Disaggregation of remotely sensed land surface temperature: A simple yet flexible index (SIFI) to assess method performances

To better assess DLST method performances under diversified scenarios, we formulated five protocols, through which a simple yet flexible index (SIFI) was subsequently designed. The establishment of an SIFI includes the following four steps: (1) a detail-based evaluation, which is designed primarily to exclude the impacts of systematic deviations on estimated LSTs; (2) a Gaussian normalization, which is primarily intended to remove the differences in temperature units and thermal contrasts; (3) a triple comparison, with the aim of attenuating the influence of the difference in the resolution ratio in comparisons of method performances; and (4) a piecewise comparison, which is primarily scheduled to distinguish among the three sharpening statuses, under-sharpening, acceptable over-sharpening, and unacceptable over-sharpening. The evaluation ability of SIFI was compared with those of the RMSE, Erreur Relative Globale Adimensionnelle de Synthèse (ERGAS), and image quality index (Q) using simulation tests and actual thermal data. The results illustrate that SIFI generally outperforms the other indexes; it is able to mitigate the impacts from process errors and controls during evaluation and is able to indicate the sharpening statuses accurately. We believe this new index will likely promote the design of future DLST algorithms and procedures.