Overslaan en naar de inhoud gaan
Publicaties | Personen | Instituten | Projecten
[ meld een fout in dit record ]mandje (0): toevoegen | toon Print deze pagina

Atmospheric correction of Sentinel-3/OLCI data for mapping of suspended particulate matter and chlorophyll-a concentration in Belgian turbid coastal waters
Vanhellemont, Q.; Ruddick, K. (2021). Atmospheric correction of Sentinel-3/OLCI data for mapping of suspended particulate matter and chlorophyll-a concentration in Belgian turbid coastal waters. Remote Sens. Environ. 256: 112284. https://dx.doi.org/10.1016/j.rse.2021.112284
In: Remote Sensing of Environment. Elsevier: New York,. ISSN 0034-4257; e-ISSN 1879-0704, meer
Peer reviewed article  

Beschikbaar in  Auteurs | Datasets 

Trefwoorden
    Properties > Physical properties > Turbidity
    Validation
    Water bodies > Coastal waters
Author keywords
    Atmospheric correction, Chlorophyll-a, OLCI, ACOLITE, PANTHYR

Auteurs  Top | Datasets 
  • Vanhellemont, Q., meer
  • Ruddick, K., meer

Abstract
    The performance of different atmospheric correction algorithms for the Ocean and Land Colour Instrument (OLCI) on board of Sentinel-3 (S3) is evaluated for retrieval of water-leaving radiance reflectance, and derived parameters chlorophyll-a concentration and turbidity in turbid coastal waters in the Belgian Coastal Zone (BCZ). This is performed using in situ measurements from an autonomous pan-and-tilt hyperspectral radiometer system (PANTHYR). The PANTHYR provides validation data for any satellite band between 400 and 900 nm, with the deployment in the BCZ of particular interest due to the wide range of observed Near-InfraRed (NIR) reflectance. The Dark Spectrum Fitting (DSF) atmospheric correction algorithm is adapted for S3/OLCI processing in ACOLITE, and its performance and that of 5 other processing algorithms (L2-WFR, POLYMER, C2RCC, SeaDAS, and SeaDAS-ALT) is compared to the in situ measured reflectances. Water turbidities across the matchups in the Belgian Coastal Zone are about 20–100 FNU, and the overall performance is best for ACOLITE and L2-WFR, with the former providing lowest relative (Mean Absolute Relative Difference, MARD 7–27%) and absolute errors (Mean Average Difference, MAD -0.002, Root Mean Squared Difference, RMSD 0.01–0.016) in the bands between 442 and 681 nm. L2-WFR provides the lowest errors at longer NIR wavelengths (754–885 nm). The algorithms that assume a water reflectance model, i.e. POLYMER and C2RCC, are at present not very suitable for processing imagery over the turbid Belgian coastal waters, with especially the latter introducing problems in the 665 and 709 nm bands, and hence the chlorophyll-a and turbidity retrievals. This may be caused by their internal model and/or training dataset not being well adapted to the waters encountered in the BCZ. The 1020 nm band is used most frequently by ACOLITE/DSF for the estimation of the atmospheric path reflectance (67% of matchups), indicating its usefulness for turbid water atmospheric correction. Turbidity retrieval using a single band algorithm showed good performance for L2-WFR and ACOLITE compared to PANTHYR for e.g. the 709 nm band (MARD 15 and 17%), where their reflectances were also very close to the in situ observations (MARD 11%). For the retrieval of chlorophyll-a, all methods except C2RCC gave similar performance, due to the RedEdge band-ratio algorithm being robust to typical spectrally flat atmospheric correction errors. C2RCC does not retain the spectral relationship in the Red and RedEdge bands, and hence its chlorophyll-a concentration retrieval is not at all reliable in Belgian coastal waters. L2-WFR and ACOLITE show similar performance compared to in situ radiometry, but due to the assumption of spatially consistent aerosols, ACOLITE provides less noisy products. With the superior performance of ACOLITE in the 490–681 nm wavelength range, and smoother output products, it can be recommended for processing of S3/OLCI data in turbid waters similar to those encountered in the BCZ. The ACOLITE processor for OLCI and the in situ matchup dataset used here are made available under an open source license.

Datasets (2)
  • Vansteenwegen, D.; Vanhellemont, Q.; Flanders Marine Institute (VLIZ): Belgium; Royal Belgian Institute for Natural Sciences (RBINS): Belgium; (2022): PANTHYR hyperspectral water radiometry Blue Accelerator Platform 2019. Marine Data Archive., meer
  • Vansteenwegen, D.; Vanhellemont, Q.; Flanders Marine Institute (VLIZ): Belgium; Royal Belgian Institute for Natural Sciences (RBINS): Belgium; (2022): PANTHYR hyperspectral water radiometry Blue Accelerator Platform 2020. Marine Data Archive., meer

Alle informatie in het Integrated Marine Information System (IMIS) valt onder het VLIZ Privacy beleid Top | Auteurs | Datasets