Quantifying and simulating landscape composition and pattern impacts on land surface temperature: A decadal study of the rapidly urbanizing city of Beijing, China
The increase in impervious surfaces due to the urbanization has caused many adverse effects on urban ecological systems, including the urban heat environmental risk. Revealing the relationship between landscape composition and pattern and land surface temperature (LST) gives insight into how to effe...
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Published in | The Science of the total environment Vol. 654; pp. 430 - 440 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier B.V
01.03.2019
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Subjects | |
Online Access | Get full text |
ISSN | 0048-9697 1879-1026 1879-1026 |
DOI | 10.1016/j.scitotenv.2018.11.108 |
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Abstract | The increase in impervious surfaces due to the urbanization has caused many adverse effects on urban ecological systems, including the urban heat environmental risk. Revealing the relationship between landscape composition and pattern and land surface temperature (LST) gives insight into how to effectively mitigate the urban heat island (UHI) effect. It is also essential to simulate and optimize the distribution of impervious surfaces in urban planning. In this study, the multi-scale relationship between impervious surface and LST in Beijing was analyzed. Different distributions of land cover types and the corresponding LSTs were simulated under two development scenarios. Various geospatial approaches, including geographic information system (GIS), remote sensing, and the Conversion of Land Use and its Effects at Small regional extent (CLUE-S), were used to facilitate the analysis. The results showed that (1) impervious surfaces increased from 36.76% to 44.95% of the total area between 2005 and 2015 and the mean LST of impervious surfaces was approximately 2 °C higher than that of the areas with vegetation cover; (2) impervious surfaces had a positive logarithmic correlation with LST, while the vegetation coverage had a negative linear correlation with LST; (3) as the grid size increased, the correlation coefficients between the impervious surface density and mean LST increased at different magnitudes, and the correlation coefficients stabilized after the scale of 900 × 900 m; (4) large and contiguous patches of impervious surfaces aggravated the UHI effect when the total percentage of impervious surface remained the same; and (5) to achieve an improved and healthier urban living environment, populations controls should be considered to decrease future impervious surface demands by 7.69%—which corresponds to an average LST decrease of 1.1 °C. Landscape distribution and configuration should also be better integrated into landscape and urban planning.
[Display omitted]
•The mean LST of IS is 2 °C higher than that of vegetation coverage area in average.•LST had positive correlation with IS density and aggregation at multiple resolution.•The correlation coefficient of IS density and LST increased with larger scale.•The density and aggregation of IS should be considered in urban planning. |
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AbstractList | The increase in impervious surfaces due to the urbanization has caused many adverse effects on urban ecological systems, including the urban heat environmental risk. Revealing the relationship between landscape composition and pattern and land surface temperature (LST) gives insight into how to effectively mitigate the urban heat island (UHI) effect. It is also essential to simulate and optimize the distribution of impervious surfaces in urban planning. In this study, the multi-scale relationship between impervious surface and LST in Beijing was analyzed. Different distributions of land cover types and the corresponding LSTs were simulated under two development scenarios. Various geospatial approaches, including geographic information system (GIS), remote sensing, and the Conversion of Land Use and its Effects at Small regional extent (CLUE-S), were used to facilitate the analysis. The results showed that (1) impervious surfaces increased from 36.76% to 44.95% of the total area between 2005 and 2015 and the mean LST of impervious surfaces was approximately 2 °C higher than that of the areas with vegetation cover; (2) impervious surfaces had a positive logarithmic correlation with LST, while the vegetation coverage had a negative linear correlation with LST; (3) as the grid size increased, the correlation coefficients between the impervious surface density and mean LST increased at different magnitudes, and the correlation coefficients stabilized after the scale of 900 × 900 m; (4) large and contiguous patches of impervious surfaces aggravated the UHI effect when the total percentage of impervious surface remained the same; and (5) to achieve an improved and healthier urban living environment, populations controls should be considered to decrease future impervious surface demands by 7.69%—which corresponds to an average LST decrease of 1.1 °C. Landscape distribution and configuration should also be better integrated into landscape and urban planning. The increase in impervious surfaces due to the urbanization has caused many adverse effects on urban ecological systems, including the urban heat environmental risk. Revealing the relationship between landscape composition and pattern and land surface temperature (LST) gives insight into how to effectively mitigate the urban heat island (UHI) effect. It is also essential to simulate and optimize the distribution of impervious surfaces in urban planning. In this study, the multi-scale relationship between impervious surface and LST in Beijing was analyzed. Different distributions of land cover types and the corresponding LSTs were simulated under two development scenarios. Various geospatial approaches, including geographic information system (GIS), remote sensing, and the Conversion of Land Use and its Effects at Small regional extent (CLUE-S), were used to facilitate the analysis. The results showed that (1) impervious surfaces increased from 36.76% to 44.95% of the total area between 2005 and 2015 and the mean LST of impervious surfaces was approximately 2 °C higher than that of the areas with vegetation cover; (2) impervious surfaces had a positive logarithmic correlation with LST, while the vegetation coverage had a negative linear correlation with LST; (3) as the grid size increased, the correlation coefficients between the impervious surface density and mean LST increased at different magnitudes, and the correlation coefficients stabilized after the scale of 900 × 900 m; (4) large and contiguous patches of impervious surfaces aggravated the UHI effect when the total percentage of impervious surface remained the same; and (5) to achieve an improved and healthier urban living environment, populations controls should be considered to decrease future impervious surface demands by 7.69%—which corresponds to an average LST decrease of 1.1 °C. Landscape distribution and configuration should also be better integrated into landscape and urban planning. [Display omitted] •The mean LST of IS is 2 °C higher than that of vegetation coverage area in average.•LST had positive correlation with IS density and aggregation at multiple resolution.•The correlation coefficient of IS density and LST increased with larger scale.•The density and aggregation of IS should be considered in urban planning. The increase in impervious surfaces due to the urbanization has caused many adverse effects on urban ecological systems, including the urban heat environmental risk. Revealing the relationship between landscape composition and pattern and land surface temperature (LST) gives insight into how to effectively mitigate the urban heat island (UHI) effect. It is also essential to simulate and optimize the distribution of impervious surfaces in urban planning. In this study, the multi-scale relationship between impervious surface and LST in Beijing was analyzed. Different distributions of land cover types and the corresponding LSTs were simulated under two development scenarios. Various geospatial approaches, including geographic information system (GIS), remote sensing, and the Conversion of Land Use and its Effects at Small regional extent (CLUE-S), were used to facilitate the analysis. The results showed that (1) impervious surfaces increased from 36.76% to 44.95% of the total area between 2005 and 2015 and the mean LST of impervious surfaces was approximately 2 °C higher than that of the areas with vegetation cover; (2) impervious surfaces had a positive logarithmic correlation with LST, while the vegetation coverage had a negative linear correlation with LST; (3) as the grid size increased, the correlation coefficients between the impervious surface density and mean LST increased at different magnitudes, and the correlation coefficients stabilized after the scale of 900 × 900 m; (4) large and contiguous patches of impervious surfaces aggravated the UHI effect when the total percentage of impervious surface remained the same; and (5) to achieve an improved and healthier urban living environment, populations controls should be considered to decrease future impervious surface demands by 7.69%-which corresponds to an average LST decrease of 1.1 °C. Landscape distribution and configuration should also be better integrated into landscape and urban planning.The increase in impervious surfaces due to the urbanization has caused many adverse effects on urban ecological systems, including the urban heat environmental risk. Revealing the relationship between landscape composition and pattern and land surface temperature (LST) gives insight into how to effectively mitigate the urban heat island (UHI) effect. It is also essential to simulate and optimize the distribution of impervious surfaces in urban planning. In this study, the multi-scale relationship between impervious surface and LST in Beijing was analyzed. Different distributions of land cover types and the corresponding LSTs were simulated under two development scenarios. Various geospatial approaches, including geographic information system (GIS), remote sensing, and the Conversion of Land Use and its Effects at Small regional extent (CLUE-S), were used to facilitate the analysis. The results showed that (1) impervious surfaces increased from 36.76% to 44.95% of the total area between 2005 and 2015 and the mean LST of impervious surfaces was approximately 2 °C higher than that of the areas with vegetation cover; (2) impervious surfaces had a positive logarithmic correlation with LST, while the vegetation coverage had a negative linear correlation with LST; (3) as the grid size increased, the correlation coefficients between the impervious surface density and mean LST increased at different magnitudes, and the correlation coefficients stabilized after the scale of 900 × 900 m; (4) large and contiguous patches of impervious surfaces aggravated the UHI effect when the total percentage of impervious surface remained the same; and (5) to achieve an improved and healthier urban living environment, populations controls should be considered to decrease future impervious surface demands by 7.69%-which corresponds to an average LST decrease of 1.1 °C. Landscape distribution and configuration should also be better integrated into landscape and urban planning. |
Author | Wang, Qingrui Zhang, Yan Guo, Lijia Liu, Ruimin Men, Cong Miao, Yuexi |
Author_xml | – sequence: 1 givenname: Lijia surname: Guo fullname: Guo, Lijia – sequence: 2 givenname: Ruimin surname: Liu fullname: Liu, Ruimin email: liurm@bnu.edu.cn – sequence: 3 givenname: Cong surname: Men fullname: Men, Cong – sequence: 4 givenname: Qingrui surname: Wang fullname: Wang, Qingrui – sequence: 5 givenname: Yuexi surname: Miao fullname: Miao, Yuexi – sequence: 6 givenname: Yan surname: Zhang fullname: Zhang, Yan |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30447581$$D View this record in MEDLINE/PubMed |
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Keywords | Urbanization Impervious surface area Land use simulation Land surface temperature Multi-scale relationship Remote sensing |
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SubjectTerms | China environmental impact geographic information systems heat heat island Impervious surface area Land surface temperature land use Land use simulation landscapes Multi-scale relationship Remote sensing risk surface temperature urban planning Urbanization vegetation cover vegetation types |
Title | Quantifying and simulating landscape composition and pattern impacts on land surface temperature: A decadal study of the rapidly urbanizing city of Beijing, China |
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