沙漠与绿洲气象2026，Vol.20Issue(3)：1-8,8.DOI:10.12057/j.issn.2097-6801.2507.21316
大数据技术在智慧农业气象实践中的现状与展望
Current Status and Prospects of Big Data Technology for Smart Agri-Meteorological Practices
摘要
Abstract
The rapid development of big data technology has provided powerful tools for innovation in agricultural meteorological research and operations.This paper focuses on the"data-scenario-action"closed-loop framework in agrometeorological services.It elucidates the application advantages of big data technology through five representative scenarios:crop growth monitoring,yield prediction,pest and disease forecasting,agricultural disaster warning,and soil moisture monitoring.For crop growth monitoring,big data integrates terabyte-scale datasets from satellite remote sensing,UAV-based multispectral imagery,and ground IoT sensors,enabling dynamic growth analysis from leaf to field scales.In yield prediction,it enables more accurate modeling of weather-crop interactions,supporting yield prediction and risk reduction.For pest and disease forecasting,big data facilitates pattern mining and correlation analysis from massive historical and real-time data,enabling the provision of timely control strategies.Regarding meteorological disaster prediction,big data technology significantly improves spatiotemporal accuracy and reliability by integrating multi-source heterogeneous data.In soil moisture monitoring,big data-driven fusion of remote sensing and in-situ sensor data enables real-time monitoring,accurate prediction,and intelligent management.Finally,the paper highlights future directions to unlock the full potential of big data in agriculture,such as optimizing algorithms,achieving cross-scale data fusion,upgrading real-time processing architectures,and advancing agricultural system intelligence.关键词
大数据技术/农业气象/智慧农业Key words
big data technology/agricultural meteorology/smart agriculture分类
农业科技引用本文复制引用
景元书,陈嘉怡,张玉双,冉楚钰,陈继珍..大数据技术在智慧农业气象实践中的现状与展望[J].沙漠与绿洲气象,2026,20(3):1-8,8.基金项目
国家自然科学基金项目(42575208) （42575208）
教育部新农科研究与改革实践项目(2021086) （2021086）
江苏省一流品牌专业建设项目(202501002) （202501002）
