Environmental data are measured and collected by simple monitoring devices installed in agricultural fields. These data are very important not only for understanding and predicting factors such as the growth of crops and the occurrence of pests and diseases, but also for optimizing agricultural production processes such as planting, irrigation, fertilization, pest control, and harvesting. However, the amount of data stored in agricultural information databases is rapidly increasing owing to an increase in the number of monitoring devices and sensors installed in such devices. To properly detect characteristic values from such a vast amount of data, it is necessary to develop new numerical technologies and methods. We developed a simple field monitoring system to establish field observations, production optimization, and information sharing between farmers. We also developed and applied a change point analysis program based on the singular spectrum transformation to conduct change point analyses of the field environmental data measured by the monitoring devices. The calculated change point values were then verified through a comparison with farm data recorded by a corporative farmer in the feasibility study.