Assessment of green space cooling effects in dense urban landscape: a case study of Delhi, India

Abstract

Most noticeable and direct impacts of urbanization on the environment is the changes in daily and seasonal thermal variable and increase the hydraulic stress. Both are cumulatively formed the urban heat island (UHI) effects. From the sustainability point of view, it is very crucial for research to focus on how to mitigate UHI. Therefore, objective of this study is to evaluate the cooling effects of different types of urban greenery at local and park level. For land surface temperature, Landsat 8—TIRS and for greenery mapping Sentinel 2A imageries have been used. LST was derived using the single channel algorithm, and greenery was mapping using combination of unsupervised (i.e., ISODATA) and supervised (i.e., maximum likelihood) image classification techniques. Numbers of class level metrics like PLAND PD; LPI; AREA_MN etc. used to measure composition and configuration of urban greenery. Ordinary least square regression, multiple linear regression, and spatial auto-regression model were used to measure the cooling effects of urban green space quantitatively. Besides, park level analysis also was done using park cooling intensity (PCI) and its relationship with park land use. Results shows that amount of urban greenery in terms of percentage of land cover or average size of the green patch is very important to reduce the UHI. PLAND, LPI, AREA_MN and COHESION negatively related with LST whereas PD, LSI, SHAPE_MN, and ENN_MN positively related with LST. So, fragmented vegetation area, green space with complex shape could increase the LST. If we look at the vegetation types and relation with LST, only dense vegetation and trees and plantation can effectively reduce the LST. Besides PCI negatively related with amount of built-up area and open space within parks. Finally, this study can help to the urban and land use planning to build a heat resilience city.