| 王呈珊1 徐波1 赵天启2.长期定位观测数据整合与价值挖掘策略思考[J].中国科技资源导刊,2026,(1):11~19 |
| 长期定位观测数据整合与价值挖掘策略思考 |
| Strategy Study on the Integration and Value Mining of Long-Term Positioning Observation Data |
| 投稿时间：2025-10-22 |
| DOI： |
| 中文关键词: 科学数据;野外观测;长期定位;数据挖掘 |
| 英文关键词: scientific data, field observation, long-term positioning, data mining |
| 基金项目: |
| 作者 | 单位 | | 王呈珊1 徐波1 赵天启2 | (1. 国家科技基础条件平台中心，北京 100862
2. 水利部牧区水利科学研究所，内蒙古呼和浩特 010013) |
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| 摘要点击次数: 20 |
| 全文下载次数: 10 |
| 中文摘要: |
| 长期定位观测数据是理解地球系统动态与支撑国家生态安全战略的核心科学资产，具有连续性、定位性和多源异构特征。我国已建立生态系统研究网络和北斗系统等观测体系，但仍面临共享机制不健全、标准不统一、算力不足等挑战。系统梳理国内外长期观测网络的建设进展与应用现状，通过多模态人工智能、模型—数据同化和知识图谱等方法，分析生态、水利及社会科学等领域的数据挖掘路径与案例，提出构建统一标准体系、推动云边协同计算、发展数字孪生平台等建议，以促进数据在碳中和、生物多样性治理和灾害预警等重大战略中的深度应用与科学决策支持。 |
| 英文摘要: |
| Long-term positioning observation data represents a core scientific asset for understanding Earth system dynamics and supporting national ecological security strategies, characterized by continuity, positioning accuracy, and multi-source heterogeneity. China has established observation systems such as the Ecosystem Research Network and the BeiDou System, yet still faces challenges including inadequate sharing mechanisms, lack of standardization, and insufficient computational power in data integration and value mining. This paper systematically reviews the development and application status of long-term observation networks both domestically and internationally. Using methods such as multimodal artificial intelligence, model-data assimilation, and knowledge graphs, it analyzes data mining approaches and case studies in fields including ecology, water resources, and social sciences. The study proposes recommendations such as establishing a unified standard system, promoting cloud-edge collaborative computing, and developing digital twin platforms, to facilitate the in-depth application of data in major strategies like carbon neutrality, biodiversity governance, and disaster early warning, thereby supporting scientific decision-making. |
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