DataSheet_1_An intelligent modeling framework to optimize the spatial layout of ocean moored buoy observing networks.docx

This research is motivated by the practical requirements in the sustainable deployment of ocean moored buoy observing networks. Ocean moored buoys play an important role in the global marine environment monitoring. Ocean buoy station layout planning is a typical multiple-objective spatial optimization problem that aims to reduce the spatial correlation of buoy stations and improve their spatial monitoring efficiency. In this paper, we develop a multi-objective mathematical model for allocating ocean buoy stations (MOLMofOBS) based on Tobler’s first law of geography. A spatial neighborhood model based on a Voronoi diagram is built to represent the spatial proximity of distributed buoy stations and delimit the effective monitoring region of every station. Then, a heuristic method based on a multiple-objective particles swarm optimization (MOPSO) algorithm is developed to calculate the MOLMofOBS via a dynamic inertia weight strategy. Meanwhile, a series of experiments is conducted to verify the efficiency of the proposed model and algorithms in solving single- and multiple-buoy station location problems. Finally, an interactive portal is developed in the Cyberinfrastructure environment to provide decision-making services for online real-time planning of the ocean buoy station locations. The work reported in this paper will provide spatial decision-making support for the sustainable development of ocean buoy observing networks.

本研究的开展源于海洋锚定浮标观测网络可持续部署的实际需求。海洋锚定浮标在全球海洋环境监测中发挥着至关重要的作用。海洋浮标站布局规划属于典型的多目标空间优化问题，其核心目标为降低浮标站的空间相关性，提升空间监测效率。本文基于托布勒地理学第一定律（Tobler’s first law of geography），构建了面向海洋浮标站配置的多目标数学模型（MOLMofOBS）。通过构建基于沃罗诺伊图（Voronoi diagram）的空间邻域模型，表征分布式浮标站的空间邻近性，并划定各站点的有效监测区域。随后，本文提出一种基于多目标粒子群优化（MOPSO）算法的启发式求解方法，借助动态惯性权重策略求解该MOLMofOBS模型。同时，开展了一系列实验以验证所提模型与算法在求解单浮标站、多浮标站选址问题中的有效性。最后，在数字基础设施（Cyberinfrastructure）环境中开发了一款交互式门户平台，可为海洋浮标站选址的在线实时规划提供决策支持服务。本文所述研究工作将为海洋浮标观测网络的可持续发展提供可靠的空间决策支持。