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ORIGINAL RESEARCH article
Front. Mar. Sci.
Sec. Coastal Ocean Processes
Volume 12 - 2025 | doi: 10.3389/fmars.2025.1593418
This article is part of the Research TopicInnovative Approaches to Coastal Zone Monitoring and Geodata ManagementView all 3 articles
Economic Impacts of Multimodal Learning in Coastal Zone Monitoring and Geodata Management
Provisionally accepted
Jun Zhou1*
Lang Zhou2- 1Yuxi Normal University, Yuxi, China
- 2Yunnan Normal University, Kunming, Yunnan Province, China
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Coastal zones are economically vital regions, supporting dense populations, intensive trade, and strategic infrastructure. However, their development is increasingly threatened by environmental degradation, spatial resource conflicts, and policy fragmentation. These challenges call for analytical frameworks that can jointly capture the spatial, economic, and ecological dynamics governing coastal systems. Traditional models often struggle to address this complexity, particularly overlooking spatial heterogeneity, ecological feedback mechanisms, and stochastic environmental changes. Such limitations hinder policymakers from achieving a balance between economic growth and long-term sustainability. To address these issues, this study introduces a Coastal Adaptive Economic Dynamics Model (CAEDM), which integrates dynamic optimization, spatial externalities, and stochastic shocks to more accurately reflect the interplay between economic activities and environmental dynamics in coastal regions. Building on this foundation, we further propose the Resilient Coastal Economic Optimization Strategy (RCEOS) to optimize resource allocation, mitigate environmental degradation, and facilitate the spatial redistribution of economic activities, ensuring the resilience and adaptive capacity of coastal ecosystems. We develop CAEDM using multimodal deep learning and coupled spatiotemporal modeling, which jointly support real-time monitoring and policy simulation. Quantitative evaluations demonstrate that CAEDM achieves up to 3.5% higher accuracy and 4.2% better AUC compared to state-of-theart models on benchmark datasets including AVSD and Coastal Tourism. This research aligns with the evolving needs of coastal zone monitoring and geodata management, offering actionable insights for enhancing long-term economic resilience and environmental sustainability in coastal areas.
Keywords: Coastal Economic Dynamics, Spatial optimization, Stochastic Environmental Modeling, Sustainable resource management, Coastal Zone Resilience
Received: 14 Mar 2025; Accepted: 14 Apr 2025.
Copyright: © 2025 Zhou and Zhou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jun Zhou, Yuxi Normal University, Yuxi, China
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