최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기대한원격탐사학회지 = Korean journal of remote sensing, v.37 no.5 pt.1, 2021년, pp.959 - 974
성태준 (울산과학기술원 도시환경공학과) , 김영준 (울산과학기술원 도시환경공학과) , 최현영 (울산과학기술원 도시환경공학과) , 임정호 (울산과학기술원 도시환경공학과)
Forel-Ule Index (FUI) is an index which classifies the colors of inland and seawater exist in nature into 21 gradesranging from indigo blue to cola brown. FUI has been analyzed in connection with the eutrophication, water quality, and light characteristics of water systems in many studies, and the p...
Aurin, D.A. and H.M. Dierssen, 2012. Advantages and limitations of ocean color remote sensing in CDOM-dominated, mineral-rich coastal and estuarine waters, Remote Sensing of Environment, 125: 181-197.
Blondeau-Patissier, D., J.F. Gower, A.G. Dekker, S.R. Phinn, and V.E. Brando, 2014. A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans, Progress in Oceanography, 123: 123-144.
Board, O.S. and N.R. Council, 2000. Clean coastal waters: understanding and reducing the effects of nutrient pollution, National Academies Press, Washington, D.C., D.C., USA.
Carlson, R.E., 1977. A trophic state index for lakes 1, Limnology and Oceanography, 22(2): 361-369.
Chen, Q., M. Huang, and X. Tang, 2020. Eutrophication assessment of seasonal urban lakes in China Yangtze River Basin using Landsat 8-derived Forel-Ule index: A six-year (2013-2018) observation, Science of the Total Environment, 745: 135392.
Chen, S., C. Hu, B.B. Barnes, R. Wanninkhof, W.-J. Cai, L. Barbero, and D. Pierrot, 2019. A machine learning approach to estimate surface ocean pCO2 from satellite measurements, Remote Sensing of Environment, 228: 203-226.
ESA (European Space Agency), 2000. Product User Guide for v5.0 Dataset, Plymouth Marine Laborat, Plymouth, DV, GB.
Forel, F. A., 1890. Une nouvelle forme de la gamme de couleur pour l'etude de l'eau des lacs, Archives des sciences physiques et naturelles/Societe de physique et d'histoire naturelle de geneve, 6: 25.
Garaba, S.P., A. Friedrichs, D. Voss, and O. Zielinski, 2015. Classifying natural waters with the Forel-Ule Colour index system: results, applications, correlations and crowdsourcing, International Journal of Environmental Research and Public Health, 12(12): 16096-16109.
Jafar-Sidik, M., D.G. Bowers, and J.W. Griffiths, 2018. Remote sensing observations of ocean colour using the traditional Forel-Ule scale, Estuarine, Coastal and Shelf Science, 215: 52-58.
Kim, H.-C., S. Son, Y.H. Kim, J.S. Khim, J. Nam, W.K. Chang, J.-H. Lee, C.-H. Lee, and J. Ryu, 2017. Remote sensing and water quality indicators in the Korean West coast: Spatio-temporal structures of MODIS-derived chlorophyll-a and total suspended solids, Marine Pollution Bulletin, 121(1-2): 425-434.
Kim, W., J.-H. Ahn, and Y.-J. Park, 2015. Correction of stray-light-driven interslot radiometric discrepancy (ISRD) present in radiometric products of geostationary ocean color imager (GOCI), IEEE Transactions on Geoscience and Remote Sensing, 53(10): 5458-5472.
Kratzer, C.R. and P.L. Brezonik, 1981. A carlson-type trophic state index for nitrogen in Florida lakes 1, JAWRA Journal of the American Water Resources Association, 17(4): 713-715.
Lanbu, Z. and Z. Baoreng, 1991. Distributions and Variations of the Transparency in the Bohai Sea, Yellow Sea and East China Sea [J], Transactions of Oceanology and Limnology, 3: 1-11.
Li, H., X. He, Y. Bai, P. Shanmugam, Y.-J. Park, J. Liu, Q. Zhu, F. Gong, D. Wang, and H. Huang, 2020. Atmospheric correction of geostationary satellite ocean color data under high solar zenith angles in open oceans, Remote Sensing of Environment, 249: 112022.
MOF (Ministry of Oceans and Fisheries), 2013. Marine Environment Standards, Sejong, Korea, p. 186.
Nie, Y., J. Guo, B. Sun, and X. Lv, 2020. An evaluation of apparent color of seawater based on the in-situ and satellite-derived Forel-Ule color scale, Estuarine, Coastal and Shelf Science, 246: 107032.
O'Reilly, J.E. and P.J. Werdell, 2019. Chlorophyll algorithms for ocean color sensors-OC4, OC5 & OC6, Remote sensing of environment, 229: 32-47.
Petus, C., J. Waterhouse, S. Lewis, M. Vacher, D. Tracey, and M. Devlin, 2019. A flood of information: Using Sentinel-3 water colour products to assure continuity in the monitoring of water quality trends in the Great Barrier Reef, Australia), Journal of environmental management, 248: 109255.
Pitarch, J., M. Bellacicco, S. Marullo, and H. J. Van Der Woerd, 2021. 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, Earth System Science Data, 13(2): 481-490.
Pitarch, J., H.J. van der Woerd, R.J. Brewin, and O. Zielinski, 2019. Optical properties of Forel-Ule water types deduced from 15 years of global satellite ocean color observations, Remote Sensing of Environment, 231: 111249.
Platt, T., 2008. Why ocean colour?: The societal benefits of ocean-colour technology, International Ocean-Colour Coordinating Group.
Ruddick, K.G., H.J. Gons, M. Rijkeboer, and G. Tilstone, 2001. Optical remote sensing of chlorophyll a in case 2 waters by use of an adaptive two-band algorithm with optimal error properties, Applied Optics, 40(21): 3575-3585.
Sathyendranath, S., R.J. Brewin, C. Brockmann, V. Brotas, B. Calton, A. Chuprin, P. Cipollini, A. B. Couto, J. Dingle, and R. Doerffer, 2019. An ocean-colour time series for use in climate studies: the experience of the ocean-colour climate change initiative (OC-CCI), Sensors, 19(19): 4285.
Siswanto, E., J. Tang, H. Yamaguchi, Y.-H. Ahn, J. Ishizaka, S. Yoo, S.-W. Kim, Y. Kiyomoto, K. Yamada, and C. Chiang, 2011. Empirical ocean-color algorithms to retrieve chlorophyll-a, total suspended matter, and colored dissolved organic matter absorption coefficient in the Yellow and East China Seas, Journal of Oceanography, 67(5): 627-650.
Son, S., Y.H. Kim, J.-I. Kwon, H.-C. Kim, and K.-S. Park, 2014. Characterization of spatial and temporal variation of suspended sediments in the Yellow and East China Seas using satellite ocean color data, GIScience & Remote Sensing, 51(2): 212-226.
Tassan, S., 1994. Local algorithms using SeaWiFS data for the retrieval of phytoplankton, pigments, suspended sediment, and yellow substance in coastal waters, Applied Optics, 33(12): 2369-2378.
Tilstone, G. H., A.A. Lotliker, P.I. Miller, P.M. Ashraf, T.S. Kumar, T. Suresh, B. Ragavan, and H.B. Menon, 2013. Assessment of MODIS-Aqua chlorophyll-a algorithms in coastal and shelf waters of the eastern Arabian Sea, Continental Shelf Research, 65: 14-26.
Ule, W., 1892. Die bestimmung der Wasserfarbe in den Seen, Kleinere Mittheilungen, Dr. A. Petermanns Mittheilungen aus Justus Perthes geographischer Anstalt: 70-71.
Van der Woerd, H.J. and M.R. Wernand, 2018. Hueangle product for low to medium spatial resolution optical satellite sensors, Remote Sensing, 10(2): 180.
Wang, S., Z. Lee, S. Shang, J. Li, B. Zhang, and G. Lin, 2019. Deriving inherent optical properties from classical water color measurements: Forel-Ule index and Secchi disk depth, Optics Express, 27(5): 7642-7655.
Wang, S., J. Li, B. Zhang, E. Spyrakos, A.N. Tyler, Q. Shen, F. Zhang, T. Kuster, M.K. Lehmann, and Y. Wu, 2018. Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index, Remote Sensing of Environment, 217: 444-460.
Wernand, M., A. Hommersom, and H.J. van der Woerd, 2013. MERIS-based ocean colour classification with the discrete Forel-Ule scale, Ocean Science, 9(3): 477-487.
Wernand, M. and H. Van der Woerd, 2010. Spectral analysis of the Forel-Ule Ocean colour comparator scale, Journal of the European Optical Society-Rapid Publications, 5: 10014S.
Woerd, H.J. and M.R. Wernand, 2015. True colour classification of natural waters with medium-spectral resolution satellites: SeaWiFS, MODIS, MERIS and OLCI, Sensors, 15(10): 25663-25680.
Wu, J., C. Chen, and S. Nukapothula, 2020. Atmospheric Correction of GOCI Using Quasi-Synchronous VIIRS Data in Highly Turbid Coastal Waters, Remote Sensing, 12(1): 89.
Yoon, Y.-J., S. Cho, S. Kim, N. Kim, S.-J. Lee, J. Ahn, E. Lee, S. Joh, and Y.-W. Lee, 2020. An Artificial Intelligence Method for the Prediction of Near-and Off-Shore Fish Catch Using Satellite and Numerical Model Data, Korean Journal of Remote Sensing, 36(1): 41-53 (in Korean with English abstract)
Zhao, W., N. Sanchez, H. Lu, and A. Li, 2018. A spatial downscaling approach for the SMAP passive surface soil moisture product using random forest regression, Journal of Hydrology, 563: 1009-1024.
Zhou, Y., D. Yu, Q. Yang, S. Pan, Y. Gai, W. Cheng, X. Liu, and S. Tang, 2021. Variations of Water Transparency and Impact Factors in the Bohai and Yellow Seas from Satellite Observations, Remote Sensing, 13(3): 514.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
오픈액세스 학술지에 출판된 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.