Corrigendum: Ocean color atmospheric correction methods in view of usability for different optical water types

In the published article, there was an error in Figure 3 as published. Figure 3 shows a comparison of the reflectance results of all atmospheric correction methods for selected points marked in Figure 2. In the published version of Figures 3D, F, points 4 and 6 do not match the exact positions in Figure 2, instead the points were slightly shifted in waters where ACOLITE-DSF did not give results (NaN), the DSF spectra are accordingly not shown. In the corrected version, points 4 and 6 agree with the positions in Figure 2, DSF provides results here. The explaining text in the publication refers, among other things, to these two spectra, which are now displayed as well. All other results remain identical. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated

Ocean color atmospheric correction methods in view of usability for different optical water types

Satellite remote sensing allows large-scale global observations of aquatic ecosystems and matter fl uxes from the source through rivers and lakes to coasts, marginal seas into the open ocean. Fuzzy logic classi fi cation of optical water types (OWT) is increasingly used to optimally determine water properties and enable seamless transitions between water types. However, effective exploitation of this method requires a successful atmospheric correction (AC) over the entire spectral range, i.e., the upstream AC is suitable for each water type and always delivers classi fi able remote-sensing re fl ectances. In this study, we compare fi ve different AC methods for Sentinel-3/OLCI ocean color imagery, namely IPF, C2RCC, A4O, POLYMER, and ACOLITE-DSF (all in the 2022 current version). We evaluate their results, i.e., remote-sensing re fl ectance, in terms of spatial exploitability, individual fl agging, spectral plausibility compared to in situ data, and OWT classi fi ability with four different classi fi cation schemes. Especially the results of A4O show that it is bene fi cial if the performance spectrum of the atmospheric correction is tailored to an OWT system and vice versa. The study gives hints on how to improve AC performance, e.g., with respect to homogeneity and fl agging, but also how an OWT classi fi cation system should be designed for global deployment

Satellite water quality monitoring: Status report 2023

Prosjektleder: Therese HarveyThis report covers the 1-year status report of the project Vannovervåking med satellitt 2023 – 2024 (2025)/ Satellite water quality monitoring 2023 –2024 (2025) funded by Miljødirektoratet/the Norwegian EnvironmentalAgency (NEA). It describes the work done in Work package 1, 3, 5 andpartly 6 as well as plans for 2024. In situ data have been gathered for themost monitored Norwegian lakes (for ØKOSTOR and ØKOFERSK) and thecoastal stations included in ØKOKYST. Both Sentinel-2 and Sentinel-3data have been processed between 2016-2023. A demo viewer forexploring the data for some dedicated lakes and coastal areas has beenset up with granted access to project members. The infrastructure havebeen set up for the initial validation of 10+10 water bodies (WB) as well astests with MET and EUMETSAT for the future host of the service havebeen tested. The validation and evaluation of different algorithms of chl-aand Secchi depth data have started for the 10+10 WBs. The selection ofWB for the initial validation was based on water quality and opticalparameters to cover a wide range of water types and conditions.MiljødirektoratetpublishedVersio

Lake water quality in-situ data requirements and availability

Copernicus is the European Union’s Earth Observation (EO) and monitoring programme. This report summarises the requirements, availability and limitations of in-situ data for development of satellite-EO products relating to lake water quality across the Copernicus services. It identifies gaps in available data and provides recommendations for coordination activities that may help improve access and usefulness of in-situ data