Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Quantifying the Impact of Urban Green Space Pattern to Land Surface Temperature: Evidence from an Urban Agglomeration of Eastern India
Understanding the spatial pattern of urban green space is largely recommended for the mitigation of urban heat island (UHI) effect. Previous researches have examined the complex relationship between green space patterns and land surface temperature (LST) but the contribution of pattern of green space is remained less explored. Therefore, this study attempted to study the variations of green space at neighborhood level during six temporal periods and to identify the relative contribution of composition and configuration of green space patterns to LST. The study is based on English Bazar urban agglomeration and its peri-urban areas. Landsat TM and OLI images with 30 m resolution were used for the extraction of green space and LST. Landscape metrics were used for identifying different patterns of green space at neighborhood level using Fragstat 4.2. Pearson correlation, stepwise regression, and hierarchical partitioning methods were used to understand this complex relationship. The result shows that there is a loss of nearly 11 km2 (5.17%) green space between 1990 and 2015. Green space configuration and composition directly affect LST though the magnitude of contribution of different green space patterns varies. It is observed that LST is negatively correlated with percentage of green space for all the periods. Variance partitioning indicates that percentage of green space and mean area of patches are the most powerful index in influencing LST for all the year. The result of study finally emphasizes the importance of the configuration of green space patches to mitigate UHI effect and for adaptation strategies.
Quantifying the Impact of Urban Green Space Pattern to Land Surface Temperature: Evidence from an Urban Agglomeration of Eastern India
Understanding the spatial pattern of urban green space is largely recommended for the mitigation of urban heat island (UHI) effect. Previous researches have examined the complex relationship between green space patterns and land surface temperature (LST) but the contribution of pattern of green space is remained less explored. Therefore, this study attempted to study the variations of green space at neighborhood level during six temporal periods and to identify the relative contribution of composition and configuration of green space patterns to LST. The study is based on English Bazar urban agglomeration and its peri-urban areas. Landsat TM and OLI images with 30 m resolution were used for the extraction of green space and LST. Landscape metrics were used for identifying different patterns of green space at neighborhood level using Fragstat 4.2. Pearson correlation, stepwise regression, and hierarchical partitioning methods were used to understand this complex relationship. The result shows that there is a loss of nearly 11 km2 (5.17%) green space between 1990 and 2015. Green space configuration and composition directly affect LST though the magnitude of contribution of different green space patterns varies. It is observed that LST is negatively correlated with percentage of green space for all the periods. Variance partitioning indicates that percentage of green space and mean area of patches are the most powerful index in influencing LST for all the year. The result of study finally emphasizes the importance of the configuration of green space patches to mitigate UHI effect and for adaptation strategies.
Quantifying the Impact of Urban Green Space Pattern to Land Surface Temperature: Evidence from an Urban Agglomeration of Eastern India
GIScience & Geo-environmental Modelling
Rahman, Atiqur (Herausgeber:in) / Sen Roy, Shouraseni (Herausgeber:in) / Talukdar, Swapan (Herausgeber:in) / Shahfahad (Herausgeber:in) / Dutta, Ipsita (Autor:in) / Das, Arijit (Autor:in)
04.03.2023
17 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
| DOAJ | 2022