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Precision irrigation aiming at improving the agricultural water use efficiency is the main mode of future agricultural irrigation, with the accurate detection of crop water stress and the scientific irrigation decision being its prerequisite. For decades, fieldbased fixedpoint monitoring, onboard vehicle movement monitoring and satellite remote sensing were the information acquisition techniques for the quantitative detection of crop water stress and irrigation decisionmaking. The emergence of unmanned aerial vehicle (UAV) fundamentally solved the technical problems of satellite remote sensing caused by its low temporalspatial resolution, including instantaneous extension, spatial scale conversion, quantitative correspondence between remote sensing parameters and model parameters. At the same time, UAV remote sensing technology also solved the problems of ground monitoring methods, such as low efficiency and high cost. Research results in recent years showed that the UAV remote sensing system could obtain hightemporal resolution images of multiple plots with high throughput, making it possible to analyze the spatial variability of agrometeorological conditions, soil conditions, crop phenotypes and their mutual relationships accurately. It provided a new method for quickly sensing the spatial variability of crop water stress within a large area of farmland, which had obvious advantages and broad prospects in the application of precision irrigation. UAV remote sensing technology was successfully applied to obtain agricultural information, including fractional vegetation cover, plant height, lodging area, biomass, leaf area index and canopy temperature. However, study on quantitative indicator monitoring for crop water stress detection and irrigation decisionmaking has just started. At present, it mainly focuses on crop water stress index (CWSI), crop coefficient, canopy structural index, soil water content, PRI etc. Some of the above indicators were successfully applied to monitor the water stress status of various crops, but for most crops and indicators, further study is needed to improve the universality of the model. The technical process and key points of UAV application in precision irrigation were given. To meet the needs of highefficiency monitoring and accurate dynamic management of agricultural water at different scales, UAV remote sensing needs to be combined with satellite remote sensing and ground monitoring systems in the future. The optimization layout method and intelligent networking technology of skyintegrated agricultural water information monitoring network, fusion and assimilation technology of multisource information, comprehensive diagnosis model with multiple water stress indicators, and big data on agricultural irrigation would be the hotspots of future research.