农情信息是世界粮农组织、各国政府、粮食贸易企业以及农场管理迫切需要掌握的信息。大数据时代的农情监测与预警正在由模型驱动向数据驱动转变，大数据正逐渐成为监测与预警的核心驱动力。伴随着农情监测与预警大数据的爆炸式增长，大数据与云计算技术的发展为农情监测与预警提供了全新的技术手段。2013年以来，全球农情遥感速报系统（CropWatch）已逐步引入聚类分析、时间序列分析、关联分析、时空变化异常诊断等大数据分析方法，并应用于业务化运行的农情监测与预警中。大数据技术提升了CropWatch的数据挖掘能力，对CropWatch农情监测与预警时空尺度的拓展以及农情监测内容的精细化起到推动作用，促进了面向需求的CropWatch农情信息与预警精准云服务的发展，促成了大数据时代CropWatch农情监测与预警技术体系的升级。未来，大数据时代的农情监测与预警将逐渐向全自动化监测、实时化精准农业管理与智能化信息服务方向发展；通过众源采集技术高效低廉的获取农情观测大数据将成为未来的发展趋势；大数据技术跨领域数据挖掘的能力，使得丰富多元化的跨界信息服务将成为大数据时代农情监测与预警的主流发展方向。大数据时代的CropWatch正在向基于大数据的农情监测与预警系统全速迈进。

Agricultural information is essential for the World Food Organization, governments, food traders, and management of farms. By providing a powerful new solution, the Big Data era transforms agricultural monitoring and early warning from being model-driven to datadriven. Along with their rapid growth, Big Data and cloud computing technologies provide an innovative means for agricultural monitoring and early warning. Since 2013, CropWatch, a remote-sensing-based global agricultural monitoring system, has gradually introduced various techniques that deal with Big Data, such as cluster analysis, time series analysis, correlation analysis, and spatial and temporal abnormal pattern analysis, into the operational system. Big Data technologies have successfully enhanced the data mining capability of CropWatch and expanded the spatial and temporal coverage of agricultural monitoring and early warning. Big Data has also had a catalytic role in promoting the service-oriented agricultural information cloud service. Big Data has also become an important driving force in upgrading the principles of the CropWatch agricultural monitoring and early warning system. In the future, with the help of Big Data, agricultural monitoring and early warning systems are expected to move toward fully automated monitoring, real-time management, and precise agriculture information service direction. Volunteered geographic information in the Big Data era provides an efficient technique for acquiring Big Data for agricultural monitoring and early warning. Based on the capacity of cross-cutting data mining technology, the diversification of crop-border information services will become the mainstream direction of agricultural information services in the Big Data era. With the use of Big Data technologies, CropWatch will transform into a Big-Data-driven agricultural monitoring and early warning system.