Assessment of single-channel algorithms for land surface temperature retrieval at two southern Brazil sites

P.S. Käfer, S.B.A. Rolim, L.V.O. Heinz, M.L. Iglesias, N.S. Da Rocha, L.R. Diaz

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

© 2020 Society of Photo-Optical Instrumentation Engineers (SPIE).Land surface temperature (LST) is an essential parameter in investigating environmental, ecological processes and climate change, and thermal infrared remote sensing is a useful tool to acquire information regarding LST. Several accurate LST retrieval methodologies have been developed or refined in recent years and have demonstrated great potential. An assessment of various recent LST inversion single-channel (SC) algorithms is presented. These algorithms include improved mono-window, SC, and improved single channel (ISC). We compared the methods using two Brazilian sites, in which two kinds of validation were performed: field measurements with the satellite overpass and a comparative analysis using the web-based Atmospheric Correction Parameter Calculator tool and the radiative transfer equation (RTE) (assumed as reference). The three methods showed high coefficient of determination with the RTE (between 0.9 and 0.98). SC algorithm produced the furthest results from the reference and was statistically different. ISC algorithm provided the most reliable LST estimates, yielding root mean square errors between 1.53 and 1.91 K. LST can be retrieved through ISC algorithm only using meteorological station data, thus being an alternative for regions where radiosonde points have low density. Our findings contribute to more operational LST products from the Landsat series in humid places.
Original languageEnglish
Article number016507
JournalJournal of Applied Remote Sensing
Volume14
Issue number1
DOIs
Publication statusPublished - 1 Jan 2020
Externally publishedYes

Funding

The Landsat 8 OLI/TIRS products are a courtesy of the US Geological Survey Earth Resources Observation and Science Center. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brazil (finance code 001) and Conselho Nacional de Desenvolvimento Científico e Tecnológico. The authors declare no conflict of interest. The Landsat 8 OLI/TIRS products are a courtesy of the US Geological Survey Earth Resources Observation and Science Center. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (finance code 001) and Conselho Nacional de Desenvolvimento Científico e Tecnológico. The authors declare no conflict of interest.

FundersFunder number
US Geological Survey Earth Resources Observation and Science Center
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Conselho Nacional de Desenvolvimento Científico e Tecnológico

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