Lijun Wang

Prof. Lijun Wang

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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SLShan LU
Shan LU
WOWonseok Oh
Wonseok Oh
Ryozo OokaRyozo Ooka
Ryozo Ooka
LWLijun Wang
Lijun Wang
Exposure to small public urban green spaces (SPUGS) has been demonstrated to have mental benefits for older adults. However, studies on identifying the objective environmental features of SPUGS and their effects on mental restoration for older adults remain limited. This study employed a multilevel regression model to investigate the restorative and vitalizing effects of the environmental features of 11 SPUGS in Tokyo. Onsite measurements were conducted in Kita-Ku, and 202 older adults were surveyed. The results showed that: (1) The fitting curve of the green view index and Restoration Outcome Scale (ROS) score showed an inverted U shape—both green view index and boundary enclosure had a strong impact on the mental restoration of older adults; (2) The colorfulness index showed the strongest relationship with the vitalizing effect. (3) The sky view factor and number of seats only influenced the ROS score, while the results of revitalization suggest that large areas of water should be avoided. (4) Physiological Equivalent Temperature (PET) was also confirmed to have negative effects on the mental restoration of older adults in autumn. These empirical findings can be used as a resource to promote the mental health of older adults in the design of SPUGS in high-density Asian countries.

13 March 2025 in Buildings
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Journal Article
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BYBiao Yin
Biao Yin
LWLijun Wang
Lijun Wang
YXYuan Xu
Yuan Xu
KHKiang Chye Heng
Kiang Chye Heng
With the transformation of urban development patterns and profound changes in population structure in China, outdoor activity spaces in residential areas are facing common issues such as obsolete infrastructure, insufficient barrier-free facilities, and intergenerational conflicts, which severely impact residents’ quality of life and hinder high-quality urban development. Guided by the principles of all-age friendly and inclusive design, this study innovatively integrates eye-tracking and multi-modal physiological monitoring technologies to collect both subjective and objective perception data of different age groups regarding outdoor activity spaces in residential areas through human factor experiments and empirical interviews. Machine learning methods are utilized to analyze the data, uncovering the differentiated response mechanisms among diverse groups and clarifying the inclusive characteristics of these spaces. The findings reveal that: (1) Common Demands: All groups prioritize spatial features such as unobstructed views, adequate space, diverse landscapes, proximity accessibility, and smooth pavement surfaces, with similar levels of concern. (2) Differentiated Characteristics: Children place greater emphasis on environmental familiarity and children’s play facilities, while middle-aged and elderly groups show heightened concern for adequate space, efficient parking management, and barrier-free facilities. (3) Technical Validation: Heart Rate Variability (HRV) was identified as the core perception indicator for spatial inclusivity through dimensionality reduction using Self-Organizing Maps (SOM), and the Extra Trees model demonstrated superior performance in spatial inclusivity prediction. By integrating multi-group perception data, standardizing experimental environments, and applying intelligent data mining, this study achieves multi-modal data fusion and in-depth analysis, providing theoretical and methodological support for precisely optimizing outdoor activity spaces in residential areas and advancing the development of all-age friendly communities.

1 December 2024 in Frontiers of Architectural Research
Verified
Journal Article
Open access
WJWei Jia
Wei Jia
LWLijun Wang
Lijun Wang

29 December 2023 in Buildings
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WHWeihao Hao
Weihao Hao
Abel TabladaAbel Tablada
Abel Tablada
XSxuepeng SHI
xuepeng SHI
LWLijun Wang
Lijun Wang
XMXi Meng
Xi Meng
Productive facades, consisting of photovoltaic shading and vertical farming systems, have been proposed as a means to improve the thermal and visual status of residential buildings while also maintaining energy performance and providing vegetables. However, how to quickly and accurately predict electricity and vegetable output during the numerous influencing architectural and environmental factors is one of the key issues in the early stages of design, and few studies have investigated the impact of such structures on both indoor environmental qualities and production performance. In this paper, we present a novel prediction method that uses experimental data to train and test an artificial neural network (ANN). The results indicated that using the Bipolar Sigmoid activation function to process the experimental data input to the artificial neuron network gives more accurate predicted results both in the yield of photovoltaic shading and vertical farming systems. In addition, this prediction method was applied to a typical high-rise residential building in Singapore to assess the self-sufficiency potential of high-rise residential buildings integrated with productive facades. The results indicated that the upper part of the building can meet 20.0–23.1% of the annual household electricity demand of a family of four in a four-room residential unit in Singapore and almost the entire year’s vegetable demand, while the middle part can meet 18.4–21.2% and 89.1%, respectively. The results demonstrated the importance of a productive facade in reducing energy demand, enhancing food security, and improving indoor visual and thermal comfort.

1 August 2023 in Frontiers of Architectural Research
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Journal Article
Open access
WJWei Jia
Wei Jia
LWLijun Wang
Lijun Wang
HCHong Heng Chong
Hong Heng Chong

28 March 2025 in Land
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Haneen AhmadHaneen Ahmad
Haneen Ahmad
YCYuxin Cao
Yuxin Cao
AAAyat Almomani
Ayat Almomani
Lama AkmeelLama Akmeel
Lama Akmeel
LWLijun Wang
Lijun Wang
Most of the time, urban planning tends to exclude the specific needs and perceptions of women, resulting in spaces that fail to meet their safety needs. This study explores the impact of physical environment factors on women’s safety perceptions in neighborhood parks in Jordan. While a few studies on this topic have been conducted in Jordan, this research makes a unique contribution by focusing on the interaction between physical design factors and demographic characteristics, examining how these factors influence women’s safety perceptions. Focusing on women’s safety in neighborhood parks, a survey was conducted and involved a sample of 380 women, using a random sampling method. confirmatory factor analysis (CFA) was employed to identify underlying relationships between safety-related factors, while cluster analysis was used to group women based on their shared safety perceptions. The results revealed statistically significant differences and identified five distinct clusters, demonstrating varied perceptions of safety among women. This study emphasizes the importance of tailoring park designs to meet women’s specific safety needs, recognizing the diversity of priorities across demographic groups. The findings offer actionable insights for urban planners and policymakers, guiding the development of safer public spaces that respond to the varied needs of women.