Virtual City Design Based on Urban Image Theory

Transcription

1 The Cartographic Journal Vol. 42 No. 1 pp June 2005 # The British Cartographic Society 2005 REFEREED PAPER Virtual City Design Based on Urban Image Theory Itzhak Omer, Ran Goldblatt and Udi Or Department of Geography and The Human Environment, The Environmental Simulation Laboratory, Tel-Aviv University, Ramat-Aviv, Tel-Aviv, 69978, Israel omery@post.tau.ac.il; ran@eslab.tau.ac.il; udi@eslab.tau.ac.il This paper aims to evaluate what effect applying residents urban image to virtual city design (a real time virtual model of an actual city) has on wayfinding performance during flying-based navigation mode. Two experiments were conducted to compare two virtual city designs using the virtual model of Tel Aviv city. One design included highlighted urban elements from the residents urban image, while in the second design no highlighted elements were included. The experiments proved that using the elements of the residents urban image in a virtual city design enhances the performance of all participants in the wayfinding tasks, and especially those with a low level of spatial knowledge. Analysis of the trajectory patterns and the verbal reports of the participants during navigation showed that the urban image design facilitates a more intensive use of a position-based strategy, in addition to the path-integration wayfinding strategy, which was found to be dominant in the virtual model without the highlighted urban image elements. On the basis of these findings we propose principles for designing virtual cities from a perspective of wayfinding. Keywords: geovisualization, virtual cities, urban image theory, wayfinding strategies, Virtual Environment design 1. INTRODUCTION A virtual city is a real-time model of an actual city that enables the user to walk through or fly over a certain area. Such models have been constructed recently for many cities, e.g. Los Angeles, Philadelphia, London, Barcelona, Glasgow, Tokyo and Tel Aviv, thanks to improvements in geovisualization tools (computer graphics, GIS etc). Currently, the research in this field tends to concentrate on the models technological dimensions and their implementations for supporting urban planning and various decision-making processes (Fisher and Unwin, 2001; Laurini, 2001; Jiang et al., 2003). However, with a few exceptions, which include a conceptual discussion on cognitive issues for virtual environment design (Slocum et al., 2001) and a consideration of wayfinding aspects in a virtual cities design (Bourdakis, 1998; Omer et al., forthcoming), little attention has been paid to the wayfinding difficulties that characterize these models and their design implications. Virtual cities are unique when compared to other geographical representations of the city, such as maps, aerial photographs or static 3D models, due to the real-time movement within them, which is characterized by high speed of locomotion, different 3D viewing perspectives and varying geographical scales. These characteristics of virtual cities could entail non-intuitive and unfamiliar user behavior, resulting in wayfinding difficulties for the users i.e. difficulties in locating their current position and finding their way to a desired location. In addition, users may experience difficulties of orientation just as users of any desktop virtual environment (VE). These difficulties are related to the lack of presence, i.e. the participant s sense of being there in the virtual environment (Slater et al., 1994), perspective distortions and the use of standard input devices that might affect performance during navigation (Darken and Sibert, 1996; Ruddle et al., 1997; Harris and Jenkin et al., 2000; Whitelock et al., 2000; Jansen et al., 2001). Enhancing wayfinding performance in a virtual city design aims to help city residents transfer their image and spatial knowledge from the real city to its virtual model. Lynch s urban image theory (Lynch, 1960) could be an appropriate tool to attain this goal since it enables us to see how city residents perceive their city. The urban image, or city image, is actually the overlap of many individual images, Lynch claims which are the result of a two-way process between the observer and his environment. The environment suggests distinctions and relations, and the observer [ ] selects, organizes and endows with meaning what he sees (Lynch, 1960, p. 6). The underlying assumption is that the city image, which is obtained from sketch maps or interviews, provides information on the imageability of the city elements. Lynch defined imageability as a quality in a physical object which gives it a high probability of evoking a strong image in any given observer (Lynch, 1960, p. 9). In discussing real city design by these elements, Lynch suggests they can be classified conveniently into five types of elements: paths, edges, districts, nodes and DOI:

2 2 The Cartographic Journal landmarks, which should be patterned together to provide an imageable environment. Though Lynch s urban image theory has not been applied to the design of a virtual city, its efficiency for enhancing wayfinding has been proved in many other VE studies. It was found that route-finding performance of the VE userimproved improved when familiar objects were placed within the VE than when no landmarks were used (Ruddle et al., 1997). In addition, the importance of the relations between Lynch s element types for navigation enhancement is emphasized in VE studies. These relations have been found to help users structure their spatial representation in differing scales (Vinson, 1999; Darken and Sibert, 1996). While these studies do not involve real large-scale VE, Al-Kodmany (2001) used Lynch s theory as a framework when combining Web-based multimedia technology to assist residents and planners in visualizing a community in Chicago by visualizing selected areas that were selected as most imageable by the residents themselves (Al-Kodmany, 2001, p. 811). The aim of this paper is to study the effect that a virtual city design based on residents urban image has on wayfinding performance. To that end, two virtual city designs of Tel Aviv city were compared. (The virtual model of Tel Aviv city will be referred to in this paper as virtual Tel Aviv.) The first design did not include highlighted urban elements selected from the residents urban image, while in the second design highlighted elements were incorporated. The conclusions of this study also have operative implications on the construction of virtual cities. One of the important decisions in this process is the selection of the urban objects to be presented by 3D models within the virtual environment. This decision also has an economic aspect since constructing 3D models, mostly with the photos of the facade textures, involves vast amounts of money and time. In cases where the urban image design is found to enhance wayfinding performance, the urban image framework can serve as an appropriate tool for this selection. For example, the current virtual Tel Aviv model does not yet include 3D models of buildings, and, therefore, this study can clarify whether these buildings could be selected based on the urban image elements. In the next section, we describe virtual Tel Aviv and the experiments and the methods used for their documentation and analysis. We go on to report the findings of these experiments. On the basis of these findings, in the fourth section we suggest principles of using residents urban image in the design of virtual cities. In the last section, we summarize theresultsofthestudyandnotesomefurtherwork. 2. METHODOLOGICAL FRAMEWORK 2.1 Virtual Tel Aviv Virtual Tel Aviv offers the user a real-time flying-based navigation mode over Tel Aviv city, an area of about 50 square km. The model was built in the Environmental Simulation Laboratory at Tel Aviv University with SkylineH 4.5 software. Using this software, we interpolated a CDTM point layer (in a resolution of 50 m) Cof Tel Aviv into a raster layer of the city s altitudes. Then we added an orthophoto of Tel Aviv (in a resolution of 25 cm), and using these altitudes, we established a 3D visualization of the city terrain. Afterwards (in experiment 2) we added GIS layers of the Tel Aviv urban image objects (paths, landmarks, nodes, edges and districts) as shown in Figure 1. These objects were highlighted by colour C(different colours for linear and non-linear objects) and labels (as text next to the object). In order to construct the urban image of Tel Aviv, C32 residents of the city were asked to draw a map of Tel Aviv and to draw the dominant elements in it (no more than C15 elements). We decided to limit the number of the elements to 15 so that only the most imageable elements would emerge, as well as to create a common understanding of the assignment for all participants. We then gathered the data from the individual sketch maps into one aggregate map representing the residents urban image of Tel Aviv. In order to create a representative urban image, only those elements that appeared in more than two sketch maps were included in this aggregate map. 2.2 The experiments Twenty-four participants (15 male and 9 female), 26 to 58 years of age, took part in the experiments. None of these participants had taken part in drawing the sketch maps from which we evaluated the urban image for use in the experiments. All participants declared they knew the city of Tel Aviv well. To make sure they were familiar with the city, a list of nine well-known locations in Tel Aviv was read to them, and they were asked whether they knew their exact locations. Two experiments were conducted by dividing the participants into two groups of 12. In experiment 1, the design of the virtual model did not include any highlighted landmarks, while in experiment 2 the design of the virtual model included highlighted urban elements from the residents urban image. (In this experiment we added the residents` urban image as a GIS layer.) The participants of both experiments had to complete the following steps: Phase 1: Each subject was provided with an A4 sheet of paper, on which the municipal borders of Tel Aviv were marked. In order to give the respondents reference points, we also marked two very familiar landmarks along the coastline of Tel Aviv the new Tel Aviv port and the old Jaffa port. The main national highway (Ayalon Highway) was also marked (Figure 2). All participants were given the same instruction: Please mark each of the above sites Con the map, as accurately as you can. The nine sites were those which were read to them at the beginning of the experiment, and they include six locations in the wayfinding tasks (the clock tower in Jaffa, the Israel Museum, Habimah National Theater, City Hall, Yehuda-Maccabi Street and the central bus station) and three other central locations (the Tel Aviv Museum of Art, the Azrieli mall and the railway station). The locations of the nine elements for each map given by the participants were compared to their real locations providing a mean distance error value for each participant. Such information allows us to define the spatial knowledge quality of the participants, a factor that might influence their behavior.

3 Virtual City Design Based on Urban Image Theory 3 Figure 1. (a) The components and (b) the interface of virtual Tel Aviv Phase 2: Participants were introduced to the virtual model of Tel Aviv on a 19" desktop monitor at the Environmental Simulation Laboratory. We explained to them how to use the flight simulator (using the keyboard as an interaction device): moving forwards, backwards, controlling the speed, stopping, moving up scale and down Figure 2. The municipal borders of Tel Aviv and the reference points which were marked scale and Cmanipulating the viewed screen. To prevent the participants from seeing the orthophoto of the examined area (Tel Aviv), they practiced using the simulator on another area of Tel Aviv for C5 minutes, or longer if they felt (or we felt) they needed extra practice. We explained to them that they could fly at any speed and at any height they wanted. Phase 3: This phase comprised two wayfinding tasks. In the first task, participants were asked to fly to three different locations in Tel Aviv: from the clock tower in Jaffa to Habimah Theater; from the theater to Yehuda-Maccabi Street, and from there to the Israel Museum. In the second task, participants were asked to fly from the new central bus station to the city hall building (see Figure 3). In both experiments, the initial viewing angle was 90u and the viewing height was 315 meters above sea level. This setting allowed the user to clearly identify the object and its immediate surroundings. It should be noted that the two tasks differed in area covered and in initial viewing conditions: The first task included the coastline as a dominant reference object in the area where the participants began the wayfinding task. In the second task no reference object was visible in the immediate environment of the starting point (Figure 4). In addition, the areas covered by the tasks were urban areas of varying density and complexity. In each assignment, the participants were asked to tell us once they had identified the target location and to receive confirmation that it was indeed the one requested.

4 4 The Cartographic Journal geographical elements mentioned, wayfinding strategies and difficulties during wayfinding tasks. Figure 3. The two tasks given to the participants and the task locations. Arrows represent the shortest flying path from each location to the next 2.3 Methods of documentation and analysis a. Tracking movement: In order to investigate individual wayfinding performance, we recorded all the participants real-time-log data of movement (coordinates, speed, height etc.) while using the model (including the area on the interface as it was seen by the user). Such tracking enabled us to perform quantitative analysis of the trajectory patterns of participants during navigation. In order to obtain these trajectory patterns, the recorded real-time-log data was converted to GIS layers and then visualized as polylines in GIS layers in ArcGIS 8.2 environment. The statistical analysis was performed using SPSS 11.0 software. b. Think-aloud method: A think-aloud or self-report method (Golledge, 1976; Darken and Sibert, 1996; Murray et al., 2000) was implemented to reveal and understand the strategies and thoughts of the participants during the assignments. The participants were asked to verbally explain to us everything that came into their minds during navigation (strategies, thoughts, questions, internal conflict, decisions etc.). When we felt they were not descriptive enough we encouraged them to elaborate and asked them what they were thinking about. Everything they said was recorded and later analysed. Each participant s documentation was examined according to three categories: the 3. RESULTS: HOW DOES THE URBAN IMAGE DESIGN INFLUENCE WAYFINDING IN A VIRTUAL CITY? Using the data analysis of the documentation in experiment 1 (navigation in the virtual model without the highlighted elements) and in experiment 2 (navigation in the virtual model with the highlighted urban image elements), we are able draw conclusion regarding the influence of highlighted elements on the participants performance during wayfinding tasks with respect to strategies and difficulties. Although each participant used different methods for arriving at the destination objects, we can classify these techniques into two basic wayfinding strategies, common in human navigation in real environments: path-integration and position-based strategies (Loomis et al., 1999; Peruch et al., 2000). Navigation by position-based, or piloting strategy relies on recognizable landscape elements. Navigators use landmarks as cues for information on their position and how to arrive at a desired location during flying-based navigation mode. Path-integration, or dead reckoning strategy, means continued integration of largescale and angular components, allowing estimation of direction and distance. In other words, during flying based navigation mode to locations that are beyond the visual field, navigators will coincidently see single reference objects and from that object calculate the position of the target location. In general terms, in experiment 2, using the urban image design model that provided a network of locations in the observed simulated environment, participants tended to use the position-based strategy. In experiment 1, however, where the model did not include the urban image elements, participants seemed to rely mainly on the path-integration strategy. The dominance of the path-integration strategy in experiment 1 is illustrated by the fact that many participants relied on global reference elements of the city. Three main linear elements were found to be helpful while navigating: the coastline (to the west), the Ayalon Highway (to the east) and the Hayarkon River (to the north). The coastline was found to be a dominant reference line in the first task, while the Ayalon Highway dominated in the second task. This can be verified both by the verbal report (Table 1) and the trajectory patterns of the participants, which tended to run close and parallel to these reference lines (Figure 5). As can be learned from the verbal reports, these elements fill three main functions in the path-integration strategy: as anchors for indicating the general direction towards the desired location, until another strong element is found; as cues for relating their position within the frame of reference (north, west...) and as transitional cues that provide a basis for interpreting mobility and relative scale during navigation. However, since adopting such a strategy requires a high level of configurational knowledge i.e. a level of spatial knowledge that incorporates information concerning directions and the relative positions of places (Golledge, 1992;

5 Virtual City Design Based on Urban Image Theory 5 Figure 4. (a) The initial viewing point of a. the clock tower in Jaffa, (b) the central bus station Kitchin and Blades, 2002, pp ), it is often not sufficient for all the participants to fulfill the wayfinding tasks. Therefore, it seems that the participants need recognizable elements to find their way by using the position-based strategy, mainly in the later stages of the tasks when they need to leave these anchors. As a result, in cases where the recognizable elements are not available, the participants, particularly those with a low level of configurational knowledge and who use mainly a procedural knowledge, experience problems that result in poor Cwayfinding performance. Analysis of the relation between the level of spatial knowledge and the wayfinding performance in the model without the urban image elements proves this. To reach this conclusion, we assume that the Table 1. Verbal documentation of the function of the geographical objects during wayfinding tasks Function of objects Experiment 1 Experiment 2 Positional location Frame of reference Transitional I know the general direction from Milano Square to the Israel Museum I am not following any specific streets, just flying in a certain general direction. I m trying to find some landmark that I know for sure like a street that will get me fully oriented. Here s the David Intercontinental Hotel I ll take a right there. Judging by these towers, this must be Pinkas Street. I don t want to get too far away from the beach, because otherwise I wouldn t know where west is! If that s the beach, then that s west and this is north. Once I know where Ayalon Highway is, I ll know which way is north. I can identify the Ayalon Highway and I m going parallel to it rather than over it. I want to fly over Ayalon Highway till I ll identify Azrieli mall. I want to drive north to the Opera Building and then veer to the east this is what I do when I drive there. Here is Rotschild Blvd so it should be somewhere in this area. I can see the label of the Shalom building. I ll take a left turn here and this will take me to the area I want.... O.K! Here is the label Azrieli so I ll turn on Kaplan St and continue straight till I reach Ibn Gvirol St. Here is the label of Ayalon Highway. I ll turn left so I ll be heading north. If this is Weizman St. and this is Dizingoff St, so this is north. O.K. lets leave the coastline and head east. I recognize Rabin Square and the city hall. So it should be much more to the east. I m flying in a general direction following main streets that I don t really recognize.... I can see the label of Alenbi st you know what? I will follow this street. I feel like I m driving a car... I ll just follow this road.

6 6 The Cartographic Journal Figure 5. The influence of urban image design on track patterns of the participants: (a) without design, (b) with design; (I) the coastline as reference line, (II) Ayalon Highway as reference line accuracy of the sketch maps (measured according to the distances between the locations drawn on the sketch maps and their real locations) serves as an indicator for estimating the quality of knowledge, while the length of the flying path serves as an indictor for wayfinding performance, as a longer path may indicate that the participant didn t know the target s exact location. A significant positive correlation was found between the distortions in the sketch maps and the length of the flying path (a Pearson correlation of 0.615, p50.033). This correlation shows that participants who had a more accurate representation of the city were able to navigate more efficiently in the virtual model. This fact can be related to the difficulty participants had in recognizing familiar objects from a bird s-eye view, a view that characterizes a flying-based navigation mode, making it hard for them to evaluate spatial relations needed for orientation. In addition, it is clear from the experiment that the users not only are unaccustomed to seeing the shape of city objects from above (without its 3D familiar shape), but they also have difficulty getting used to their proportions (Table 2). Because of this, when an object or an area has a familiar shape, a city square for example, it is extremely difficult for the user to identify it without seeing its surroundings (or a label with its name). For example, many participants experienced problems distinguishing between CHamedina Square and Dizingoff Square (well-known squares in Tel Aviv) despite the fact that the ratio between these two areas is about 2 : 1 (approximately 850 sqm and 450 sqm, respectively). Participants also experienced problems estimating speed of movement, which caused them to

7 Virtual City Design Based on Urban Image Theory 7 misjudge the location of objects, as they thought they had already gone past them, or not yet approached them. Wayfinding strategies changed significantly in experiment 2. Adding the imageable objects to the model provided a more legible and recognizable environment. This environment provided the conditions for adopting a position-based strategy, i.e. the labeled objects served as positional information for a location, or a network of locations, for evaluating the relative distances between locations, as we may expect from a flying-based navigation mode. Therefore, in addition to, and in several cases even instead of, relying on dominant spatial features that are easily identified from a bird s-eye view, the participants in experiment 2 continuously updated their position using the highlighted elements, usually elements with which they were familiar from their everyday experience in the city. The transformation from the path-integration strategy to the position-based strategy in the second experiment can be verified when comparing the documentations of the experiments: the verbal reports (Table 1) and the trajectory patterns of the participants (Figure 5). The verbal terminology used in each strategy is also different. While in the first experiment (without the urban image design), the terminology used was based mainly on descriptions of the reference points/lines, the participants in experiment 2, who used the position-based strategy, relied mainly on the relations between the observed elements. As illustrated in table 1, the urban image elements function as aids for updating or calibrating the users position (e.g. If I m at location X, I can go on from here towards the target location ), as well as for confirmation (i.e., This element should be X [ ] yes, here is the label telling me it is X ). The trajectory patterns also illustrate this transformation: When the urban image labels were available for the users, they felt confident enough to leave the reference lines much sooner than participants in the first experiment, where no highlighted elements were available (see Figure 5). Thus, the availability of recognizable urban features enables a continuous update of the current position during navigation, when the identified locations function as a network of locations or as positional information for confirming location. The urban image elements available improved wayfinding performance because with them the participants had fewer difficulties in recognizing familiar objects and in evaluating spatial relations between them (which is needed for orientation). When comparing the two experiments, in the test where the design of the virtual model used urban image elements, wayfinding performance was significantly improved. The total length of the flying paths in experiment 1 was 52,043 mc (std. 30,774 m) while in experiment 2 it was 15,136 m. (std. 9,467 m). A T-test confirmed these difference (t53.976, df5(22), p C). However, an examination of the relation between the level of spatial knowledge and the wayfinding performance in experiment 2 shows an uncorrelated relation (a Pearson correlation of 0.043, p50.895). Notice that this relation was significantly correlated in experiment 1.This means that the urban image design of the virtual city improved the performance of all participants, especially those with a low level of spatial knowledge. This finding is an additional indication that those with low level of configurational knowledge depend heavily on covering the area in which they are navigating with recognizable geographical objects. To summarize, the urban image design enables a more intensive use of the position-based strategy, in addition to, and in several cases even instead of, the path-integration wayfinding strategy, which was found to be a dominant strategy when the model design did not include the highlighted elements. Based on these findings, we can conclude that Lynch s urban image theory can be applied in the design of virtual cities due to its capabilities to enhance wayfinding performance. In suggesting principles for such design, in the next section we present a comparison between real city and the virtual city concerning the imageability of the urban elements. 4. THE RELATION BETWEEN THE REAL CITY URBAN IMAGE AND THE VIRTUAL CITY IMAGE: IMPLICATIONS FOR DESIGN Figure 6a presents the imageable elements of the urban image of real Tel Aviv city, namely, the objects that Table 2. Verbal documentation of difficulties during wayfinding tasks Verbal report of experiment 2 Verbal report of experiment 1 difficulties I feel that I m getting lost! Which way is north?? If I can find the north, it ll be much easier. Lack of orientation I couldn t identify Dizingoff square without the label! I know the cinema should be here, but I can t identify it! It s difficult when it s not three- dimensional! In Tel-Aviv all the roads look the same... this is why I m looking for the labels. I can see a junction, but which one is it? I decided to follow Ayalon Highway, as it s a major road, and it s much easier to identify it on the air- photography. I understood the area I thought is the square is actually Habima Theater. Is this what Tel Aviv looks like from above??? What is this big building? This is Hamedina Square?... No, no this is Dizengoff Square. But wait a minute! Which square is this?? It takes me time get used to the proportions... the city seems so big suddenly! Identification Space-time scale

8 8 The Cartographic Journal Figure 6. (a) The urban image drawn by Tel Aviv residents appeared in the individual sketch maps. Figure 6b presents the urban image of virtual Tel Aviv established by gathering the objects verbally mentioned (while looking for an object or viewing one) by the participants in experiment 1, who performed the wayfinding tasks in the model without the highlighted urban image elements.

9 Virtual City Design Based on Urban Image Theory 9 Figure 6. (b) The urban image of the objects mentioned during wayfinding tasks As one can gather from the visual comparison of the two images, both are essentially similar. A positive correlation between the appearance frequency of the urban-image elements in the cognitive maps and the appearance frequency of these elements when mentioned in the wayfinding tasks, verified this conclusion (a Pearson correlation of 0.75, p50.000). The elements that are characterized by a relatively high imageability during the

10 10 The Cartographic Journal Figure 7. Classification of the imageable elements of real and virtual Tel Aviv, according to Lynch s element types wayfinding tasks are mainly those with high physical identification; that is, they can be easily identified from a bird s-eye view. The elements which were found to be very useful during navigation include large continuous elements, in particular the coastline, the Ayalon Highway and the Hayarkon River, as well as elements with distinctive landscapes and boundaries such as Hayarkon Park. Other elements that are easy to identify from a bird s eye view are those with unique morphology, especially city squares, which stand out in the image that emerges during navigation. Hamedina Square, Rabin Square and Dizingoff Square were found to be main nodes of that image. The elements that are characterized with a lower imageability in the virtual city are those with a low possibility of physical identification small-size landmarks that have a unique morphology from a side-view (rather then from a bird s-eye view) and districts such as the Neveh Zedek neighborhood, which has no recognizable boundaries. As a result of these differences, the image that emerges during navigation in the virtual city is more a common one that is one formed by elements mentioned by most of the participants, a fact to which the high frequency of the appearance of elements testifies (Figure 6). In addition, as illustrated in Figure 7, the paths and nodes are relatively more imageable during navigation from a bird s-eye view, while the landmarks, districts and edges are relatively less imageable than in the real city image. The close similarity between the real and the virtual urban images strengthens the hypothesis that Lynch s urban image theory enables users to transform their spatial representation of the real city to its virtual counterpart. Moreover, it may also confirm that a preconceived real urban image can be integrated into, or participate in, the users representation that emerges during navigation i.e. they call on information they have from the real urban image to help them navigate in the virtual environment (see Figure 8). Thus, the integration of the real city s urban image into the virtual model enables users to identify imageable elements which are seen in the real city, even if they have a low physical identification level from the bird seye-view, and also to use elements that are particularly imageable from the bird s-eye-view during flying based navigation mode. Figure 8. Distinction and integration between real and virtual city representations Comparing the real and the virtual city images provides information as to which elements should be highlighted. As mentioned in the introduction, this selection is one of the decisions that has to be made when creating virtual cities with the aim of enhancing wayfinding, and economical aspect must also be taken into account. Selecting only part of the buildings to be constructed is advisable, especially when dealing with large cities with an enormous number of objects. Therefore, the distinction between three groups of objects those imageable particularly in the real city, those imageable particularly in the virtual city and those that are common for both could be used for selecting the most appropriate objects for emphasis in order to enhance wayfinding performance. One possible use of this distinction is to give priority to the group of particularly imageable elements of the real city, which will help the virtual city s user identify them. Another possible use is to focus on the integration between these three groups, where the common imageable elements can serve as a link between the particular groups. Once the selection of the objects has been made, a generalization process can be implemented for selecting which geographic objects will be presented when a new scale or perspective emerges during flying-based navigation i.e. the level of detail (LOD) in a design of a virtual model. The generalization process can be constructed taking into account the imageability of the urban elements as a source of knowledge that can be applied by generalization methods, especially those developed for GIS and 3D visualization, which are mainly driven by communication requirements, such as legibility, graphical clarity and understandability (Muller et al., 1995; Frery et al., 2004). One of the basic assumptions of Lynch s urban image theory is that the more imageable the element, the more

11 Virtual City Design Based on Urban Image Theory 11 useful it is in wayfinding in larger-scale areas of the city, while the less imageable elements are used in local-scale areas of the city (1960, pp ). Working on this assumption, the scale in which the objects should be displayed can be determined according to their degree of imageablity, which is represented by their frequency in the aggregative map. As Bourdakis (1998) points out, it is essential to refer to the context in flying-based navigation mode over urban environment, due to its varied density and complexity. For that purpose, the designer may be able to refer to the interrelations between the urban elements and their classification into Lynch s element types in the representation of contextual relations that are suggested for cartographic generalization, such as being part of a significant group, being in a particular area and being in relation with same level surrounding objects (Mustiere and Moulin, 2002). 5. CONCLUSIONS AND FURTHER STUDY The impetus behind the study presented in this paper was the need for virtual city design to deal with wayfinding difficulties experienced by the users, as well as to locate a framework by which the designer can decide which urban objects should be highlighted over the city orthophoto. The assumption of the study was that Lynch s urban image theory can serve as an appropriate framework due to its potential in facilitating the transferal of images and spatial knowledge from the real city to its virtual representation. Experiments conducted using virtual Tel Aviv proved that a design based on urban image elements improves the performance of all participants, especially those with a low level of spatial knowledge. Moreover, the urban image design facilitates more intensive use of a position-based strategy, in addition, or even instead of, the pathintegration wayfinding strategy, which was found to be a dominant strategy when the virtual model did not include the highlighted urban image elements. Furthermore, a vast similarity was found between the imageable elements mentioned during the wayfinding tasks in the virtual model (which did not include the highlighted elements) and the imageable elements of the real city that were revealed by the drawn sketch maps. Based on these findings, this paper proposes that designers of virtual cities use the similarities and differences between the imageable elements of the real city and of the virtual city as a source for generalization knowledge. This comparison provides a useful tool in the selection of elements to be highlighted, and for constructing a generalization process with respect to scale and context. To this end we are currently working at the ESLab of Tel University on building a wayfinding support system for the virtual model of Tel Aviv, based on the presented methodology. Accordingly, 3D models of selected buildings are being constructed and inserted into the virtual model. The generalization process in the developed system is based on the residents urban image of the real city, as well as on the imageable elements of the virtual one. REFERENCES Al-Kodmany, K. (2001). Supporting imageability on the World Wide Web: Lynch`s five elements of the city in community planning, Environment and Planning B: Planning and Design, 28, Bourdakis, V. (1998). Navigation in Large VR Urban Models, in Virtual Worlds, Springer-Verlag, ed. by Heudin, J. C., pp , Heidelberg, Berlin. Darken R. and Sibert J. (1993). A toolset for navigation in virtual environments, Proceedings of the ACM Symposium on User Interface Software and Technology, Atlanta, GA. Available at, Darken, R. and Sibert, J. (1996). 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