Evaluation of Landsat-8 TIRS data recalibrations and land surface temperature split-window algorithms over a homogeneous crop area with different phenological land covers

Successive re-calibrations were implemented in Landsat-8 TIRS data since launch. This paper evaluates the performances of both: (1) these re-calibrations, up to the last calibration update announced for TIRS data in the next Landsat Collection 2; and (2) single-channel (SC) corrections and split-win...

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Bibliographic Details
Published in:ISPRS journal of photogrammetry and remote sensing 2021-04, Vol.174, p.237-253
Main Authors: Niclòs, Raquel, Puchades, Jesús, Coll, César, Barberà, María J., Pérez-Planells, Lluís, Valiente, José A., Sánchez, Juan M.
Format: Article
Language:English
Subjects:
Calibration
In-situ measurements
Landsat-8 TIRS
LST algorithms
Thermal-infrared
Validation
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Summary:Successive re-calibrations were implemented in Landsat-8 TIRS data since launch. This paper evaluates the performances of both: (1) these re-calibrations, up to the last calibration update announced for TIRS data in the next Landsat Collection 2; and (2) single-channel (SC) corrections and split-window (SW) algorithms to retrieve land surface temperature (LST) from TIRS data. A robust and accurate multi-year (2014–2019) set of reference ground data were used, which included thermal infrared (TIR) radiance measurements taken along transects in a uniform and thermally homogeneous rice paddy area, but also emissivity measurements for the different ground covers at the site through the year. The calibration results showed significant biases at the site for data after the 2014 reprocessing, but negligible biases and root-mean-square differences (RMSDs)
ISSN:0924-2716
1872-8235
DOI:10.1016/j.isprsjprs.2021.02.005