Seemo: A new tool for early design window view satisfaction evaluation in residential buildings

Kim, Jaeha; Kent, Michael; Kral, Katharina; Dogan, Timur

doi:10.1016/j.buildenv.2022.108909

Cited by 28 publications

(12 citation statements)

References 42 publications

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“…This included three layers, namely: sky, landscape, and ground; and a distant building and relatively near nature (e.g., lawn and trees). Previous studies [53,54] had observed an interaction between content and access (e.g., window size) but there is no quantified information on how they interact. Therefore, isolating the effect of the window view access by controlling the view content should be a salient feature to the experimental design.…”

Section: Window Viewmentioning

confidence: 99%

“…The participants verbally answered questions about their satisfaction using a 7-point Likert scale, ranging from: "Very dissatisfied" (-3) to "Very satisfied" (+3), and were balanced across an indifference (0) point (Figure 5). This satisfaction scale is commonly used in IEQ research [67,68] and window view research [54,69], where occupants rated their satisfaction levels to the conditions.…”

Section: Satisfaction With the Amount Of The Window Viewmentioning

confidence: 99%

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View access index: The effects of geometric variables of window views on occupants’ satisfaction

Schiavon

Santos

et al. 2023

Building and Environment

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Section: Window Viewmentioning

confidence: 99%

Section: Satisfaction With the Amount Of The Window Viewmentioning

confidence: 99%

View access index: The effects of geometric variables of window views on occupants’ satisfaction

Schiavon

Santos

et al. 2023

Building and Environment

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“…regression) models (Bzdok et al 2018). Studies for indoor environmental quality (Graham et al 2021;Kent et al 2021), thermal comfort (Kim et al 2018;Cheung et al 2019), and window view design (Kim et al 2022) are among those which have applied machine-learning algorithms, testing the predictive limits from data that sought to understand occupant satisfaction. To determine the predictive capacity of the environmental information criteria, machine learning algorithms were used to verify their ability to predict window view preferences in our current study.…”

Section: Excellentmentioning

confidence: 99%

Predicting Window View Preferences Using the Environmental Information Criteria

Kent

Schiavon

2022

LEUKOS

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Daylighting standards provide an assessment method that can be used to evaluate the quality of window views. As part of this evaluation process, designers must achieve five environmental information criteria (location, time, weather, nature, and people) to obtain an excellent view. To the best of our knowledge, these criteria have not yet been verified and their scientific validity remains conjectural. In a two-stage experiment, a total of 451 persons evaluated six window view images. Using machine learning models, we found that the five criteria could provide accurate predictions for window view preferences. When one view was largely preferred over the other, the accuracy of decision tree models ranged from 83% to 90%. For smaller differences in preference, the accuracy was 67%. As ratings given to the five criteria increased, so did evaluations for psychological restoration and positive affect. Although causation was not established, the role of most environmental information criteria was important for predicting window view preferences, with nature generally outweighed the others. We recommend the use of the environmental information criteria in practice, but suggest some alterations to these standards to emphasize the importance of nature within window view design. Instead of only supporting high-quality views, nature should be promoted across all thresholds dictating view quality.

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“…In contrast to the visibility assessment from possible viewpoints on the ground, we argued that the cityscape changes caused by the deployment of solar applications could also have visual impacts on the occupants through windows. As a crucial element connecting the inner self to outside world, the window view has been playing a great role in urban life, including residential satisfaction (Kim et al, 2022), thermal comfort (Ko et al, 2020), work performance (Lottrup et al, 2015), occupant well-being (Elsadek et al, 2020), visual privacy (Zheng et al, 2021(Zheng et al, , 2022, and even financial values (Turan et al, 2021). Predictably, with a large number of PV modules widely spread over the rooftops and even building facades, the original fabric of the building envelope will be changed, potentially resulting in a negative impact on the window view quality of neighboring occupants.…”

Section: Introductionmentioning

confidence: 99%

Feasibility assessment of solar photovoltaic deployments on building surfaces with the constraint of visual impacts

Lin

et al. 2022

Environment and Planning B: Urban Analytics and City Science

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As a major component of social acceptance, visual impact is often considered a significant constraint in solar applications. Visual impact assessment of solar applications, however, has been limited to pedestrians in previous studies. The extent to which PV systems can have visual impacts on occupants and whether it is necessary to include occupants in the measurement of visual impact remains uncertain. To fill this gap, we extended it from pedestrians to occupants and proposed a quantitative method to integrate pedestrians and occupants into a framework, combining the estimation of solar potential for the feasibility assessment of PV applications in a built environment. The concept is tested with a real case, located in Qingdao city, China, to present the technical flowchart for the feasibility assessment of solar PV deployments with the visual constraint. Building surfaces with qualified solar irradiation and low visibility were identified and compared in two cases, that is, with and without the inclusion of occupants as the visual constraint. The comparison results show that the change of suitable building surfaces for solar applications is 172,306 m2 (21% of suitable area) and 126 GWh (19% of yield energy) across the study area, indicating the significance of including occupants in the visibility assessment for the deployment of solar applications. The proposed method considers the visual constraint for the feasibility assessment of solar applications from the perspective of pedestrians and occupants, and it is helpful to identify the suitable surfaces for the large-scale deployment of solar applications at an early planning stage of solar city.

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Seemo: A new tool for early design window view satisfaction evaluation in residential buildings

Cited by 28 publications

References 42 publications

View access index: The effects of geometric variables of window views on occupants’ satisfaction

View access index: The effects of geometric variables of window views on occupants’ satisfaction

Predicting Window View Preferences Using the Environmental Information Criteria

Feasibility assessment of solar photovoltaic deployments on building surfaces with the constraint of visual impacts

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