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The objective of this paper is to examine the scaling-up effect on the relationship between landscape patterns and land surface temperatures based on a case study of Indianapolis, United States. The integration of remote sensing, GIS, and landscape ecology methods was used in this study. Four TERRA ASTER images were acquired to derive the land-use and land-cover (LULC) patterns and land surface temperatures (LST) in different seasons. Each LULC and LST image was resampled to eight spatial scales: 15, 30, 60, 90, 120, 250, 500, and 1,000 m. The scaling-up effect on the spatial and ecological characteristics of landscape patterns and LSTs were examined by the use of landscape metrics. Optimal spatial resolutions were determined on the basis of the minimum distance in the landscape metric spaces. The results show that the patch percentages of LULC and LST patches were not strongly affected by the scaling-up process in different seasons. The patch densities and landscape shape indices and LST patches kept decreasing across the scales without distinct seasonal differences. Thirty meters was found to be the optimal resolution in the study of the relationship between urban LULC and LST classes. Ninety meters was found to be the optimal spatial resolution for assessing the landscape-level relationship between LULC and LST patterns. This paper may provide useful information for urban planners and environmental practitioners to manage urban landscapes and urban thermal environments as a result of urbanization.
Hua et al. (Sun,) studied this question.