A Thermal Disaggregation Model Based on Trapezoid Interpolation

Abstract

A trapezoid interpolation thermal disaggregation (TI_DisTrad) model was proposed in this study. This model can disaggregate coarse resolution land surface temperature (LST) to fine resolution LST based on fractional vegetation cover (FVC) versus LST space. The proposed model assumes that the quantitative relationships among the Bowen ratio, FVC and LST can work for the pixels inside the FVC-LST space at both coarser and finer resolutions. Pixels that were outside the FVC-LST space were addressed with a support vector machine regression. We evaluated the TI_DisTrad model over an agricultural region in central Iowa (USA) and an urban region in Beijing (China). The performance of the TI_DisTrad model was assessed by comparing results against those of five other popular benchmark models. The results show that the TI_DisTrad model was slightly superior to three of the benchmark models over the agricultural regions and achieved more accurate LST compared to two of the benchmark models over the urban region. When using two surface energy balance models (the one-source model and the two-source model), the estimated evapotranspiration (ET) from the TI_DisTrad disaggregated LST data was more accurate than the estimated ET from the disaggregated LST obtained using the other benchmark approaches, corresponding to an increase in average accuracy of the TI_DisTrad model.