汇聚海量数据深化应用场景开创智慧水土保持

doi:10.16843/j.sswc.2022.02.001

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摘要数字经济、智慧社会成为当今世界创新发展的新动能,智慧水土保持要为生态保护与高质量发展提供更强动力与支撑。智慧水土保持的基础是海量数据,需广泛、深度挖掘数据资源。大数据、云计算、人工智能、互联网、区块链等高新科技与水土保持管理及社会化服务的深度融合,区域土壤侵蚀长系列、多频次调查数据,为水土流失防治的科学布局、智慧决策提供支撑;长期、定位观测数据的深度开发,将为构建预测预报模型、预警预案提供支持。水土保持重点工程图斑精细化管理,流域山水林田湖草沙综合治理理论、标准、成果的深度开发,支持水土保持生态功能监测评价、生态系统质量与稳定性、可推广成功案例及其科学配置的技术措施智能化服务。生产建设项目水土保持方案、监测、监理、验收、信息化监管等海量数据开发,服务于科学精准高效跟踪检查,水土保持合规性自主预判、问题警示、整改核实等;对违反水土保持信用情形实施智能监测、警示、快速跟踪。年度水土流失动态监测数据深度开发,服务于水土保持任务完成监测、目标考评,重要生态功能区、生态敏感区、水土流失重点防治区的智能化跟踪监测、预警、评价。

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	姜德文

关键词 ：海量数据挖掘, 丰富应用场景, 大数据, 云计算, 人工智能, 智慧水土保持, 数字经济

Abstract：[Background] Digital economy and intelligent society have become new drivers of innovation and development in today world. Intelligent soil and water conservation is a trend and provides stronger impetus and support for ecological protection and high-quality development. [Methods] Here author presented 5 aspects of intelligent soil and water conservation based on own long-term working experiences and accurate understanding on this topic. [Results] 1) Intelligent soil and water conservation is based on massive data. The massive data may be just stored in the archives and on paper, even not be so reliable and cannot be processed by computer. They should be met 5 requirements of being processable in computer, systematical, reliable, no secret leakage and shareable. 2) Deep integration of high and new technologies such as big data, cloud computing, artificial intelligence, Internet and blockchain with soil and water conservation management and socialized services, long series and multi frequency survey data of regional soil erosion provide support for scientific layout and intelligent decision-making of soil erosion prevention and control. The in-depth development of long-term and positioning observation data will provide support for the construction of prediction model and early warning plan. 3) The detailed management of key soil and water conservation projects, the in-depth development of the theories, as well as standards and achievements of comprehensive management of mountains, rivers, forests, fields, lakes, grass and sand in a basin, together support the monitoring and evaluation of ecological functions of soil and water conservation, the quality and stability of ecosystem, popularized and replicated successful cases and the scientific allocation of technical measures, and provide intelligent services. 4) Massive data development of soil and water conservation plan, monitoring, supervision, approval and information supervision of production and construction projects serve scientific, accurate and efficient tracking and inspection, independent prediction of soil and water conservation compliance, problem alert, rectification and verification, etc. Intelligent monitoring, warning and rapid tracking of violations of soil and water conservation credit should be implemented. 5) The annual dynamic monitoring data of soil and water loss is deeply developed to serve the completion of monitoring and target evaluation of soil and water conservation tasks, and the intelligent tracking, monitoring, early warning and evaluation of important ecological function areas, ecologically sensitive areas and key prevention and control areas of soil and water loss.[Conclusions] We have massive data from the previous soil and water conservation work, and huge more coming from current digital time, there are a lot of work in the field of intelligent soil and water conservation.

Key words： massive data mining enriching application scenarios big data cloud computing artificial intelligence intelligent soil and water conservation digital economy

收稿日期: 2022-03-28

PACS:

S157

作者简介: 姜德文(1959-),男,博士,二级教授。主要研究方向:水土保持与生态保护。E-mail:jiangdw888@sina.com

引用本文:

姜德文. 汇聚海量数据深化应用场景开创智慧水土保持[J]. 中国水土保持科学, 2022, 20(2): 1-6.
JIANG Dewen. Gathering massive data, deepening application scenarios and creating intelligent soil and water conservation. SSWC, 2022, 20(2): 1-6.

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http://journal12.magtechjournal.com/Jweb_stbc/CN/10.16843/j.sswc.2022.02.001 或 http://journal12.magtechjournal.com/Jweb_stbc/CN/Y2022/V20/I2/1

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