Simulation of future land surface temperature distribution and evaluating surface urban heat island based on impervious surface area

Şekertekin, Aliihsan; Zadbagher, Elaheh

doi:10.1016/j.ecolind.2020.107230

Cited by 78 publications

(32 citation statements)

References 73 publications

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“…The area of tree-based green space within approximately 0.32 ha can effectively enhance their cooling intensity [30]. A high coverage ratio of green space corresponds to a lower surface temperature [31,32]. Belt-shaped green areas parallel to the wind direction appear to have a higher cooling effect than those vertical to the wind direction and the difference of the cooling effect reached 6.3 K between the two orientation scenarios with big canopy trees [33].…”

Section: Introductionmentioning

confidence: 99%

Cooling Island Effect of Blue-Green Corridors: Quantitative Comparison of Morphological Impacts

Jiang

Huang

Shi

et al. 2021

IJERPH

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The patterns of green corridors in urban riverfront districts provide different synergistic cooling effects of blue-green space in urban areas. The purpose of this study is to quantify the spatial morphological impact of green corridors in riverfront block-scale area on the cooling effect. Three representative patterns (radiate, grid and dendritic) were selected in the study. The comprehensive influences analysis between multi-dimensional factors of spatial structure and morphology of green corridors and Ta (air temperature) distribution are processed by Envi-met4.4.5 simulation data and statistical analysis methods, such as regression tree model (BRT), were combined. The results showed that the D (distance from riverbank) has the greatest impact on the cooling effect of each belt green space. The D in the range of 600–750 m was affected by the cooling effect of blue-green space; The orientation with parallel to (southeast–northwest) or roughly the same as the prevailing wind direction (north–south) green corridors had relatively better cooling effect. When the width of green corridor was 20–25 m, the ME (marginal effect) of cooling was the largest; at 30–35 m (corridor width), the overall ME of cooling was the best; When the dPC (decreased probability connectivity, here the index was adapted to describe the connectivity degree) of green corridors was in the range of 0.5–1.5, the cooling effect of green corridor could be significantly improved. When dPC is 1.5, its marginal effect on temperature reached the maximum. The study provided a quantitative correlation technology for the morphological influence of blue-green space on the distribution of UCI (urban cooling island), which can guide the spatial layout control of green corridors in the planning and design of urban riverfront district.

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Section: Introductionmentioning

confidence: 99%

Cooling Island Effect of Blue-Green Corridors: Quantitative Comparison of Morphological Impacts

Jiang

Huang

Shi

et al. 2021

IJERPH

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“…The first was the change in surface radiation energy balance. In humid and semi-humid regions, the change in bare soil was relatively small, and the expansion of impervious surface area and loss of vegetation space were the main land change, which brought about an increase in land surface temperature and was easy to form urban heat island phenomena [58,59] due to the perceived energy change by the human body from impervious surface area to vegetation space. In contrast, in arid and semi-arid regions, the type of land change within the urban areas was dominated by both the expansion of impervious surface area and vegetation space and the loss of bare soil.…”

Section: Potential Environmental Effects Of Intra-urban Land Change In Africa During 2000-2020mentioning

confidence: 99%

Evaluating the Dynamic Changes of Urban Land and Its Fractional Covers in Africa from 2000–2020 Using Time Series of Remotely Sensed Images on the Big Data Platform

et al. 2021

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Dramatic urban land expansion and its internal sub-fraction change during 2000–2020 have taken place in Africa; however, the investigation of their spatial heterogeneity and dynamic change monitoring at the continental scale are rarely reported. Taking the whole of Africa as a study area, the synergic approach of normalized settlement density index and random forest was applied to assess urban land and its sub-land fractions (i.e., impervious surface area and vegetation space) in Africa, through time series of remotely sensed images on a cloud computing platform. The generated 30-m resolution urban land/sub-land products displayed good accuracy, with comprehensive accuracy of over 90%. During 2000–2020, the evaluated urban land throughout Africa increased from 1.93 × 104 km2 to 4.18 × 104 km2, with a total expansion rate of 116.49%, and the expanded urban area of the top six countries accounted for more than half of the total increments, meaning that the urban expansion was concentrated in several major countries. A turning green Africa was observed, with a continuously increasing ratio of vegetation space to built-up area and a faster increment of vegetation space than impervious surface area (i.e., 134.43% vs., 108.88%) within urban regions. A better living environment was also found in different urbanized regions, as the newly expanded urban area was characterized by lower impervious surface area fraction and higher vegetation fraction compared with the original urban area. Similarly, the humid/semi-humid regions also displayed a better living environment than arid/semi-arid regions. The relationship between socioeconomic development factors (i.e., gross domestic product and urban population) and impervious surface area was investigated and both passed the significance test (p < 0.05), with a higher fit value in the former than the latter. Overall, urban land and its fractional land cover change in Africa during 2000–2020 promoted the well-being of human settlements, indicating the positive effect on environments.

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“…Nevertheless, the rapid development of remote sensing techniques has enabled satellite images to acquire near-real-time data on detailed spatial surfaces. Therefore, to obtain high-resolution, consistent, and repetitive LST at the regional and global scales, remote sensing is the only practical and feasible way [ 8 , 9 , 10 , 11 , 12 ]. Many satellites carry thermal infrared sensors, such as MODIS/Terra and Aqua, advanced very high-resolution radiometer (AVHRR)/NOAA, and Landsat-8/TIRS [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of Retrieval Algorithms of Land Surface Temperature from Landsat-8 Data: A Case Study of Shanghai, China

Yue

Lin

2021

IJERPH

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In the trend of global warming and urbanization, frequent extreme weather has a severe impact on the lives of citizens. Land Surface Temperature (LST) is an essential climate variable and a vital parameter for land surface processes at local and global scales. Retrieving LST from global, regional, and city-scale thermal infrared remote sensing data has unparalleled advantages and is one of the most common methods used to study urban heat island effects. Different algorithms have been developed for retrieving LST using satellite imagery, such as the Radiative Transfer Equation (RTE), Mono-Window Algorithm (MWA), Split-Window Algorithm (SWA), and Single-Channel Algorithm (SCA). A case study was performed in Shanghai to evaluate these existing algorithms in the retrieval of LST from Landsat-8 images. To evaluate the estimated LST accurately, measured data from meteorological stations and the MOD11A2 product were used for validation. The results showed that the four algorithms could achieve good results in retrieving LST, and the LST retrieval results were generally consistent within a spatial scale. SWA is more suitable for retrieving LST in Shanghai during the summer, a season when the temperature and the humidity are both very high in Shanghai. Highest retrieval accuracy could be seen in cultivated land, vegetation, wetland, and water body. SWA was more sensitive to the error caused by land surface emissivity (LSE). In low temperature and a dry winter, RTE, SWA, and SCA are relatively more reliable. Both RTE and SCA were sensitive to the error caused by atmospheric water vapor content. These results can provide a reasonable reference for the selection of LST retrieval algorithms for different periods in Shanghai.

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Simulation of future land surface temperature distribution and evaluating surface urban heat island based on impervious surface area

Cited by 78 publications

References 73 publications

Cooling Island Effect of Blue-Green Corridors: Quantitative Comparison of Morphological Impacts

Cooling Island Effect of Blue-Green Corridors: Quantitative Comparison of Morphological Impacts

Evaluating the Dynamic Changes of Urban Land and Its Fractional Covers in Africa from 2000–2020 Using Time Series of Remotely Sensed Images on the Big Data Platform

A Comparative Analysis of Retrieval Algorithms of Land Surface Temperature from Landsat-8 Data: A Case Study of Shanghai, China

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