The Implications of a City`s layout's Visibility on Wayfinding Performance (preliminary study) Itzhak Omer and Ran Goldblatt Tel Aviv University, Israel ICA Workshop on Geospatial Analysis and Modeling 8 July 2006, Vienna, Austria

Background: A city`s layout's visibility can be defined as the number and structure of visual fields and their integration. The visual integration of a city`s layout has the potential to effect the quality of spatial knowledge acquired by human subjects while navigating through the city and their ability to construct a cognitive spatial representation of it. Previous research, especially from the Space Syntax theory, focuses on the effect of one property of visual integration: the topological depth between visual fields (connectivity, integration and intelligibility between the axial lines) and less on the overlapping between them

The aim of the research: Examine how the overlapping between visual fields affects wayfinding performance in a 3D virtual city. more specifically: the aim is to examine how the overlapping between visual fields affects the ability to acquire (ordinal) procedural spatial knowledge through direct experience (primary learning) and apply this knowledge in given wayfinding tasks. This examination has been done with respect to the topological depth between the visual fields.

Methodology: a 3D Virtual Environment (VE) of an imaginary small scale urban area of about 0.25 Square Km was built using Skyline® 4.6 software Seven landmark elements with unique typical textures were used in the experiment

Legend: 1- Clinic 2- Commercial center 3- Tree 4- School 5- Historic building 6- Restaurant 7- Square Participants were asked to observe a recorded `tour` around the city Phase one: A learning phase The route never went through the shortest path between any two examined landmark elements:

Participants were asked to mark on an anchored map the exact location of the seven citys elements. This allowed us to examine the quality of the participant's configural spatial knowledge. start square tree The map on which participants were asked to mark the exact location of the elements for revealing level of configurational knowledge A sketch map examination:

Length of the visual chain Common visible elements TargetOriginTask 1 (square) 1Tree (ST) School1. 1 (historic building or square) 2School (RS) Restaurant2. 1 (school or restaurant) 3Square (HS) Historic building3. 3 (restaurant and square and tree) 0 Commercial center (HC) Historic building4. 2 (square and tree) 0 Commercial center (CC) Clinic5.5. Five wayfinding tasks were given to participants. They were chosen with respect to the overlapping between the visual fields and with respect to the topological depth between them. Phase two: A wayfinding task phase

Analysis and documentation: 2.Mean distance error: we calculated for each participant the mean distance error of the elements` location on the map he/she drown in relation to their real location 1.Length of route: We estimated ease of task completion using the length of the taken route during the wayfinding task relative to the shortest available path Evaluation of success: = shortest paths = taken route A A A = real location A = estimated location = distance Example (one participant):Example (one task):

1. The effect of the visual integration on procedural (ordinal) knowledge Results

Examination of the relation between the performance of the participants was found to be correlated (R 2 =0.82) with the accuracy of the landmark locations on the maps drawn by the participants at the beginning of the wayfinding task phase. 2. The effect of visual integration on configurational knowledge

preliminary Conclusion and further research 1. A high degree of overlapping between visual fields and a short topological depth between them contribute to the acquisition of a more accurate procedural and configurational knowledge. 2. The results of the research encourage the use of complementarily methods for analyzing the City`s layout's Visibility which takes into consideration the overlapping between visual fields in addition to the topological depth between them. A multidimensional topological analysis is an example for such kind of a method.