carried out to collect elevation and slope data on the ground and in a GIS map. The work was carried out in three phases, namely, Phase I: the estimate elevation and slope (in GIS map), Phase II: the field data collection, and Phase III: the data analysis.

In phase I, the study site was determined on topographical map. A topographical map (1: 10000 scale) was digitized for contour and interpolated to produce a 20 m DEM. At the same time, the similar point location was determined in the GIS map and the coordinates were recorded in each sample point. The slope class of the study site was derived from the topographical map. The layout of line transects which consists of 6 lines and 66 sample points has been designed and overlaid with slope class map, and the contour map had been done. The distance of each line is 100m and the distance of each point is 20m.

In phase II, the data collection was carried out on the field based on the line transect designed in phase I. The base line for the transect lines was 100 meters long (bearing 280 degrees) off 20 m of the tie point of Sg. Rasau branch. All 6 transect lines were established by bearing 190 degrees. After measurements were taken at every point of elevation and slope, the data were then recorded in GPS and the slope values were taken using the clinometer. At the third phase, all collected data from both tasks (phase I and phase II) were keyed into the computer for further analysis. The SPSS software was then used to analyse all the collected data. The linear regression was used to calculate the value of the differences between the estimated elevation and slope from the map with the measured elevation and slope on the ground.

Results and Discussion
The result of this study is presented in Figure 2 showing that the creation of the 3-D is possible within the limitation of the quality of a contour data. However, this model has been improved by draping the vehicle road, walking trail, rivers and forest compartment layers as feature classes onto the DEM. In the 3-D visualization, the highest point of the forest area was determined at 202.5 meters which is located in compartment 15. The surface of the forest can also be determined by looking at the 3-D model. Another advantage of the 3-D visualization is that we can simply determine the flow of the river. In fact, and in this particular case, the catchment boundary can also be delineated. Given the available quality of the layer files, the generated 3-D model may be considered as a good representation and may be further improved and used in other applications that are specific to the AHFR as a research forest.

The slope class distribution in the 3-D view is shown in Figure 3. The brighter colour indicates the flat area while the darker colour indicates the higher slope. Five range classes were used to classify the slope class which are 0-0.14%, 0.14-0.61%, 0.61-1.47%, 1.47-3.18% and 3.18-7.44%. Meanwhile, the soil series in a 3-D illustration is shown in Figure 4 indicating a clear distribution zone of the soil series in the AHFR, namely, the Serdang-Bungor-Munchong, Serdang-Kedah and Tanah Bercerun. Figure shows the 3-D view of the slope class distribution for the AHFR





The contour density in the entire study area is 10.16km km-2, thus the RMSE of the DEM created for the study area is 0.33. This value is based on the 20 m DEM resolution. Figures 5 show the differences between measured and estimated data of the slope and elevation. In particular, the results indicate a linear relationship with the measured data. The maximum and minimum data measured for slope and elevation in the study area were also observed. The maximum value for slope was 67 degrees (estimated) and 68 degrees (measured) respectively while the minimum value is 3 degrees (estimated) and 5 degrees (measured) respectively.



Most of the measured and estimated data collected were less than 30 degrees while elevation analyses showed that most of the data collected were ranged between 30 m to 70 m in height. The maximum value for elevation was 69 m (measured) and 67 m (estimated) while the minimum value was 3 m (estimated) and 5 m (measured). It should be noted that about six data items measured were similar in value, indicating that the study sites were located at six different points of elevation (6 contours level) on the ground. The maximum values indicate that for both data the measurements taken in the field were slightly higher than those estimated from the map.

The coefficient of determination (r2) values for both of the collected data in this analysis are 0.9591(slope) and 0.9587(elevation) at the .05 significance levels. These results imply that approximately 95% of the appraisal data of the slope and elevation data are attributable to variations on the ground surfaces and to the spatial data that are present in the spatial information. This shows that a relatively small difference occurs between estimated and measured data in generating the DEM model for the study area. As to the data quality issues in the procedure, it must be pointed out that they pertain to the fact that the individual data set was used at a micro level. Nonetheless, since the data were generated with the intention of capturing and converting a topographical map of the AHFR into a digital form, the objective of its application has been satisfied.



Conclusion
The 3-D visualization is more attractive and intelligible. Based on the result it may be concluded that the 3-D generation for the AHFR is relatively good and convincingly shows the accuracy of the DEM analysis. Slight differences exist in sloping surfaces but negligible in the case of the flat surface. However, since the differences of both maps in the study are less than 10% (slope r2 = 0.9591; elevation r2 = 0.9587) the results may be concluded as reliable for nominal maps of the 1: 10 000 scale. The technique of creating the 3-D model presented can thus be used as a basic procedure for creating other information in the 3-D model. A crucial advantage of the perspective view of the 3-D model is that information items such as river network, road, slope and elevation can be viewed effectively from any angles. As such, it is recommended that future research integrates remote sensing imagery as a spatial layer, and this can be done by utilizing the “image drape” technique found in the Erdas Imagine software. The 3-D model is not only useful to users, but also to the prospect of conducting many studies such as determining the soil erosion, catchments area and wind flow direction through the hilly area. Finally, this study has proven that with the extension module the GIS may be a capable and very useful tool to anyone who needs to generate quantitative variations in developing a 3-D model.

References

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