Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea

Sea surface temperature (SST) is a key hydrological variable which can be monitored via satellite. One source of thermal data with a spatial resolution high enough to study sub-mesoscale processes in coastal waters may be the Landsat mission. The Thermal Infrared Sensor on board Landsat 8 collects d...

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Autor principal:	Katarzyna Bradtke
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	sea surface temperature NLSST coefficients Baltic Landsat 8 TIRS Science Q
Acceso en línea:	https://doaj.org/article/d06e40a9f4f3467c9d726d2923e5688c
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spelling	oai:doaj.org-article:d06e40a9f4f3467c9d726d2923e5688c2021-11-25T18:54:49ZLandsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea10.3390/rs132246192072-4292https://doaj.org/article/d06e40a9f4f3467c9d726d2923e5688c2021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4619https://doaj.org/toc/2072-4292Sea surface temperature (SST) is a key hydrological variable which can be monitored via satellite. One source of thermal data with a spatial resolution high enough to study sub-mesoscale processes in coastal waters may be the Landsat mission. The Thermal Infrared Sensor on board Landsat 8 collects data in two bands, which allows for the use of the well-known nonlinear split-window formula to estimate SST (NLSST) using top-of-the-atmosphere (TOA) brightness temperature. To calibrate its coefficients a significant number of matchup points are required, representing a wide range of atmospheric conditions. In this study over 1200 granules of satellite data and 12 time series of in situ measurements from buoys and platforms operating in the Baltic Sea over a period of more than 6 years were used to select matchup points, derive NLSST coefficients and evaluate the results. To filter out pixels contaminated by clouds, ice or land influences, the IdePix algorithm was used with Quality Assessment Band and additional test of the adjacent pixels. Various combinations of flags were tested. The results show that the NLSST coefficients derived previously for coastal areas, characterised by a more humid atmosphere, might overestimate low SST values. Formulas derived for the Baltic Sea produced biases close to 0 °C and RMSEs in the range of 0.49–0.52 °C.Katarzyna BradtkeMDPI AGarticlesea surface temperatureNLSST coefficientsBalticLandsat 8 TIRSScienceQENRemote Sensing, Vol 13, Iss 4619, p 4619 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	sea surface temperature NLSST coefficients Baltic Landsat 8 TIRS Science Q
spellingShingle	sea surface temperature NLSST coefficients Baltic Landsat 8 TIRS Science Q Katarzyna Bradtke Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea
description	Sea surface temperature (SST) is a key hydrological variable which can be monitored via satellite. One source of thermal data with a spatial resolution high enough to study sub-mesoscale processes in coastal waters may be the Landsat mission. The Thermal Infrared Sensor on board Landsat 8 collects data in two bands, which allows for the use of the well-known nonlinear split-window formula to estimate SST (NLSST) using top-of-the-atmosphere (TOA) brightness temperature. To calibrate its coefficients a significant number of matchup points are required, representing a wide range of atmospheric conditions. In this study over 1200 granules of satellite data and 12 time series of in situ measurements from buoys and platforms operating in the Baltic Sea over a period of more than 6 years were used to select matchup points, derive NLSST coefficients and evaluate the results. To filter out pixels contaminated by clouds, ice or land influences, the IdePix algorithm was used with Quality Assessment Band and additional test of the adjacent pixels. Various combinations of flags were tested. The results show that the NLSST coefficients derived previously for coastal areas, characterised by a more humid atmosphere, might overestimate low SST values. Formulas derived for the Baltic Sea produced biases close to 0 °C and RMSEs in the range of 0.49–0.52 °C.
format	article
author	Katarzyna Bradtke
author_facet	Katarzyna Bradtke
author_sort	Katarzyna Bradtke
title	Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea
title_short	Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea
title_full	Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea
title_fullStr	Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea
title_full_unstemmed	Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea
title_sort	landsat 8 data as a source of high resolution sea surface temperature maps in the baltic sea
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/d06e40a9f4f3467c9d726d2923e5688c
work_keys_str_mv	AT katarzynabradtke landsat8dataasasourceofhighresolutionseasurfacetemperaturemapsinthebalticsea
_version_	1718410555161575424

Landsat 8 Data as a Source of High Resolution Sea Surface Temperature Maps in the Baltic Sea

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