A Simple Fusion Approach of Chlorophyll Images and Sea Surface Temperature Images for Improving the Detection of Moroccan Coastal Upwelling

Elabidi, Zineb; Minaoui, Khalid; Tamim, Ayoub; Laanaya, Hicham

doi:10.1109/igarss.2018.8518889

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…By considering the qualitative evaluation of our previous works provided in [20] and [21], we can affirm that the proposed methodology is more proficient for delineating the Moroccan coastal upwelling areas.…”

Section: A Qualitative Validationmentioning

confidence: 56%

“…Due to the difficulty in validating visually pixel by pixel this gigantic database, the oceanographer took the challenge to validate 92 images for two successive years (2013 and 2014) based on his knowledge on the spatiotemporal variation of the Moroccan upwelling. Corresponding to the validation notation stated in [20], "Poor" was assigned when the proper main upwelling front is not detected; in this case, the proposed methodology might overestimate by shrinking (oversegmentation) or expanding (undersegmentation) the size of the Fig. 5.…”

Section: A Qualitative Validationmentioning

confidence: 99%

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

Abidi

Minaoui

Aouni

et al. 2021

IEEE Geosci. Remote Sensing Lett.

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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.

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Section: A Qualitative Validationmentioning

confidence: 56%

Section: A Qualitative Validationmentioning

confidence: 99%

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

Abidi

Minaoui

Aouni

et al. 2021

IEEE Geosci. Remote Sensing Lett.

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show abstract

“…In addition to the prior research, the authors in [26,27] provided two distinct approaches based on an image fusion idea to detect Moroccan coastal upwelling. Indeed, they were able to identify the upwelling region from both SST and chlorophyll-a images, and they also offered a new index to evaluate their suggested approach.…”

Section: Introductionmentioning

confidence: 99%

A New Upwelling Index for the Moroccan Atlantic Coast for the Period between 1982–2021

Belmajdoub,

Minaoui,

El Aouni

et al. 2023

Remote Sensing

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Being a component of the Eastern Boundary Upwelling (EBU) ecosystem, Morocco’s Atlantic coast presents high biological production throughout the year, with seasonal variations in upwelling dynamics. This characterization reflects the inherent nature of EBU’s ecosystems. In this work, we develop a novel methodology to compute a new upwelling index based on the analysis of sea surface temperature (SST) images. Our new upwelling index is not only simple to calculate but also efficient. Indeed, it is limited only to the upwelling region, which has allowed the improvement of the quantification and analysis of the seasonal and interannual variability of the upwelling dynamics. The new proposed upwelling index is based on the application of a recent segmentation method that allows for the monitoring of upwelling dynamics using satellite observations. The proposed upwelling index is applied to a 40-year database of weekly SST images covering the period from 1982 to 2021, and the results are used to analyze seasonal and interannual variations of the upwelling in the region.

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An improved fusion method for detecting upwelling off the coast of northwest Africa from chlorophyll-a and sea surface temperature satellite images

Abidi

Minaoui

2022

Remote Sensing Letters

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A Simple Fusion Approach of Chlorophyll Images and Sea Surface Temperature Images for Improving the Detection of Moroccan Coastal Upwelling

Cited by 4 publications

References 8 publications

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

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

A New Upwelling Index for the Moroccan Atlantic Coast for the Period between 1982–2021

An improved fusion method for detecting upwelling off the coast of northwest Africa from chlorophyll-a and sea surface temperature satellite images

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