76 citations as recorded by crossref.

1. Earth observation reveals the shifting patterns of China's lake colour driven by climate change and land cover H. Ying et al. https://doi.org/10.1016/j.jenvman.2024.122809
2. Satellites reveal hot spots of ocean changes in the early 21st century Z. Li et al. https://doi.org/10.1126/sciadv.ads0307
3. Retrieve of total suspended matter in typical lakes in China based on broad bandwidth satellite data: Random forest model with Forel-Ule Index M. Zhai et al. https://doi.org/10.3389/fenvs.2023.1132346
4. Recognition of Water Colour Anomaly by Using Hue Angle and Sentinel 2 Image Y. Zhao et al. https://doi.org/10.3390/rs12040716
5. Refined Monitoring of Water Bodies in Built-Up Areas and Analysis and Evaluation of Water Color Characteristics in Complex Urban Backgrounds B. Li et al. https://doi.org/10.1109/JSTARS.2025.3575847
6. The Forel-Ule scale revisited spectrally: preparation protocol, transmission measurements and chromaticity S. Novoa et al. https://doi.org/10.2971/jeos.2013.13057
7. WACODI: A generic algorithm to derive the intrinsic color of natural waters from digital images S. Novoa et al. https://doi.org/10.1002/lom3.10059
8. Red tide detection based on high spatial resolution broad band optical satellite data R. Liu et al. https://doi.org/10.1016/j.isprsjprs.2021.12.009
9. A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000–2018 S. Wang et al. https://doi.org/10.1038/s41597-021-00807-z
10. Biases in ocean color over a Secchi disk J. Pitarch https://doi.org/10.1364/OE.25.0A1124
11. Modelling Water Colour Characteristics in an Optically Complex Nearshore Environment in the Baltic Sea; Quantitative Interpretation of the Forel-Ule Scale and Algorithms for the Remote Estimation of Seawater Composition S. Woźniak & J. Meler https://doi.org/10.3390/rs12172852
12. Research on the Characteristic Spectral Band Determination for Water Quality Parameters Retrieval Based on Satellite Hyperspectral Data X. Xia et al. https://doi.org/10.3390/rs15235578
13. An innovation of two established methods for monitoring water colour and clarity: participatory science using the mini- and midi- secchi disks R. Brewin et al. https://doi.org/10.3389/fenvs.2025.1610130
14. Optical classification of an urbanized estuary using hyperspectral remote sensing reflectance K. Turner et al. https://doi.org/10.1364/OE.472765
15. Spatiotemporal Variability of the Lake Tana Water Quality Derived from the MODIS-Based Forel–Ule Index: The Roles of Hydrometeorological and Surface Processes N. Abegaz et al. https://doi.org/10.3390/atmos14020289
16. From green to brown: two decades of darkening coastal water in the Gulf of Riga, the Baltic Sea J. Aigars et al. https://doi.org/10.3389/fmars.2024.1369537
17. Monitoring and classification of high Arctic lakes in the Svalbard Islands using remote sensing J. Urbański https://doi.org/10.1016/j.jag.2022.102911
18. The Potential of Hue Angle Calculated Based on Multispectral Reflectance for Leaf Chlorophyll Content Estimation Q. Jiao et al. https://doi.org/10.1109/TGRS.2023.3322130
19. Monitoring Optical Variability in Complex Inland Waters Using Satellite Remote Sensing Data Y. Du et al. https://doi.org/10.3390/rs14081910
20. Remote sensing observations of ocean colour using the traditional Forel-Ule scale M. Jafar-Sidik et al. https://doi.org/10.1016/j.ecss.2018.10.002
21. An Inversion Model for Suspended Sediment Concentration Based on Hue Angle Optical Classification: A Case Study of the Coastal Waters in the Guangdong-Hong Kong-Macao Greater Bay Area J. Yang et al. https://doi.org/10.3390/s25061728
22. Comparison of PBIA and GEOBIA classification methods in classifying turbidity in reservoirs D. Facco et al. https://doi.org/10.1080/10106049.2021.1899302
23. Empirical Formulas for Estimating Backscattering and Absorption Coefficients in Complex Waters from Remote-Sensing Reflectance Spectra and Examples of Their Application S. Woźniak et al. https://doi.org/10.3390/s19184043
24. Three-Dimensional Variation in Light Quality in the Upper Water Column Revealed With a Single Parameter Z. Lee et al. https://doi.org/10.1109/TGRS.2021.3093014
25. Classifying Natural Waters with the Forel-Ule Colour Index System: Results, Applications, Correlations and Crowdsourcing S. Garaba et al. https://doi.org/10.3390/ijerph121215044
26. Optical properties of Forel-Ule water types deduced from 15 years of global satellite ocean color observations J. Pitarch et al. https://doi.org/10.1016/j.rse.2019.111249
27. Using Optical Water Types to Monitor Changes in Optically Complex Inland and Coastal Waters K. Uudeberg et al. https://doi.org/10.3390/rs11192297
28. A Simple Cloud-Native Spectral Transformation Method to Disentangle Optically Shallow and Deep Waters in Sentinel-2 Images C. Lee et al. https://doi.org/10.3390/rs14030590
29. Water quality monitoring of large reservoirs in China based on water color change from 1999 to 2021 Y. Lai et al. https://doi.org/10.1016/j.jhydrol.2024.130988
30. Long-term spatiotemporal mapping in lacustrine environment by remote sensing:Review with case study, challenges, and future directions L. Lai et al. https://doi.org/10.1016/j.watres.2024.122457
31. Dynamics and drivers of changing color of lakes of India A. Gujrati et al. https://doi.org/10.1007/s40808-025-02526-5
32. Observing the Ocean Submesoscale with Enhanced-Color GOES-ABI Visible Band Data J. Jolliff et al. https://doi.org/10.3390/s19183900
33. Review of the Forel–Ule Index based on in situ and remote sensing methods and application in water quality assessment M. Ye & Y. Sun https://doi.org/10.1007/s11356-021-18083-0
34. Retrieval of the hue angle of natural waters using HY-1C CZI data Z. Liu et al. https://doi.org/10.1080/01431161.2025.2602839
35. Biophysical Submesoscale Processes in the Wake of Hurricane Ivan: Simulations and Satellite Observations T. Smith et al. https://doi.org/10.3390/jmse7110378
36. Utilizing Eutrophication Assessment Directives From Transitional to Marine Systems in the Thames Estuary and Liverpool Bay, UK N. Greenwood et al. https://doi.org/10.3389/fmars.2019.00116
37. Detecting centennial changes in the clarity and colour of the Red and Eastern Mediterranean Seas by retracing the “Pola” expeditions J. Heath et al. https://doi.org/10.3389/fmars.2024.1358899
38. Evaluating interdependencies of lake water surface temperature and clarity K. Nitish & J. Indu https://doi.org/10.1016/j.scitotenv.2025.178695
39. 基于CIE颜色系统的东中国近海长时序水色变化研究 李. Li Minghui et al. https://doi.org/10.3788/AOS241400
40. An Optical Classification Tool for Global Lake Waters M. Eleveld et al. https://doi.org/10.3390/rs9050420
41. Assessments of trophic state in lakes and reservoirs of Wuhan using Sentinel-2 satellite data Y. Zhou et al. https://doi.org/10.1080/22797254.2021.1960201
42. Spectral Classification of the Yellow Sea and Implications for Coastal Ocean Color Remote Sensing H. Ye et al. https://doi.org/10.3390/rs8040321
43. Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index S. Wang et al. https://doi.org/10.1016/j.rse.2018.08.026
44. Estimation of Reservoir Bio-Optical Water Quality Parameters Using Smartphone Sensor Apps and Landsat ETM+: Review and Comparative Experimental Results Y. Ouma et al. https://doi.org/10.1155/2018/3490757
45. Coastal Ocean Darkening Effects via Terrigenous DOM Addition on Plankton: An Indoor Mesocosm Experiment N. Mustaffa et al. https://doi.org/10.3389/fmars.2020.547829
46. An Evaluation of Citizen Science Smartphone Apps for Inland Water Quality Assessment T. Malthus et al. https://doi.org/10.3390/rs12101578
47. An Assessment of Water Color for Inland Water in China Using a Landsat 8-Derived Forel–Ule Index and the Google Earth Engine Platform X. Chen et al. https://doi.org/10.1109/JSTARS.2021.3085411
48. True Colour Classification of Natural Waters with Medium-Spectral Resolution Satellites: SeaWiFS, MODIS, MERIS and OLCI H. Woerd & M. Wernand https://doi.org/10.3390/s151025663
49. A discussion on the estimation of apparent colour of water with the Forel-Ule index for medium-width sections of rivers with high hydrodynamic activity A. Falcão et al. https://doi.org/10.1016/j.rsase.2023.101075
50. Identification of Floating Green Tide in High-Turbidity Water from Sentinel-2 MSI Images Employing NDVI and CIE Hue Angle Thresholds L. Wang et al. https://doi.org/10.3390/jmse12091640
51. An improved Forel–Ule index method for trophic state assessments of inland waters using Landsat 8 and sentinel archives Y. Zhou et al. https://doi.org/10.1080/15481603.2021.1987003
52. Using Optical Water-Type Classification in Data-Poor Water Quality Assessment: A Case Study in the Torres Strait C. Petus et al. https://doi.org/10.3390/rs14092212
53. A Printable Device for Measuring Clarity and Colour in Lake and Nearshore Waters R. Brewin et al. https://doi.org/10.3390/s19040936
54. On the Potential Optical Signature of Convective Turbulence over the West Florida Shelf J. Jolliff et al. https://doi.org/10.3390/rs13040619
55. Effect of Reduced Anthropogenic Activities on Water Quality in Lake Vembanad, India G. Kulk et al. https://doi.org/10.3390/rs13091631
56. Spatiotemporal Dynamics of Remote-Sensed Forel–Ule Index for Inland Waters Across China During the COVID-19 Pandemic L. Xu et al. https://doi.org/10.1109/JSTARS.2023.3298108
57. Knowledge-guided mixture density network for chlorophyll-a retrieval and associated pixel-by-pixel uncertainty assessment in optically variable inland waters Y. Liu et al. https://doi.org/10.1016/j.scitotenv.2024.170843
58. Evaluating historic and modern optical techniques for monitoring phytoplankton biomass in the Atlantic Ocean R. Brewin et al. https://doi.org/10.3389/fmars.2023.1111416
59. 150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean R. Vandermeulen et al. https://doi.org/10.1016/j.rse.2020.111900
60. Can Forel–Ule Index Act as a Proxy of Water Quality in Temperate Waters? Application of Plume Mapping in Liverpool Bay, UK L. Fronkova et al. https://doi.org/10.3390/rs14102375
61. An Improved Eutrophication Assessment Algorithm of Estuaries and Coastal Waters in Liaodong Bay M. Li et al. https://doi.org/10.3390/rs13193867
62. A new method for accurate inversion of Forel-Ule index using MODIS images - revealing the water color evolution in China's large lakes and reservoirs over the past two decades K. Xia et al. https://doi.org/10.1016/j.watres.2024.121560
63. Citizens and satellites: Assessment of phytoplankton dynamics in a NW Mediterranean aquaculture zone J. Busch et al. https://doi.org/10.1016/j.jag.2015.11.017
64. Forel-Ule index extraction and spatiotemporal variation from MODIS imagery in the Bohai Sea of China L. Wang et al. https://doi.org/10.1364/OE.487312
65. MODIS observations of water color of the largest 10 lakes in China between 2000 and 2012 J. Li et al. https://doi.org/10.1080/17538947.2016.1139637
66. EyeOnWater Raspberry Pi: a do-it-yourself maker sensor system project to measure and classify natural water colour based on the Forel–Ule scale N. Rüssmeier et al. https://doi.org/10.5194/jsss-14-203-2025
67. An evaluation of apparent color of seawater based on the in-situ and satellite-derived Forel-Ule color scale Y. Nie et al. https://doi.org/10.1016/j.ecss.2020.107032
68. Global maps of Forel–Ule index, hue angle and Secchi disk depth derived from 21 years of monthly ESA Ocean Colour Climate Change Initiative data J. Pitarch et al. https://doi.org/10.5194/essd-13-481-2021
69. A three-decade lake dataset on the Mongolian plateau tracking water area and quality dynamics (1990–2020) J. Guo et al. https://doi.org/10.1038/s41597-025-06059-5
70. Evaluation of trophic state for inland waters through combining Forel-Ule Index and inherent optical properties Y. Liu et al. https://doi.org/10.1016/j.scitotenv.2022.153316
71. Accuracy and Reproducibility of Above-Water Radiometry With Calibrated Smartphone Cameras Using RAW Data O. Burggraaff et al. https://doi.org/10.3389/frsen.2022.940096
72. Variations of Remote-Sensed Forel-Ule Index in the Bohai and Yellow Seas during 1997–2019 B. Zhang et al. https://doi.org/10.3390/rs15143487
73. Calibration and validation of the HydroColor and Citclops smartphone applications for water quality monitoring P. Mahama & S. Salama https://doi.org/10.1016/j.heliyon.2024.e30100
74. Reduced sediment load and vegetation restoration leading to clearer water color in the Yellow River: Evidence from 38 years of Landsat observations K. Xia et al. https://doi.org/10.1016/j.jag.2025.104369
75. Remote sensing assessment of trophic status based on chromaticity angle in Lake Daihai W. Fang et al. https://doi.org/10.18307/2022.0409
76. Methods for detecting green tide in the Yellow Sea using Google Earth Engine platform Y. Shang et al. https://doi.org/10.1016/j.rsma.2024.103666