Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach

The present study was aimed to investigate how and to what extent urban land surface temperature (ULST) is affected by spatial pattern of green cover patch in an urban ambient in Isfahan, Iran. To materialize the effects of spatial pattern of green cover on ULST, Landsat ETM + image data on May 5, 2002 was acquired to be processed for ULST estimation and to generate Land Use/Land Cover (LULC) classes. Given to five percent of total available cells with a randomized distribution across the built-up areas, the linkage between ULST and composition, configuration and structure of green cover class was quantified. Five patch level landscape metrics including nearest distance (ND), patch area (AREA), perimeter to area (PARA), shape index (SHAPE) and core area index (CAI) were chosen and applied as explaining variables in statistical analyses due to their potential effects on ULST. Results of the present study have revealed that all the landscape metrics values of the green cover class were significantly correlated to their nearest ULST sample points, amongst which a stronger linkage was observed between ND (r = 0.611, p < 0.05) and ULST compared to others. Stepwise generalized additive modeling method-based multiple linear regression model was then fitted to dataset and resulted in developing the model (r(2) = 0.41, p < 0.05), explaining the relationship between spatial pattern of green cover and ULST. Finally, we concluded that the present study could provide additional level of knowledge through which urban planners can optimize composition, configuration and structure of green cover patches to mitigate the adverse impacts of LST phenomenon especially where urbanization is still ongoing.