1
|
Zhou Y, Zhao H, Mao S, Zhang G, Jin Y, Luo Y, Huo W, Pan Z, An P, Lun F. Exploring surface urban heat island (SUHI) intensity and its implications based on urban 3D neighborhood metrics: An investigation of 57 Chinese cities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 847:157662. [PMID: 35907552 DOI: 10.1016/j.scitotenv.2022.157662] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 07/19/2022] [Accepted: 07/23/2022] [Indexed: 06/15/2023]
Abstract
Excessive urban temperature exerts a substantially negative impact on urban sustainability. Three-dimensional (3D) landscapes have a great impact on urban thermal environments, while their heat conditions and driving factors still remain unclear. This study mapped urban 3D neighborhoods and their associated SUHI (surface urban heat island) intensities in summer daytime across 57 Chinese cities, and then explored their relationships, driving factors as well as implications. Nine categories of urban 3D neighborhoods existed in Chinese cities and the 3D neighborhood of High Density & Medium Rise (HDMR) contributed the largest share of urban areas. The distribution of 3D neighborhoods varied among cities due to their distinct natural and economic traits. The average SUHI intensity can amount to 4.27 °C across all Chinese 3D neighborhoods. High Density & Low Rise (HDLR) and HDMR presented higher SUHI intensities than other 3D neighborhoods in China. Urban green space (UGI) and building height (BH) had great influences on SUHI intensities. The relative contribution of UGI decreased with the increase of building density and building height, but BH presented the opposite trend. The interaction of urban 3D landscapes and function zones led to highly complicated urban thermal environments, with higher SUHI intensities in industrial zones. Besides, the SUHI intensities of 3D neighborhoods presented great diurnal and seasonal variations, with higher SUHI intensities in HDHR and HDMR at nighttime in winter and summer. What's more, urban residents may suffer unequal heat risk inside cities due to the deviations of SUHI intensities among different 3D neighborhoods. It could be a highly effective way to mitigate SUHI effects in cities by increasing urban greening and improving urban ventilation.
Collapse
Affiliation(s)
- Yi Zhou
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Land Quality, Ministry of Land and Resources, Beijing 100193, China.
| | - Haile Zhao
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Land Quality, Ministry of Land and Resources, Beijing 100193, China
| | - Sicheng Mao
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Land Quality, Ministry of Land and Resources, Beijing 100193, China.
| | - Guoliang Zhang
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Land Quality, Ministry of Land and Resources, Beijing 100193, China.
| | - Yulin Jin
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Land Quality, Ministry of Land and Resources, Beijing 100193, China
| | - Yuchao Luo
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Land Quality, Ministry of Land and Resources, Beijing 100193, China.
| | - Wei Huo
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Land Quality, Ministry of Land and Resources, Beijing 100193, China
| | - Zhihua Pan
- College of Resources and Environmental Science, China Agricultural University, Beijing 100193, China.
| | - Pingli An
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Land Quality, Ministry of Land and Resources, Beijing 100193, China.
| | - Fei Lun
- College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Land Quality, Ministry of Land and Resources, Beijing 100193, China.
| |
Collapse
|
2
|
Dominant Factors in the Temporal and Spatial Distribution of Precipitation Change in the Beijing–Tianjin–Hebei Urban Agglomeration. REMOTE SENSING 2022. [DOI: 10.3390/rs14122880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Urbanization has a significant influence on precipitation, but existing studies lack the spatial and temporal heterogeneity analysis of its impact on precipitation in urban areas at different levels. This study investigates the spatial heterogeneity of precipitation and the influencing factors on six dimensions in 156 urban areas in the Beijing–Tianjin–Hebei urban agglomeration from 2000 to 2018, utilizing a mixed-methods analytical approach. The results show that the change in the natural factor layer caused by urbanization was the most important factor, affecting urban precipitation variation in summer and over the whole year, accounting for 34.5% and 10.7%, respectively. However, the contribution of the urban thermal environment in summer cannot be ignored, and the change in the urban thermal environment caused by human activities in winter is an important influencing factor. When considering the optimal combination of factors, relative humidity was shown to be significant in the spatial variations in precipitation during summer, which contributed 26.2%, followed by human activity as indicated by night-time light intensity. Over the whole year, aerosol optical depth makes the substantial contribution of 21.8% to urban precipitation change. These results provide benchmarks for improving the adaptability of urban-environment change and urban planning in the context of urbanization.
Collapse
|
3
|
Urban Heat Island Effects on Megacities in Desert Environments Using Spatial Network Analysis and Remote Sensing Data: A Case Study from Western Saudi Arabia. REMOTE SENSING 2021. [DOI: 10.3390/rs13101941] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Contemporary cities continue to face significant geoenvironmental challenges due to constant rapid urbanization. Furthermore, the governments of cities worldwide are considering the green cities approach to convert their cities’ weaknesses into opportunities. The 2030 Saudi vision supports smart growth concepts, with a vision of speeding up economic growth while ensuring that natural assets strengthen the country’s foundations. The urban heat island (UHI) effect is a threatening phenomenon that increases the required cooling loads and negatively affects urban communities and the quality of life, especially in arid environments. This study integrates remote sensing and spatial network analysis to investigate the UHI using the distribution of land surface temperatures (LST) extracted from satellite data during both winter and summer seasons in Makkah city. We investigated and compared the UHIs in two districts, Al-Sharashef and AlEskan, representing the organic and deformed iron-grid with fragmented paralleled street networks, respectively. The spatial analysis of different LST maps, which were derived from Landsat-8 images revealed significant differences between the two case studies. The mean temperature for the AlEskan district was 1–1.5 °C higher than that of the Al-Sharshaf district. This difference can be attributed to the different urban fabrics between the two districts. Moreover, the zones that are currently under construction show relatively higher LST compared to residential zones. The research revealed that the organic/compact urban fabric is better than the deformed iron-grid urban fabric in mitigating the UHI. However, these results are specific to the test site; however, they emphasize the role of integration of remote sensing and spatial network analysis in urban planning. In light of these findings, we recommend integrating remote sensing-based LST analysis with spatial analysis of urban fabrics to better understand the causal effects of UHI, especially in cities located in desert environments. This can help mitigate the impact of projected global warming and contribute to improving the quality of urban life.
Collapse
|