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作 者:王林龙 张会华 刘洋[1,3] 沙浩辰 乐林暄 于红妍 赵宝伟 冯峻极 Wang Linlong;Zhang Huihua;Liu Yang;Sha Haochen;Le Linxuan;Yu Hongyan;Zhao Baowei;Feng Junji(Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,China;Research Institute of Forestry Policy and Information,Chinese Academy of Forestry,Beijing 100091,China;Key Laboratory of Forestry Remote Sensing and Information Technology,National Forestry and Grassland Administration,Beijing 100091,China;The Information Center of National Forestry and Grassland Administration,Beijing 100714,China;Qinghai Service and Support Center,Qilian Mountain National Park,Xining 810099,Qinghai,China)
机构地区:[1]中国林业科学研究院资源信息研究所,北京100091 [2]中国林业科学研究院林业科技信息研究所,北京100091 [3]国家林业和草原局林业遥感与信息技术重点实验室,北京100091 [4]国家林业和草原局信息中心,北京100714 [5]祁连山国家公园青海服务保障中心,西宁810099
出 处:《林草政策研究》2024年第3期11-21,共11页Journal of forestry and grassland policy
基 金:“十四五”国家重点研发计划项目“基于网格化数据的大尺度生态质量和服务评估与生态安全格局辨识预警技术”(2023YFF1303701)。
摘 要:在实现“双碳”目标背景下,森林碳汇监测技术成为研究热点。文中总结了国内外森林碳汇监测体系建设、监测方法及技术应用方面的现状,并在此基础上从技术创新层面及政策支持层面提出进一步推动森林碳汇监测技术快速发展的相关建议:(1)构建森林碳汇云计算平台,形成生成式预训练大模型,开发多模态数据智能挖掘算法,搭建森林碳汇智能监测数字孪生平台;(2)加强政策支持与法规建设,推动跨部门协同与国际合作,强化监测成果的应用与转化的政策支持方向。In the context of China taking efforts to achieve“dual carbon”goals,the forest sink monitoring technology has emerged as a research hotspot.This paper summarizes the current status of forest sink monitoring framework setup,monitoring methodology,and technological applications at home and abroad.Based on this,relevant suggestions are proposed on how to facilitate the fast development of forest sink monitoring technologies through technology innovation and policy support,including:(1)establishing a forest sink cloud computing platform to form the generative pre-trained large models and develop the multi-modal data intelligent mining algorithms so as to construct a digital twin platform for the intelligent monitoring of forest sink;(2)strengthening policy supports and the regulatory framework to promote cross-sector collaboration and international cooperation,and enhancing the application and transformation of monitoring results.
分 类 号:S757[农业科学—森林经理学]
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