Revision of the Single-Channel Algorithm for Land Surface Temperature Retrieval From Landsat Thermal-Infrared Data

By J. Jiménez-Muñoz, Jordi Cristóbal, José A. Sobrino, G. Sòria, Miquel Ninyerola, Xavier Pons. IEEE Transactions on Geoscience and Remote Sensing, 2009

580 citations recorded by the source corpus.

This paper presents a revision, an update, and an extension of the generalized single-channel (SC) algorithm developed by Jimenez-Munoz and Sobrino (2003), which was particularized to the thermal-infrared (TIR) channel (band 6) located in the Landsat-5 Thematic Mapper (TM) sensor. The SC algorithm relies on the concept of atmospheric functions (AFs) which are dependent on atmospheric transmissivity and upwelling and downwelling atmospheric radiances. These AFs are fitted versus the atmospheric water vapor content for operational purposes. In this paper, we present updated fits using MODTRAN 4 radiative transfer code, and we also extend the application of the SC algorithm to the TIR channel of the TM sensor onboard the Landsat-4 platform and the enhanced TM plus sensor onboard the Landsat-7 platform. Five different atmospheric sounding databases have been considered to create simulated data used for retrieving AFs and to test the algorithm. The test from independent simulated data provided root mean square error (rmse) values below 1 K in most cases when atmospheric water vapor content is lower than 2 g middotcm-2. For values higher than 3 g middotcm-2, errors are not acceptable, as what occurs with other SC algorithms. Results were also tested using a land surface temperature map obtained from one Landsat-5 image acquired over an agricultural area using inversion of the radiative transfer equation and the atmospheric profile measured in situ at the sensor overpass time. The comparison with this ldquoground-truthrdquo map provided an rmse of 1.5 K.

Subfields: Ecology, Environmental Engineering, Media Technology

View Paper: https://www.semanticscholar.org/paper/afcce617f4dd83319457e923e8d761c349f3fa8d

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Citations in the corpus

An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data (2015, background): “[19], in which the feasibility had been analyzed through look-up tables (LUTs) to avoid the problem relevant to uncertainties introduced from fitting the atmospheric parameters to water vapor content for their estimation.”
Land Surface Temperature Retrieval from Landsat 8 TIRS - Comparison between Radiative Transfer Equation-Based Method, Split Window Algorithm and Single Channel Method (2014, methodology): “The SC method has been applied to Landsat 5 TM, Landsat 7 ETM+, MODIS ASTER and ENVISAT AATSR sensors’ TIR bands for LST retrieval [10,12,33,35].”
Local regression models for spatial interpolation of urban heat island—an example from Wrocław, SW Poland (2012, methodology): “applied using single-channel algorithm (Jiménez-Muñoz et al. 2009).”
Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation (2020, methodology): “In this study, LST retrieval algorithms, namely, Radiative Transfer Equation (RTE) method [39,42], Single Channel Algorithm (SCA) [44] and Mono Window Algorithm (MWA) [43] were evaluated using Landsat 5 Thematic Mapper (TM), 7 Enhanced Thematic Mapper Plus (ETM+) and 8 Operational Land Imager (OLI) ”
Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data (2014, methodology): “[9] retrieves LST (Ts) using the following general equation:”