Outdoor Perception Research Articles

Using Google Street View photographs to assess long-term outdoor thermal perception and thermal comfort in the urban environment during heatwaves

The outdoor thermal comfort of urban residents is negatively affected by heatwaves that are becoming more frequent and severe with the ongoing climate crisis. As such, the assessment of outdoor perception and comfort during heatwaves has become an important ingredient of successful urban adaptation strategies. However, systematic assessment of long-term thermal perception across a large number of places and large populations of people is difficult. In this study, we consider an approach to the assessment of long-term thermal perception that combines features of currently used approaches (i.e., use of rating scales of thermal perception, use of surveys, and the use of photographs representing places) and we provide some preliminary validation of this approach. Specifically, across three studies conducted in two Czech cities, we show that long-term thermal perceptions for a large sample of 1,856 urban places can be elicited in a large sample of city residents (total N = 1,812) using rating scales in off-site surveys complemented with visual representations of the target locations. In Studies 1 and 2, we partially validate this approach by showing that such long-term thermal perceptions can be traced back to average surface temperature, sky-view factor, and the presence of blue and green infrastructure, all factors that the literature relates to thermal perception. Moreover, we show evidence that observers can reliably glean these properties from the visual representation of places. In Study 3, we provide additional evidence of the predictive validity of such long-term thermal perceptions by showing that they predict place-related activities (waiting and walking) and the place preference of other people more than one year later. Thus, this approach to the measurement of long-term thermal perception related to heatwaves can be a useful addition to currently used approaches.

Automatic extraction of urban outdoor perception from geolocated free texts

The automatic extraction of urban perception shared by people on location-based social networks (LBSNs) is an important multidisciplinary research goal. One of the reasons is it facilitates the understanding of the intrinsic characteristics of urban areas in a scalable way, helping to leverage new services. However, content shared on LBSNs is diverse, encompassing several topics, such as politics, sports, culture, religion, and urban perceptions, making the task of content extraction regarding a particular topic very challenging. Considering free-text messages shared on LBSNs, we propose an automatic and generic approach to extract people’s perceptions. For that, our approach explores opinions that are spatiotemporal and semantically similar. We exemplify our approach in the context of urban outdoor areas in Chicago, New York City and London. Studying those areas, we found evidence that LBSN data bring valuable information about urban regions. To analyze and validate our outcomes, we conducted a temporal analysis to measure the results’ robustness over time. We show that our approach can be helpful to better understand urban areas considering different perspectives. We also conducted a comparative analysis based on a public dataset, which contains volunteers’ perceptions regarding urban areas expressed in a controlled experiment. We observe that both results yield a very similar level of agreement.

Assessing the effect of weather on human outdoor perception using Twitter

Human comfort in outdoor spaces (HCOS) is linked to people's psychological responses to environmental variables. Previous studies have established comfort ranges for these variables through interviews and questionnaires, reaching only limited populations. However, larger amounts of data would not only generate more robust results in local studies, but it would also allow for the possibility of creating an approach that could be applied to a wider range of weather conditions and different climates. Therefore, this study describes a new methodology to assess people's perception of weather based on human responses to weather conditions extracted from tweets, with the purpose of establishing comfort ranges for environmental variables. Tweets containing weather-associated keywords were collected, stored, and then linked to real-time meteorological data acquired nearby the locations in which the tweets were posted. Afterwards, people's perception of weather was extracted from the tweets using a classifier trained specifically on weather data that identified irrelevant, neutral, positive, and negative tweets. The obtained tweets and their related atmospheric data were analyzed to establish comfort ranges. The tweets' responses to effective temperature were very similar to those obtained in previous studies, although the peak of comfort is shifted towards the cold stress. Similarly, the tweets' responses to the thermohygrometric index were alike to previous results, but the peak of comfort is shifted towards the heat stress. Regarding the single weather variables under study, the obtained comfort ranges are similar to the ones found in previous research; in particular, the temperature comfort range matches perfectly at 20-22°C. Therefore, it was concluded that tweets can be used to assess HCOS; not only are the results of this methodology comparable to results obtained in previous studies, but the procedure itself also shows new features and unexpected future applications.

The outdoor perception of distance ratios

The outdoor perception of distance ratios

Computational Design and Parametric Optimization Approach with Genetic Algorithms of an Innovative Concrete Shading Device System

Office buildings in contemporary architecture usually have a high value of window to wall ratio (WWR) determining transparent façade as the most important part of the building façade to control solar gains, thermal losses and visual comfort. Therefore, in order to fulfill strict National energy regulations and LEED requirements, façades require a proper balance between transparent and opaque or shaded surfaces to avoid overheating, optimizing daylighting aspects and outdoor perception. Concrete is usually used in building sector for primary structure or secondary structure of cladding solutions. With new concrete materials and innovative digital fabrication process is possible to rediscover concrete for high performance façade/shading solutions. The aim of this paper is the development of high performance concrete static shading system using computational design approach and its optimization, by genetic algorithms, based on several parameters such as radiation control, outdoor view and daylight indexes and energy performance.After the development of a geometry definition managed with a parametric modelling approach (Rhinoceros and Grasshopper), genetic algorithm optimization were used in order to define the openness's sizes and their cutting angle to minimize solar radiation entrance during year, maintaining outdoor view. The possible geometric alternatives were part of a sensitivity analysis with Radiance and Energy-plus engine to assess the shading system performance in terms of daylighting and energy use. In order to evaluate their performances a study case, a single office unit placed in Milan (Italy) was defined, considered with wall facing outdoors, having a WWR of 86%, and five surfaces adiabatic. The results shows that using this approach is possible to develop an effectiveness shading solution able to control radiation over the year and likewise guarantee a high performance regarding the outdoor perception and visual comfort.

Predicting transmission of shaped sonic booms into a residential house structure

Human perception of sonic booms is a major impediment to commercial supersonic flight. Shaping, which reduces the audible shock waves of a boom, can make outdoor perception of booms acceptable. Perception of sonic booms experienced indoors is of concern, and it is not yet established whether shaped booms offer benefit to indoor listeners. A better understanding of the transmission of shaped booms into building structures is needed. In the authors' earlier work the vibration response of house elements subjected to different sonic boom wave shapes was evaluated using a single degree of freedom model. This paper expands that approach with a modal analysis model. The acceleration of building elements and the resulting sound pressure inside a room are computed in the time and frequency domains. Analytical results are compared with experimental data measured by NASA during sonic boom tests conducted at Edwards Air Force Base in 2007. The effects of wave signature parameters on transmission are studied to evaluate the advantages of various kinds of minimized boom shapes.