Junnan Liu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Junnan Liu has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Gaoyuan Wang
Tianjin University
2 shared publications - Chye Kiang Heng
Department of Architecture, College of Design and Engineering, National University of Singapore, Singapore, Singapore
1 shared publication Gaoyuan Wang
1 shared publication- Liuying Wang
School of Architecture, Tianjin University, Tianjin 300072, China
1 shared publication Shurui Yin
1 shared publicationTian Chen
1 shared publication
Latest Publications
- 31 July 2024
- Published by Elsevier in Science of The Total Environment
- Vol. 949, 175155
Spatiotemporal evolution and interaction of water constraints and their socio-ecological drivers in the Taihu Lake Basin
- 31 July 2024
- Published by Elsevier in Science of The Total Environment
- Vol. 949, 175155
Spatiotemporal evolution and interaction of water constraints and their socio-ecological drivers in the Taihu Lake Basin
- Open Access
The Regulating Effect of Urban Large Planar Water Bodies on Residential Heat Islands: A Case Study of Meijiang Lake in Tianjin
Efficiently harnessing the urban cool island effect associated with large urban aquatic bodies holds significant importance in mitigating the urban heat island (UHI) effect and enhancing the quality of residential living. This study focuses on Tianjin’s Meijiang Lake and its surrounding 47 residential areas, combining Landsat 8 remote sensing satellite data with geographic information system (GIS) buffer analyses and multiple linear regression analyses to reveal the summer thermal characteristics of residential waterfront areas with diverse spatial layouts. The results indicate that: (1) Meijiang Lake’s effective cooling radius extends up to 130 m from the water’s edge, achieving a maximum temperature reduction of 14.44%. Beyond 810 m, the cooling effect diminishes significantly. (2) Waterfront distance (WD), building density (BD), building width (L) and normalized difference vegetation index (NDVI) emerge as the primary factors influencing changes in average land surface temperature (ΔLST) in residential areas. The degrees of influence are ordered as follows: BD > WD > NDVI > L. “Dispersed” pattern residential areas exhibit the most favorable thermal environments, which are primarily influenced by WD, while “parallel” pattern residential areas demonstrate the least favorable conditions, primarily due to WD and NDVI. (3) The direct adjacency of residential areas to large-scale aquatic bodies proves to be the most effective approach for temperature reduction, resulting in a 5.03% lower average temperature compared to non-adjacent areas. Consequently, this study derives strategies for improving the thermal environment via the regulation of spatial planning elements in residential areas, including waterfront patterns, vegetation coverage, WD, and BD.
Open AccessThe Regulating Effect of Urban Large Planar Water Bodies on Residential Heat Islands: A Case Study of Meijiang Lake in Tianjin
Efficiently harnessing the urban cool island effect associated with large urban aquatic bodies holds significant importance in mitigating the urban heat island (UHI) effect and enhancing the quality of residential living. This study focuses on Tianjin’s Meijiang Lake and its surrounding 47 residential areas, combining Landsat 8 remote sensing satellite data with geographic information system (GIS) buffer analyses and multiple linear regression analyses to reveal the summer thermal characteristics of residential waterfront areas with diverse spatial layouts. The results indicate that: (1) Meijiang Lake’s effective cooling radius extends up to 130 m from the water’s edge, achieving a maximum temperature reduction of 14.44%. Beyond 810 m, the cooling effect diminishes significantly. (2) Waterfront distance (WD), building density (BD), building width (L) and normalized difference vegetation index (NDVI) emerge as the primary factors influencing changes in average land surface temperature (ΔLST) in residential areas. The degrees of influence are ordered as follows: BD > WD > NDVI > L. “Dispersed” pattern residential areas exhibit the most favorable thermal environments, which are primarily influenced by WD, while “parallel” pattern residential areas demonstrate the least favorable conditions, primarily due to WD and NDVI. (3) The direct adjacency of residential areas to large-scale aquatic bodies proves to be the most effective approach for temperature reduction, resulting in a 5.03% lower average temperature compared to non-adjacent areas. Consequently, this study derives strategies for improving the thermal environment via the regulation of spatial planning elements in residential areas, including waterfront patterns, vegetation coverage, WD, and BD.