{"title":"Profile Data Reconstruction for Deep Chl$a$ Maxima in Mediterranean Sea via Improved-MLP Networks","authors":"Yongjun Yu;Wanchuan Kan;He Gao;Jie Yang;Baoxiang Huang","doi":"10.1109/JSTARS.2024.3468330","DOIUrl":null,"url":null,"abstract":"Deep chlorophyll maximum (DCM) is a common oceanographic phenomenon characterized by a significant peak in chlorophyll concentration at a specific depth below the ocean surface. DCM formation is closely related to factors, such as light availability, nutrient distribution, and ocean circulation, making it an important indicator for studying marine ecosystems and their changes. This study aims to estimate subsurface chlorophyll concentrations in the Mediterranean region using an improved multilayer perceptron model, bridging the gap between sparse observation data and dense sea surface data. We utilize Biogeochemical Argo and satellite data, including longitude, latitude, sea surface temperature, surface chlorophyll concentration, and month, as inputs to the model to estimate subsurface chlorophyll concentrations from 1 to 300 m depth. Through fitting and analyzing chlorophyll concentration data in the Mediterranean region, we explore DCM characteristics and their variations across different regions and seasons. The results indicate that the IMLP model performs excellently in estimating subsurface chlorophyll concentrations and effectively captures DCM features in various regions and seasons. By comparing the model estimations with observation data, we reveal patterns in DCM characteristics in the Mediterranean region, providing valuable data support for further research into marine ecosystems.","PeriodicalId":13116,"journal":{"name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","volume":null,"pages":null},"PeriodicalIF":4.7000,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10700938","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10700938/","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Deep chlorophyll maximum (DCM) is a common oceanographic phenomenon characterized by a significant peak in chlorophyll concentration at a specific depth below the ocean surface. DCM formation is closely related to factors, such as light availability, nutrient distribution, and ocean circulation, making it an important indicator for studying marine ecosystems and their changes. This study aims to estimate subsurface chlorophyll concentrations in the Mediterranean region using an improved multilayer perceptron model, bridging the gap between sparse observation data and dense sea surface data. We utilize Biogeochemical Argo and satellite data, including longitude, latitude, sea surface temperature, surface chlorophyll concentration, and month, as inputs to the model to estimate subsurface chlorophyll concentrations from 1 to 300 m depth. Through fitting and analyzing chlorophyll concentration data in the Mediterranean region, we explore DCM characteristics and their variations across different regions and seasons. The results indicate that the IMLP model performs excellently in estimating subsurface chlorophyll concentrations and effectively captures DCM features in various regions and seasons. By comparing the model estimations with observation data, we reveal patterns in DCM characteristics in the Mediterranean region, providing valuable data support for further research into marine ecosystems.
期刊介绍:
The IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing addresses the growing field of applications in Earth observations and remote sensing, and also provides a venue for the rapidly expanding special issues that are being sponsored by the IEEE Geosciences and Remote Sensing Society. The journal draws upon the experience of the highly successful “IEEE Transactions on Geoscience and Remote Sensing” and provide a complementary medium for the wide range of topics in applied earth observations. The ‘Applications’ areas encompasses the societal benefit areas of the Global Earth Observations Systems of Systems (GEOSS) program. Through deliberations over two years, ministers from 50 countries agreed to identify nine areas where Earth observation could positively impact the quality of life and health of their respective countries. Some of these are areas not traditionally addressed in the IEEE context. These include biodiversity, health and climate. Yet it is the skill sets of IEEE members, in areas such as observations, communications, computers, signal processing, standards and ocean engineering, that form the technical underpinnings of GEOSS. Thus, the Journal attracts a broad range of interests that serves both present members in new ways and expands the IEEE visibility into new areas.