# Advancing Towards a Marine Digital Twin Platform: Modeling the Mar Menor Coastal Lagoon Ecosystem in the South Western Mediterranean

arXiv: https://arxiv.org/abs/2409.10134 · HTML: https://mlsanity.com/paper/2409.10134/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 68 references that are in the map.
- First posted on arXiv 16 Sep 2024.

## Builds on (most cited first, 3 of 3)

- [Optuna: A Next-generation Hyperparameter Optimization Framework](https://mlsanity.com/paper/1907.10902/) (2019)
- [Supervised Multi-Regional Segmentation Machine Learning Architecture for Digital Twin Applications in Coastal Regions](https://mlsanity.com/paper/2305.14460/) (2023)
- [Modeling Digital Twin Data and Architecture: A Building Guide with FIWARE as Enabling Technology](https://mlsanity.com/paper/2309.12358/) (2023)

## Built on by (most cited first, 1 of 1)

- [Chlorophyll-a Mapping and Prediction in the Mar Menor Lagoon Using C2RCC-Processed Sentinel 2 Imagery](https://mlsanity.com/paper/2510.09736/) (2025)

## Abstract (arXiv)

Coastal marine ecosystems face mounting pressures from anthropogenic activities and climate change, necessitating advanced monitoring and modeling approaches for effective management. This paper pioneers the development of a Marine Digital Twin Platform aimed at modeling the Mar Menor Coastal Lagoon Ecosystem in the Region of Murcia. The platform leverages Artificial Intelligence to emulate complex hydrological and ecological models, facilitating the simulation of what-if scenarios to predict ecosystem responses to various stressors. We integrate diverse datasets from public sources to construct a comprehensive digital representation of the lagoon's dynamics. The platform's modular design enables real-time stakeholder engagement and informed decision-making in marine management. Our work contributes to the ongoing discourse on advancing marine science through innovative digital twin technologies.