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5 results on '"Ayoub Tamim"'

1. An Efficient Detection of Moroccan Coastal Upwelling Based on Fusion of Chlorophyll-a and Sea Surface Temperature Images With a New Validation Index

Author

Ayoub Tamim, Anass El Aouni, Zineb El Abidi, Khalid Minaoui, Hicham Laanaya, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal]-Centre National de la Recherche Scientifique et Technologique (CNRST), Mathematics and computing applied to oceanic and atmospheric flows (AIRSEA), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Grenoble Alpes (UGA)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Higher institute of Marine Fisheries, and Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST)

Subjects
Chlorophyll a, Index (economics), [PHYS.MPHY]Physics [physics]/Mathematical Physics [math-ph], [MATH.MATH-DS]Mathematics [math]/Dynamical Systems [math.DS], 0211 other engineering and technologies, 02 engineering and technology, image fusion, chemistry.chemical_compound, [PHYS.MECA.MEFL]Physics [physics]/Mechanics [physics]/Fluid mechanics [physics.class-ph], 14. Life underwater, Electrical and Electronic Engineering, 021101 geological & geomatics engineering, Remote sensing, Fusion, Image fusion, Front (oceanography), sea-surface temperature (SST), Geotechnical Engineering and Engineering Geology, main Moroccan upwelling front, Sea surface temperature, chemistry, Chlorophyll-a, [NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD], Upwelling, Satellite, validation index, Geology
Abstract

International audience; This research deals with the problem of identifying and extracting effectively the main Moroccan upwelling front. The proposed methodology, based on the image-fusion concept, comes to benefit from the information available in both sea-surface temperature (SST) and chlorophyll-a satellite images. Moreover, a new validation index is proposed by computing a simple gradient along the extracted upwelling limit. The developed procedure is applied over a database of 366 SST and 366 chlorophyll-a images from 2007 to 2014, covering the Moroccan Atlantic coast. The final results are validated qualitatively by an oceanographer and quantitatively by our innovative index. The findings of validation demonstrate the performance of our fusion approach.

Published
2021
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2. Automatic detection of Moroccan coastal upwelling zones using sea surface temperature images

Author

Hussein Yahia, Khalid Minaoui, Ayoub Tamim, Salma El Fellah, Khalid Daoudi, Mohamed El Ansari, Driss Aboutajdine, Abderrahman Atillah, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), Université Ibn Zohr [Agadir], Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), and Université Mohammed V de Rabat [Agdal] (UM5)

Subjects
010504 meteorology & atmospheric sciences, 0211 other engineering and technologies, 02 engineering and technology, 01 natural sciences, Fuzzy logic, Sea surface temperature images, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Cluster (physics), Segmentation, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Cluster validity indices, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Upwelling, business.industry, Fuzzy c-means clustering, k-means clustering, Pattern recognition, Filter (signal processing), Region-growing algorithm, Sea surface temperature, General Earth and Planetary Sciences, Satellite, Artificial intelligence, business, Geology
Abstract

International audience; An efficient unsupervised method is developed for automatic segmentation of the area covered by upwelling waters in the coastal ocean of Morocco using the Sea Surface Temperature (SST) satellite images. The proposed approach first uses the two popular unsupervised clustering techniques, k-means and fuzzy c-means (FCM), to provide different possible classifications to each SST image. Then several cluster validity indices are combined in order to determine the optimal number of clusters, followed by a cluster fusion scheme, which merges consecutive clusters to produce a first segmentation of upwelling area. The region-growing algorithm is then used to filter noisy residuals and to extract the final upwelling region. The performance of our algorithm is compared to a popular algorithm used to detect upwelling regions and is validated by an oceanographer over a database of 92 SST images covering each week of the years 2006 and 2007. The results show that our proposed method outperforms the latter algorithm, in terms of segmentation accuracy and computational efficiency.

Published
2018
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3. Detection of Moroccan coastal upwelling in SST images using the Expectation-Maximization

Author

Driss Aboutajdine, Khalid Daoudi, Khalid Minaoui, Ayoub Tamim, Abderrahman Atillah, LRIT, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), and This work is funded by the French-Moroccan research pro- gram Volubilis (MA/11/256) and the project n◦MPI 12/2010.

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Upwelling, Meteorology, Dunn index, Davies-Bouldin index, Area opening, Image segmentation, Expectation-Maximisation, Sea surface temperature, Geography, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Robustness (computer science), Expectation–maximization algorithm, Sea Surface Temperature, Segmentation, Satellite, Submarine pipeline, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment
Abstract

International audience; This paper proposes an unsupervised algorithm for automatic detection and segmentation of upwelling region in Moroccan Atlantic coast using the Sea Surface Temperature (SST) satellite images. This has been done by exploring the Expectation-Maximization algorithm. The good number of clus- ters that best reproduces the shape of upwelling areas is selected by using the two popular Davies-Bouldin and Dunn indices. Area opening technique is developed that is used to remove and discarded the residuals noise in offshore waters not belonging to the upwelling region. The complete system has been validated by an oceanographer using a database of 30 SST images of the year 2007, demonstrating its capability and robustness for precise detection of Moroccan coastal upwelling.

Published
2015
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4. An Efficient Tool for Automatic Delimitation of Moroccan Coastal Upwelling Using SST Images

Author

Ayoub Tamim, Abderrahman Atillah, Hussein Yahia, Khalid Minaoui, Khalid Daoudi, Driss Aboutajdine, LRIT, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), LRIT Associated Unit to the CNRST-URAC n◦ 29, Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), Université Mohammed V de Rabat [Agdal] (UM5), and CORDI-S grant

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, unsu-pervised classification, —Sea surface temperature image, Image segmentation, Region-growing algorithm, Geotechnical Engineering and Engineering Geology, Otsu's method, symbols.namesake, Sea surface temperature, upwelling, Oceanography, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Climatology, Moroccan atlantique coast, symbols, Upwelling, Satellite, Segmentation, Submarine pipeline, Electrical and Electronic Engineering, Cluster analysis, Geology
Abstract

International audience; An unsupervised classification method is developed for the coarse segmentation of Moroccan coastal upwelling using the Sea Surface Temperature (SST) satellite images. The algorithm is started with the generation of c-partitioned labeled image using Otsu's method for the purpose of finding regions of homogenous temperatures. Then two well-known validity indices are used to select the c-partition which best reproduce the shape of upwelling area. A region-growing algorithm is developed that is used to remove the noisy structures in the offshore waters not belonging to the upwelling area. The algorithm is used to provide a seasonal variability of upwelling activity in the southern Moroccan Atlantic coast using 70 SST images of the years 2007 and 2008. The performance of the proposed methodology has been validated by an oceanographer, showing its effectiveness for automatic delimitation of Moroccan upwelling region.

Published
2014

5. A simple tool for automatic extraction of Moroccan coastal upwelling from Sea Surface Temperature images

Author

Ayoub Tamim, Hussein Yahia, Driss Aboutajdine, Abderrahman Atillah, Khalid Daoudi, Khalid Minaoui, Mohammed Faouzi Smiej, LRIT, Laboratoire de Recherche Informatique et Télécommunications (LRIT), Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST)-Université Mohammed V de Rabat [Agdal] (UM5)-Centre National de la Recherche Scientifique et Technologique (CNRST), LRIT Associated Unit to the CNRST-URAC n◦ 29, Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Centre Royal de Télédétection Spatiale (CRTS), Laboratoire de Recherche en Informatique et Télécommunications [Rabat] (GSCM-LRIT), Université Mohammed V de Rabat [Agdal] (UM5), Utilisation scientifique des images du satellites MSG acquises en temps réel (MSG-ATR), Centre National de la Recherche Scientifique (CNRS), Centre Royal de Télédétection Spatiale, IEEE, and IEEE Morocco Section

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation, Sea surface temperature, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Advanced very-high-resolution radiometer, Computer science, Climatology, Upwelling, Extraction (military), Satellite, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; This work aims at automatically identify and ex- tract the region covered by the upwelling waters in the costal ocean of Morocco using the well known region-growing segmen- tation algorithm. The later consists in coarse segmentation of upwelling area which characterized by cold and usually nutrient- rich water near the coast. The complete system has been validated by an oceanographer over a database of 30 Sea Surface Tem- perature (SST) satellite images of the year 2007 obtained from Advanced Very High Resolution Radiometer (AVHRR) sensor onboard NOAA-18 satellite serie, demonstrating its capability and effectiveness to reproduce the shape of upwelling area.

Published
2014
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