The Diversified Impacts of Urban Morphology on Land Surface Temperature among Urban Functional Zones

Gao, Sihang; Zhan, Qiwen; Yang, Chen; Liu, Huimin

doi:10.3390/ijerph17249578

Cited by 37 publications

(15 citation statements)

References 76 publications

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“…At the same time, methods for GIS-based spatial analysis and UHI map generation are being improved [59], as well as the interpolation techniques for cartographic representation [60]. Correlation analysis and regression modeling are commonly used to detect the influence of LULC and urban morphology on the UHI [61,62]. Thanks to advances in geospatial technologies, UHI/SUHI maps based on the LCZ concept have been created for hundreds of cities around the world today.…”

Section: Introductionmentioning

confidence: 99%

An Application of the LCZ Approach in Surface Urban Heat Island Mapping in Sofia, Bulgaria

2021

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This article presents the results of the thermal survey of the capital of Bulgaria (Sofia) carried out in August 2019, with the application of an unmanned aerial system (UAS). The study is based on the concept of local climate zones (LCZs), taking into account the influence of the features of land use/land cover and urban morphology on the urban climate. The basic spatial units used in the study are presented in the form of a regular grid consisting of 3299 cells with sides of 250 ´ 250 m. A total of 13 types of LCZs were identified, of which LCZs 6, 5, 8, 4, D, and A form the largest share. In the thermal imaging of the surface, a stratified sampling scheme was applied, which allowed us to select 74 cells, which are interpreted as representative of all cells belonging to the corresponding LCZ in the urban space. The performed statistical analysis of the thermal data allowed us to identify both the most thermally loaded zones (LCZs 9, 4, and 5) and the cells forming Urban Cool Islands (mainly in LCZs D and C). The average surface temperature in Sofia during the study period (in the time interval between 8:00 PM and 10:00 PM) was estimated at 20.9 °C, and between the different zones it varied in the range 17.2–25.1 °C. The highest maximum values of LST (27.9–30.6 °C) were registered in LCZ 4 and LCZ 5. The relation between the spatial structure of the urban thermal patterns and urban surface characteristics was also analyzed. Regression analysis confirmed the hypothesis that as the proportion of green areas increases, surface temperatures decrease, and, vice versa, as the proportion of built-up and impermeable areas increases, surface temperatures increase. A heat load map (via applying a z-transformation to standardize the temperature values), a map of the average surface temperature, and a map of the average intensity of the heat island on the surface were generated in the GIS environment. The results of the study adequately reflect the complex spatial model of the studied phenomenon, which gives grounds to conclude that the research approach used is applicable to similar studies in other cities.

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Section: Introductionmentioning

confidence: 99%

An Application of the LCZ Approach in Surface Urban Heat Island Mapping in Sofia, Bulgaria

2021

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“…Industrial heat emission is one of the main heat sources in Wuhan ( Huang & Wang, 2019 ). When operating normally, these secondary industry and heat emissions would increase the LST in industrial area ( Huang & Wang, 2019 ; Gao et al., 2020 ). While, the COVID-19 pandemic decreased the industrial activities, resulting in reduction of energy consumption, as well as industrial heat emissions and lower LST in industrial areas.…”

Section: Methodsmentioning

confidence: 99%

“…By referring to previous studies ( Sailor, 2011 ; Liao et al., 2017 ; Hu et al., 2020 ; Sun et al., 2018 ; He et al., 2021 ), we introduced and proposed four assumptions of the relationship between industrial production and LST in industrial areas: (1) industrial production is positively correlated with energy consumption; ( Tang et al., 2018 ) (2) energy consumption is closely correlated with heat emissions; ( Sun et al., 2018 ; He et al., 2020 ) (3) close correlation exists between industrial heat and secondary GDP; Sun et al., 2018 ; He et al., 2020 ) (4) the industrial heat emissions is also positively correlated with the LST in industrial areas ( Huang & Wang, 2019 ; Gao et al., 2020 ). Based on these assumptions, we can employ the LST to represent industrial activities, and further detail the spatiotemporal changes of LST to explore the COVID-19 impacts on industrial production in Wuhan.…”

Section: Methodsmentioning

confidence: 99%

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Spatiotemporal patterns of the COVID-19 control measures impact on industrial production in Wuhan using time-series earth observation data

Yinqing

Zhang

et al. 2021

Sustainable Cities and Society

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Understanding the spatiotemporal patterns of the COVID-19 impact on industrial production could improve the estimation of the economic loss and sustainable work resumption policies in cities. In this study, assuming and checking a correlation between the land surface temperature (LST) and industrial production, we applied the BFAST algorithm and linear regression models on multi-temporal MODIS data to derive monthly time-series deviation of LST with a spatial resolution of 1 × 1 km, to quantificationally explore the fine-scale spatiotemporal patterns of the COVID-19 control measures impact on industrial production, within Wuhan city. The results demonstrate that (1) the trend of time-series LST could partly reflect the impact of the COVID-19 pandemic on industrial production, and the year-around industrial production was less than expectations, with a fall of 14.30%; (2) the most serious COVID-19 impact on industrial production appeared in Mar. and Apr., then, after the lifting of lockdown, some regions (approximate 4.90%) firstly returned to expected levels in Jun, and almost all regions (98.49%) have completed the resumption of work and production before Nov.; (3) the southwest and south-central had more serious impact of the COVID-19 pandemic, approximate twice as much as that in the north and suburban, in Wuhan. The results and findings elaborated the spatiotemporal distribution and their changes during 2020 within Wuhan, which could provide a beneficial support for assessment of the COVID-19 pandemic and implementation of resumption plans for sustainable development.

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“…The urban built intensity indexes are selected as factors of the urban heat island [ 15 ]. The significant impact of urban morphology on land surface temperature was observed in different types of urban functional zones.…”

Section: Introductionmentioning

confidence: 99%

The Ventilation Efficiency of Urban Built Intensity and Ventilation Path Identification: A Case Study of Wuhan

Yin

Zhan

Tayyab

et al. 2021

IJERPH

Self Cite

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Urban ventilation is being hampered by rough surfaces in dense urban areas, and the microclimate and air quality of the urban built environment are not ideal. Identifying urban ventilation paths is helpful to save energy, reduce emissions, and improve the urban ecological environment. Wuhan is the capital city of Hubei, and it has a high urban built intensity and hot summers. Taking Wuhan city, with a size of 35 km ×50 km, as an example, the built environment was divided into grids of 100 m × 100 m and included the building density, floor area ratio, and average building height. The ventilation mechanism of the urban built intensity index has previously been explained. The decrease in building density is not the sole factor causing an increase in wind speed; the enclosure and width of the ventilation path and the height of the front building are also influential. Twelve urban built units were selected for CFD numerical simulation. The ventilation efficiency of each grid was evaluated by calculating the wind speed ratio, maximum wind speed, average wind speed, and area ratio of strong wind. The relationship between the urban built intensity index and ventilation efficiency index was established using the factor analysis method and the Pearson correlation coefficient; building density and average building height are the most critical indexes of ventilation potential. In addition, the layout of the building also has an important impact on ventilation. A suitable built environment is that in which the building density is less than 30%, the average building height is greater than 15 m, and the floor area ratio is greater than 1.5. The urban built intensity map was weighted to identify urban ventilation paths. The paper provides a quantitative reference for scientific planning and design of the urban spatial form to improve ventilation.

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The Diversified Impacts of Urban Morphology on Land Surface Temperature among Urban Functional Zones

Cited by 37 publications

References 76 publications

An Application of the LCZ Approach in Surface Urban Heat Island Mapping in Sofia, Bulgaria

An Application of the LCZ Approach in Surface Urban Heat Island Mapping in Sofia, Bulgaria

Spatiotemporal patterns of the COVID-19 control measures impact on industrial production in Wuhan using time-series earth observation data

The Ventilation Efficiency of Urban Built Intensity and Ventilation Path Identification: A Case Study of Wuhan

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