Direct and indirect effects of multisensory modalities on visitor’ s thermal comfort in an urban park in a humid-hot climate

Liu, Chang; Tang, Lina; Yan, Jinshan; Ouyang, Jingyi

doi:10.1080/13504509.2022.2142692

Cited by 9 publications

(5 citation statements)

References 27 publications

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“…Besides meteorological factors, some studies tested and confirmed the hypothesis that building orientation and street layout are prominent factors affecting outdoor thermal comfort [58,63]. Only one study directly evaluated the effect of direct psychological cognition (multi-sensory modalities) on thermal comfort using the structural equation method (SEM) [19]. Using regression techniques, Kruger and Drach (2017) assessed multiple factors like ethnicity, skin color, body mass index (BMI), and age for estimating the thermal neutral range [68].…”

Section: Significant Predictor Variablesmentioning

confidence: 99%

“…Contrary to this traditional method of assessment, Cheung and Jim (2019) pointed out that the duration that a person spends outdoors determines comfortability by calculating the 1-h duration acceptable range, and prediction results of PET and UTCI based on their hypothesis showed very high accuracy [84]. Overall, all studies that tested the hypothesis of whether demographic and personal factors were prominent confirmed that they are significant along with meteorological factors [9,19,45,48,53,61,68,74,77,82].…”

Section: Significant Predictor Variablesmentioning

confidence: 99%

“…As an alternative to the traditional approach of estimating OTCI, a few researchers have recently used machine learning models such as ANNs and random forest to improve the predictive accuracy of the thermal comfort index [17,18]. Other studies employing non-traditional approaches include multi-sensory design with walkability and outdoor thermal comfort [19], estimating real-time OTCI and Physiological Equivalent Temperature (PET) using IoT devices, and applying digital twins and Geographic Information Systems (GIS) to predict OTCI [12]. Overall, the studies that use an OTCI still need to be more accurate, while most studies that use Machine learning (ML) or Internet of Things (IoT) mostly try only to improve the existing OTCI [20,21] thereby making the two approaches fragmented.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Review on Gaps and Challenges in Prediction Outdoor Thermal Comfort Indices: Leveraging Industry 4.0 and ‘Knowledge Translation’

Elnabawi,

Hamza

2024

Buildings

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The current outdoor thermal comfort index assessment is either based on thermal sensation votes collected through field surveys/questionnaires or using equations fundamentally backed by thermodynamics, such as the widely used UTCI and PET indices. The predictive ability of all methods suffers from discrepancies as multi-sensory attributes, cultural, emotional, and psychological cognition factors are ignored. These factors are proven to influence the thermal sensation and duration people spend outdoors, and are equally prominent factors as air temperature, solar radiation, and relative humidity. The studies that adopted machine learning models, such as Artificial Neural Networks (ANNs), concentrated on improving the predictive capability of PET, thereby making the field of Artificial Intelligence (AI) domain underexplored. Furthermore, universally adopted outdoor thermal comfort indices under-predict a neutral thermal range, for a reason that is linked to the fact that all indices were validated on European/American subjects living in temperate, cold regions. The review highlighted gaps and challenges in outdoor thermal comfort prediction accuracy by comparing traditional methods and Industry 4.0. Additionally, a further recommendation to improve prediction accuracy by exploiting Industry 4.0 (machine learning, artificial reality, brain–computer interface, geo-spatial digital twin) is examined through Knowledge Translation.

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Section: Significant Predictor Variablesmentioning

confidence: 99%

Section: Significant Predictor Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Review on Gaps and Challenges in Prediction Outdoor Thermal Comfort Indices: Leveraging Industry 4.0 and ‘Knowledge Translation’

Elnabawi,

Hamza

2024

Buildings

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“…Specifically, a 1-unit increase in physical senses produces an increase of 0.518 units in thermal sensation, and an increase of 0.428 units in psychological perceptions. Their findings provide a reference for the ecological restoration of urban park green spaces in the context of global warming [ 34 ].…”

Section: Landsenses Ecology and Watershed Ecology Restorationmentioning

confidence: 99%

Landsenses Ecology: A New Idea for Watershed Ecology Restoration

Liu

Ouyang

Yan

et al. 2023

IJERPH

Self Cite

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Watershed ecology restoration is the key to solving the ecological and environmental problems of watersheds and achieving sustainable development. As one direction of the frontiers of ecology, landsenses ecology is supported by science and technology and cares for humans. It has a great significance for enhancing the human habitat and achieving sustainable development. Combining landsenses ecology and the technical process of watershed ecology restoration allows the integration of people’s visions into the system of strategies and applied technologies for watershed ecology restoration while ensuring the restoration of the ecological functions of watersheds. It is a complement to the traditional ecosystem restoration model. This study establishes the connection between landsenses ecology and watershed ecology restoration in terms of goals, models and focus of attention. It aims to construct an indicator system of restoration with the application of landsenses ecology, form a complete process of ecological restoration with the integration of landsenses ecology and apply it to the ecological restoration of watershed elements with relatively intensive human activity such as urban green areas, buildings and wetlands (rivers and lakes). Rather than just always emphasizing natural ecology, landsenses ecology treats human beings as part of nature. It tries to establish a more comprehensive, humanized ideal restoration model by taking “human perceptions” into consideration. Through a restoration process based on long-term and continuous coordination, feedback and improvement, it can improve the ecological benefits of the watershed and improve residents’ well-being, so as to ultimately realize the establishment of a “community of life between man and nature”.

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“…Thermal comfort refers to subjective perceptions of the external environment [30]. The physiologically equivalent Ta is more universal and mature than the outdoor space thermal comfort evaluation index and is suitable for mesoscale spatial simulations.…”

Section: Outdoor Thermal Comfort Calculationmentioning

confidence: 99%

Thermal Comfort Improvement Strategies for Outdoor Spaces in Traditional Villages Based on ENVI-Met: Shimengao Village in Chizhou City

Xiao,

Sheng,

Zhang

et al. 2023

Sustainability

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The thermal comfort of outdoor spaces in traditional villages must be improved because high building density combined with complex and narrow spaces leads to a poor thermal environment. In traditional villages, outdoor spaces are the most frequently used places by local residents and tourists. In this study, the Shimengao Village in Tangxi Town, Chizhou City, a typical mountainous area in the southern Anhui Province, was selected as the research object, and Depthmap software was used to identify the most frequently used outdoor spaces. The spatial layout and three different outdoor spaces of the traditional village were measured and validated using ENVI-met software. In addition, the distribution of thermal comfort in the core area of the village and influencing factors were analyzed. Our results demonstrated that during summer, PET reached its highest value at 15:00, exhibiting a poor thermal environment in the core area of traditional village integration. From 15:00 to 21:00, PET values declined, resulting in improved thermal comfort levels. Open spaces had better thermal comfort ratings throughout the day. The thermal comfort distribution of three different types of outdoor space in traditional villages was also analyzed. The courtyard space had the worst thermal comfort, followed by the street space, whereas the square space had the best thermal comfort environment. This was correlated with the spatial layout of traditional villages, external facilities of buildings, microlandscapes (plants, water availability, etc.), and outdoor ground materials. Hence, we propose that optimizing the overall spatial layout of a traditional village, increasing the external facilities of buildings, creating “micro landscapes,” and optimizing the materials of outdoor spaces are important for improving the thermal comfort of the outdoor spaces of traditional villages.

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Direct and indirect effects of multisensory modalities on visitor’ s thermal comfort in an urban park in a humid-hot climate

Cited by 9 publications

References 27 publications

Review on Gaps and Challenges in Prediction Outdoor Thermal Comfort Indices: Leveraging Industry 4.0 and ‘Knowledge Translation’

Review on Gaps and Challenges in Prediction Outdoor Thermal Comfort Indices: Leveraging Industry 4.0 and ‘Knowledge Translation’

Landsenses Ecology: A New Idea for Watershed Ecology Restoration

Thermal Comfort Improvement Strategies for Outdoor Spaces in Traditional Villages Based on ENVI-Met: Shimengao Village in Chizhou City

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