FN Archimer Export Format PT J TI Hybrid hidden Markov model for marine environment monitoring BT AF ROUSSEEUW, Kevin POISON CAILLAULT, Emilie LEFEBVRE, Alain HAMAD, Denis AS 1:1,2;2:1;3:2;4:1; FF 1:PDG-ODE-LITTORAL-LERBL;2:;3:PDG-ODE-LITTORAL-LERBL;4:; C1 ULCO/LISIC, BP 719, FR-62228 Calais, France IFREMER, Centre Manche Mer du Nord, BP 699, FR-62321 Boulogne-sur-Mer, France C2 UNIV LITTORAL COTE D'OPALE, FRANCE IFREMER, FRANCE SI BOULOGNE SE PDG-ODE-LITTORAL-LERBL IN WOS Ifremer jusqu'en 2018 copubli-france copubli-univ-france IF 2.145 TC 16 UR https://archimer.ifremer.fr/doc/00255/36643/35225.pdf LA English DT Article CR DYPHYMA I ET II IBTS INTERNATIONAL BOTTOM TRAWL SURVEY (IBTS), BO CĂ´tes De La Manche DE ;Hybrid Hidden Markov Model;marine water monitoring;Phytoplankton blooms;spectral clustering AB Phytoplankton is an important indicator of water quality assessment. To understand phytoplankton dynamics, many fixed buoys and ferry boxes were implemented, resulting in the generation of substantial data signals. Collected data are used as inputs of an effective monitoring system. The system, based on unsupervised hidden Markov model (HMM), is designed not only to detect phytoplancton blooms but also to understand their dynamics. HMM parameters are usually estimated by an iterative expectation-maximization (EM) approach. We propose to estimate HMM parameters by using spectral clustering algorithm. The monitoring system is assessed based on database signals from MAREL-Carnot station, Boulogne-sur-Mer, France. Experimental results show that the proposed system is efficient to detect environmental states such as phytoplankton productive and nonproductive periods without a priori knowledge. Furthermore, discovered states are consistent with biological interpretation. PY 2015 PD JAN SO Ieee Journal Of Selected Topics In Applied Earth Observations And Remote Sensing SN 1939-1404 PU Institute of Electrical and Electronics Engineers (IEEE) VL 8 IS 1 UT 000349550400020 BP 204 EP 213 DI 10.1109/JSTARS.2014.2341219 ID 36643 ER EF