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

Crop Watch

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 Crop Watch 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 Crop Watch 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

Crop Watch will transform into a Big-Data-driven agricultural monitoring and early warning system.