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Fisher-Gewirtzman D., Wagner, I., 2003, “Spatial Openness as a Practical Metric for Evaluating Built-Up Environments ”, Environment and Planning B: Planning and Design, Vol 30, 37-49.

Hijazi, I.H., Koenig, R., Schneider, S., Li, X., Bielik, M., Schmitt, G. and Donath, D., 2016, Geostatistical Analysis for the Study of Relationships between the Emotional Responses of Urban Walkers to Urban Spaces. International Journal of E-Planning Research, Hershey, PA: IGI Global.

Six factors that influence perceived urban density are tested: 1.  Visibility. The median visibility of each

image was computed from a depth perception map created for the study.

2.  Amount of building matter per image 3.  Amount of visible road 4.  Amount of visible sky 5.  Amount of green space 6.  Amount of vehicles The photographs were analysed according to the six parameters, and for image properties of luminosity, contrast, and r/g/b values.

The study was conducted as an online questionnaire using the Qualtrics online survey platform. The survey was an optional task at the end of the Massive Open Online Course (MOOC) “Future Cities” course run by the Chair of Information Architecture. Respondents of the questionnaire were students of that MOOC. During the questionnaire participants viewed two photographs of urban locations and had to choose which one was more dense.

190 participants from 58 different countries took part, of which 123 were male; average age was between 18-30 years old. Fig. 3 shows the rankings of the images relating to perceived urban density along a linear scale, from least to highest perceived urban density. The 12 images have the property of being high (above the grey line) or low (below the grey line) for each of the 6 tested parameters (#1-6 listed above). Initial findings suggest that visibility alone is

not enough to explain participants’ judgements. Participants reported four factors to be the most important when making their judgement: 1) number of visible buildings, 2) building height, 3) visibility, and 4) presence of green spaces. The number of visible buildings was reported as being the single most important factor when judging the perceived urban density of an image.

Towards defining perceived urban density Beatrix Emo1, Lukas Treyer2, Gerhard Schmitt2, Christoph Hölscher1 1Chair of Cognitive Science, ETH Zurich; 2Chair of Information Architecture, ETH Zürich

4 Initial results

Fig. 3. Rankings of the factors tested in the pilot study. The 12 images are categorised as having a high or low value for the six tested parameters (#1-6 listed above). The figure shows the results of the ranking of the images according to perceived urban density along a linear scale (grey line) from lowest to highest perceived urban density. Images which have a high value of a parameter are listed above the

grey line; images that have a low value of a parameter are listed below the grey line.

Fig. 2. E.g. of the analysis conducted per image. The original photograph (left) is analysed using an image segmentation algorithm (middle, parameters #2-5); the visibility properties of the image are calculated from a depth

perception map (right), parameter #1, created using the point-cloud model (fig.1).

5 Conclusion

The paper reports the findings of a pilot study designed to examine how people perceive urban density. It is a first step towards defining the parameters that are relevant for the perception of urban density. The relatively low number of images used is a limitation of the study. More and different types of images are needed to be able to test the hypothesis. The study does not test for the influence of presence of people on perceived urban density; this parameter should be accounted for in future work. We see this study as a first step towards developing a larger research agenda, where i) individual differences and ii) cultural differences in the perception of urban density are taken into account.

6 References

2 Parameters

1 Introduction

As an ever growing percentage of world population lives in cities, planning urban environments that strike a balance between accommodating a large number of people whilst retaining a pleasant atmosphere is an important issue (Eberle et al., 2014). We report the findings of an initial study aimed at identifying parameters that might be relevant for the perception urban density. The context of the study is rooted in the perception of western European cities, specifically Switzerland. We created a questionnaire study in which the role of six factors on perceived urban density is tested. The research hypothesis is that perceived urban density is the inverse of visibility (Fisher-Gewirtzman and Wagner, 2003).

3 Method overview

The question participants responded to was: “Which location is more dense?”. We gathered a basic profile of the participants through a number of questions pre- (e.g.. where they currently lived, where they grew up, age, gender) and post- questionnaire (e.g.. what factors most influenced their judgement, how they ranked the importance of those factors etc.). Photographs used in the questionnaire were 12 stills taken from a 360 degree video of a route in central Zurich, Switzerland

Fig. 1. We created a point cloud model using a photogrammetry structure-from-motion implementation called Colmap, to calculate the visibility parameter (#1).

(fig. 4), that was created for another project (Hijazi et al., 2016). The large sample of possible images was reduced to 12 in order to be able to run a full pairwise comparison i.e. each participant viewed all possible comparisons of every photograph paired against every other photograph. The 12 images are the highest and lowest of each of the 6 parameters listed. The images are ranked according to how relevant they are for the perception of urban density.

Fig. 4. Route of the video in Zürich Wiedikon from which

the photographs were taken.