Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

November 18, 2024


Pages


DOI

Article

An integrated analytical approach for multimodal remote sensing data in marine ecosystem damage early warning


Authors

Min Yang Affiliation:
North China Sea Marine Technical Center, Ministry of Natural Resources, Qingdao, Shandong, 266061, China.


Abstract

With the rapid economic development, the increase of human activities in coastal areas, the continuous discharge of pollutants from land-based sources into the sea, and the increase in the protection of offshore by the sea-related management departments, the judgment of early warning level of marine ecosystems is therefore of great significance. The article is based on the survey and monitoring data of Ocean A in 2022-2023 and utilizes MNDWI and Otsu to extract marine multimodal remote sensing data. Then, the environmental status of A ocean is analyzed. By constructing the early warning indicator system of A marine ecosystem based on the P-R-S model and exploring the integrated analysis method of BP ANN in the marine ecosystem, the condition of A marine ecosystem was warned, and the results were analyzed. The results show that from 2020 to 2023, the degree of sustainable development of A marine ecosystem will be in the state of “light warning”-a strong degree of sustainable development.


Keywords

Multimodal remote sensing, Marine ecosystems, Early warning, Integrated analysis, P-R-S modeling, 00A69


Citation

Yang, M. (2024). An integrated analytical approach for multimodal remote sensing data in marine ecosystem damage early warning. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-3298

Published by: Engineering Journals

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