41 citations as recorded by crossref.

1. Validation of MERIS spectral inversion processors using reflectance, IOP and water quality measurements in boreal lakes K. Kallio et al. https://doi.org/10.1016/j.rse.2014.06.016
2. Testing the performance of empirical remote sensing algorithms in the Baltic Sea waters with modelled and in situ reflectance data M. Ligi et al. https://doi.org/10.1016/j.oceano.2016.08.002
3. Partition of Marine Environment Dynamics According to Remote Sensing Reflectance and Relations of Dynamics to Physical Factors T. Suominen et al. https://doi.org/10.3390/rs13112104
4. Water quality near Estonian harbours in the Baltic Sea as observed from entire MERIS full resolution archive L. Sipelgas et al. https://doi.org/10.1016/j.marpolbul.2017.09.058
5. A Review of Protocols for Fiducial Reference Measurements of Water-Leaving Radiance for Validation of Satellite Remote-Sensing Data over Water K. Ruddick et al. https://doi.org/10.3390/rs11192198
6. Using bio-optical parameters as a tool for detecting changes in the phytoplankton community (SW Portugal) P. Goela et al. https://doi.org/10.1016/j.ecss.2015.07.037
7. Integrating mooring and ship-based data for improved validation of OLCI chlorophyll-a products in the Baltic Sea S. Kratzer & M. Plowey https://doi.org/10.1016/j.jag.2020.102212
8. Applying MERIS time series and dynamic time warping for delineating areas with similar temporal behaviour in the northern Baltic Sea T. Suominen https://doi.org/10.1016/j.ecolind.2018.08.023
9. Robust remote sensing algorithms to derive the diffuse attenuation coefficient for lakes and coastal waters K. Alikas et al. https://doi.org/10.1002/lom3.10033
10. River bulge evolution and dynamics in a non-tidal sea – Daugava River plume in the Gulf of Riga, Baltic Sea E. Soosaar et al. https://doi.org/10.5194/os-12-417-2016
11. Synergy of Satellite, In Situ and Modelled Data for Addressing the Scarcity of Water Quality Information for Eutrophication Assessment and Monitoring of Swedish Coastal Waters S. Kratzer et al. https://doi.org/10.3390/rs11172051
12. A Validation of OLCI Sentinel-3 Water Products in the Baltic Sea and an Evaluation of the Effect of System Vicarious Calibration (SVC) on the Level-2 Water Products S. O’Kane et al. https://doi.org/10.3390/rs16213932
13. MOD2SEA: A Coupled Atmosphere-Hydro-Optical Model for the Retrieval of Chlorophyll-a from Remote Sensing Observations in Complex Turbid Waters B. Arabi et al. https://doi.org/10.3390/rs8090722
14. Assessment of trophic state and water quality of coastal-inland lakes based on Fuzzy Inference System A. Kulshreshtha & P. Shanmugam https://doi.org/10.1016/j.jglr.2018.07.015
15. Summer Distribution of Total Suspended Matter Across the Baltic Sea D. Kyryliuk & S. Kratzer https://doi.org/10.3389/fmars.2018.00504
16. Which ocean colour algorithm for MERIS in North West European waters? G. Tilstone et al. https://doi.org/10.1016/j.rse.2016.11.012
17. Spectral features of ocean colour radiometric products in the presence of cyanobacteria blooms in the Baltic Sea I. Cazzaniga et al. https://doi.org/10.1016/j.rse.2023.113464
18. On the equivalence of near-surface methods to determine the water-leaving radiance G. Zibordi & M. Talone https://doi.org/10.1364/OE.28.003200
19. Radiometric validation of atmospheric correction for MERIS in the Baltic Sea based on continuous observations from ships and AERONET-OC P. Qin et al. https://doi.org/10.1016/j.rse.2017.08.024
20. Consistency between Satellite Ocean Colour Products under High Coloured Dissolved Organic Matter Absorption in the Baltic Sea G. Tilstone et al. https://doi.org/10.3390/rs14010089
21. Evaluation of Sentinel-3A OLCI Products Derived Using the Case-2 Regional CoastColour Processor over the Baltic Sea D. Kyryliuk & S. Kratzer https://doi.org/10.3390/s19163609
22. The Coastal Surveillance Through Observation of Ocean Color (COASTℓOOC) dataset P. Massicotte et al. https://doi.org/10.5194/essd-15-3529-2023
23. Applicability of Earth Observation chlorophyll-a data in assessment of water status via MERIS — With implications for the use of OLCI sensors J. Attila et al. https://doi.org/10.1016/j.rse.2018.02.043
24. The impact of sea bottom effects on the retrieval of water constituent concentrations from MERIS and OLCI images in shallow tidal waters supported by radiative transfer modeling B. Arabi et al. https://doi.org/10.1016/j.rse.2019.111596
25. Suitability of different in-water algorithms for eutrophic and absorbing waters applied to Sentinel-2 MSI and Sentinel-3 OLCI data A. Ansper-Toomsalu et al. https://doi.org/10.3389/frsen.2024.1423332
26. Long-term water quality assessment in coastal and inland waters: An ensemble machine-learning approach using satellite data M. Karthick et al. https://doi.org/10.1016/j.marpolbul.2024.117036
27. Satellite-based water quality monitoring for improved spatial and temporal retrieval of chlorophyll-a in coastal waters E. Harvey et al. https://doi.org/10.1016/j.rse.2014.11.017
28. Machine Learning Regression Approaches for Colored Dissolved Organic Matter (CDOM) Retrieval with S2-MSI and S3-OLCI Simulated Data A. Ruescas et al. https://doi.org/10.3390/rs10050786
29. Temporal analysis of remotely sensed turbidity in a coastal archipelago T. Suominen & H. Tolvanen https://doi.org/10.1016/j.jag.2016.01.012
30. Gap identification in coastal eutrophication research – Scoping review for the Baltic system case G. Vigouroux & G. Destouni https://doi.org/10.1016/j.scitotenv.2022.156240
31. Using MERIS data to assess the spatial and temporal variability of phytoplankton in coastal areas J. Beltrán-Abaunza et al. https://doi.org/10.1080/01431161.2016.1249307
32. International Intercomparison of In Situ Chlorophyll-a Measurements for Data Quality Assurance of the Swedish Monitoring Program S. Kratzer et al. https://doi.org/10.3389/frsen.2022.866712
33. Retrieval of suspended particulate matter from turbidity – model development, validation, and application to MERIS data over the Baltic Sea E. Kari et al. https://doi.org/10.1080/01431161.2016.1230289
34. Satellite-based water quality monitoring in Lake Vänern, Sweden P. Philipson et al. https://doi.org/10.1080/01431161.2016.1204480
35. A novel earth observation based ecological indicator for cyanobacterial blooms S. Anttila et al. https://doi.org/10.1016/j.jag.2017.09.007
36. Assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the Baltic Sea based on Sentinel-3 OLCI L. González Vilas et al. https://doi.org/10.3389/fmars.2023.1256990
37. Inherent Optical Properties of the Baltic Sea in Comparison to Other Seas and Oceans S. Kratzer & G. Moore https://doi.org/10.3390/rs10030418
38. Water Colour Analysis of Lake Kummerow Using Time Series of Remote Sensing and In Situ Data K. Dörnhöfer et al. https://doi.org/10.1007/s41064-018-0046-3
39. New simple statistical formulas for estimating surface concentrations of suspended particulate matter (SPM) and particulate organic carbon (POC) from remote-sensing reflectance in the southern Baltic Sea S. Woźniak et al. https://doi.org/10.1016/j.oceano.2016.03.002
40. The OLCI Neural Network Swarm (ONNS): A Bio-Geo-Optical Algorithm for Open Ocean and Coastal Waters M. Hieronymi et al. https://doi.org/10.3389/fmars.2017.00140
41. Earth Observation-Based Cyanobacterial Bloom Index Testing for Ecological Status Assessment in the Open, Coastal and Transitional Waters of the Baltic and Black Seas D. Vaičiūtė et al. https://doi.org/10.3390/rs16040696