A comparative study of land surface temperature retrieval methods from remote sensing data

摘要

The main purpose of this paper is to describe, compare, and analyze the various extraction methods for landnsurface temperature (LST) in terms of their computational algorithms, their different input parameters, and their relativenaccuracy to make them more readily usable by a broader cross-section of nontechnical practitioners. Due to thenheterogeneity of most natural land surfaces, the atmospheric influence, and a wide variety of satellite sensors, thenestimation and validation of LST can be difficult. Furthermore, the large number of algorithms developed to deal withnthis heterogeneity has led to widespread confusion on how and when to use one algorithm versus another. This papernprovides a concise, but thorough, overview of the different algorithms used for the estimation of land surface temperaturenas well as a comparative list of methods and associated parameters that facilitate, to the general user, the selection andnapplication of the most appropriate method for LST extraction given the situation at hand. We restricted our analysis fornthe single-channel algorithms to two models. We included a two-channel algorithm (or split-window when it is applied innthe region 10u000212.5 mm) according to the literature. The Temperature Emissivity Separation algorithm was also taken intonaccount. The determination of the key parameters needed to execute these algorithms is presented.