The land surface temperature (LST) pattern is treated as one of the primary indications of environmental impacts of land cover change. Researchers continue to explore the potential contribution of land surface to temperature rising. The LST-land surface relationship is dynamic and varies spatially. Based upon the previous studies, this research assumes that such dynamics is manifested at two levels: (1) the phenomenon level, and (2) its formation mechanism level. The research presents a workflow of exploring such dynamics at both levels. The variogram of the phenomenon and multi-scale analysis of the LST-land surface relationship are mutually interpreted. In the case study of Wuhan, China, the variogram of the LST indicates that the operational scale of the phenomenon is 500–650 m. It suggests the optimal scale to inspect the LST and its cause in the study area. This finding is verified and further inspected through multi-scale analysis of the LST–Impervious Surface Fraction (ISF) relationship at the formation mechanism level. The research also employs the Spatial Autocorrelation model to show how the ISF impacts the LST through scales. A flexible autocorrelation weight matrix is proposed and implemented in the model. The parameters of the model exhibit the thermal sensitivity of land surface and again represent the scale features. The Ordinary Least Square regression is used as the benchmark. Several implications are discussed.
|Number of pages||11|
|Journal||International Journal of Applied Earth Observation and Geoinformation|
|Issue number||part A|
|Early online date||16 Nov 2015|
|Publication status||Published - Mar 2016|
- Spatial dynamics