A general spectral bandpass adjustment function (SBAF) for harmonizing landsat-sentinel over inland and coastal waters

Landsat 8/9 Operational Land Imager (OLI) and Sentinel-2 Multispectral Imager (MSI) are the most relevant medium spatial resolution data sources for aquatic applications, and integrating these spectral images into a single product constellation offers significant potential for monitoring dynamic pro...

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Main Authors: Thainara M.A. Lima, Vitor S. Martins, Rejane S. Paulino, Cassia B. Caballero, Daniel A. Maciel, Claudia Giardino
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Science of Remote Sensing
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666017225000318
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author Thainara M.A. Lima
Vitor S. Martins
Rejane S. Paulino
Cassia B. Caballero
Daniel A. Maciel
Claudia Giardino
author_facet Thainara M.A. Lima
Vitor S. Martins
Rejane S. Paulino
Cassia B. Caballero
Daniel A. Maciel
Claudia Giardino
author_sort Thainara M.A. Lima
collection DOAJ
description Landsat 8/9 Operational Land Imager (OLI) and Sentinel-2 Multispectral Imager (MSI) are the most relevant medium spatial resolution data sources for aquatic applications, and integrating these spectral images into a single product constellation offers significant potential for monitoring dynamic processes over coastal and inland waters. Due to water's inherently low reflectance values, small differences in the relative spectral responses (RSR) between the two sensors can result in significant discrepancies in water reflectance retrievals. To ensure compatibility and consistency in harmonized products for aquatic studies, spectral bandpass adjustment function (SBAF) for cross-calibration between OLI and MSI sensors must be carefully derived and applied. This study provides a global analysis of 4047 match-ups of atmospherically corrected Landsat-8/9 OLI and Sentinel-2 A/B MSI L1 products over inland and coastal waters to generate a new general SBAF for aquatic studies. Atmospheric correction was performed using the 6 S V radiative transfer model, a widely validated approach for aquatic remote sensing applications. The selected images were sensed ≤30 min apart on the same day, under <5 % cloud cover, ≤5° solar zenith difference across different atmospheric conditions and aquatic systems (928 coastal and inland water bodies) over the world. A robust quality-controlled protocol was developed to remove low-quality image pairs under sun/sky glint, ice/snow surface, and cirrus clouds. Following this procedure, 2,2 million quality filtered water reflectance pixels were extracted. The SBAF coefficients (i.e., slope and offset) were derived through statistical regression between Landsat-8/9 and Sentinel-2 reflectance values. Additionally, we simulated sensor band responses using a global in-situ hyperspectral water dataset and calculated the SBAF coefficients for comparison with the pixel-based results. The application of SBAF was demonstrated through comparative analyses of spectral reflectance from Landsat-8/9 and Sentinel-2 before and after the cross-calibration. Our findings underscore the effectiveness of these coefficients in reducing spectral discrepancies between Landsat-8/9 and Sentinel-2 water reflectance measurements.
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spelling doaj-art-55bcd9ec7f9741a6989d17025d8a22292025-08-20T03:21:43ZengElsevierScience of Remote Sensing2666-01722025-06-011110022510.1016/j.srs.2025.100225A general spectral bandpass adjustment function (SBAF) for harmonizing landsat-sentinel over inland and coastal watersThainara M.A. Lima0Vitor S. Martins1Rejane S. Paulino2Cassia B. Caballero3Daniel A. Maciel4Claudia Giardino5Department of Agricultural &amp; Biological Engineering, Mississippi State University (MSU), Starkville, MS 39762, USA; Corresponding author.Department of Agricultural &amp; Biological Engineering, Mississippi State University (MSU), Starkville, MS 39762, USA; Corresponding author.Department of Agricultural &amp; Biological Engineering, Mississippi State University (MSU), Starkville, MS 39762, USADepartment of Agricultural &amp; Biological Engineering, Mississippi State University (MSU), Starkville, MS 39762, USAInstrumentation Laboratory for Aquatic Systems (LabISA), Earth Sciences General Coordination of the National Institute for Space Research (INPE), São José Dos Campos, SP, BrazilConsiglio Nazionale Delle Ricerche, Istituto per Il Rilevamento Elettromagnetico Dell'Ambiente (CNR-IREA), Milan, ItalyLandsat 8/9 Operational Land Imager (OLI) and Sentinel-2 Multispectral Imager (MSI) are the most relevant medium spatial resolution data sources for aquatic applications, and integrating these spectral images into a single product constellation offers significant potential for monitoring dynamic processes over coastal and inland waters. Due to water's inherently low reflectance values, small differences in the relative spectral responses (RSR) between the two sensors can result in significant discrepancies in water reflectance retrievals. To ensure compatibility and consistency in harmonized products for aquatic studies, spectral bandpass adjustment function (SBAF) for cross-calibration between OLI and MSI sensors must be carefully derived and applied. This study provides a global analysis of 4047 match-ups of atmospherically corrected Landsat-8/9 OLI and Sentinel-2 A/B MSI L1 products over inland and coastal waters to generate a new general SBAF for aquatic studies. Atmospheric correction was performed using the 6 S V radiative transfer model, a widely validated approach for aquatic remote sensing applications. The selected images were sensed ≤30 min apart on the same day, under <5 % cloud cover, ≤5° solar zenith difference across different atmospheric conditions and aquatic systems (928 coastal and inland water bodies) over the world. A robust quality-controlled protocol was developed to remove low-quality image pairs under sun/sky glint, ice/snow surface, and cirrus clouds. Following this procedure, 2,2 million quality filtered water reflectance pixels were extracted. The SBAF coefficients (i.e., slope and offset) were derived through statistical regression between Landsat-8/9 and Sentinel-2 reflectance values. Additionally, we simulated sensor band responses using a global in-situ hyperspectral water dataset and calculated the SBAF coefficients for comparison with the pixel-based results. The application of SBAF was demonstrated through comparative analyses of spectral reflectance from Landsat-8/9 and Sentinel-2 before and after the cross-calibration. Our findings underscore the effectiveness of these coefficients in reducing spectral discrepancies between Landsat-8/9 and Sentinel-2 water reflectance measurements.http://www.sciencedirect.com/science/article/pii/S2666017225000318Sentinel-2Landsat-8/9SBAFRadiometric cross-calibrationInland watersCoastal waters
spellingShingle Thainara M.A. Lima
Vitor S. Martins
Rejane S. Paulino
Cassia B. Caballero
Daniel A. Maciel
Claudia Giardino
A general spectral bandpass adjustment function (SBAF) for harmonizing landsat-sentinel over inland and coastal waters
Science of Remote Sensing
Sentinel-2
Landsat-8/9
SBAF
Radiometric cross-calibration
Inland waters
Coastal waters
title A general spectral bandpass adjustment function (SBAF) for harmonizing landsat-sentinel over inland and coastal waters
title_full A general spectral bandpass adjustment function (SBAF) for harmonizing landsat-sentinel over inland and coastal waters
title_fullStr A general spectral bandpass adjustment function (SBAF) for harmonizing landsat-sentinel over inland and coastal waters
title_full_unstemmed A general spectral bandpass adjustment function (SBAF) for harmonizing landsat-sentinel over inland and coastal waters
title_short A general spectral bandpass adjustment function (SBAF) for harmonizing landsat-sentinel over inland and coastal waters
title_sort general spectral bandpass adjustment function sbaf for harmonizing landsat sentinel over inland and coastal waters
topic Sentinel-2
Landsat-8/9
SBAF
Radiometric cross-calibration
Inland waters
Coastal waters
url http://www.sciencedirect.com/science/article/pii/S2666017225000318
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