The invention relates to a field maize canopy temperature extraction method based on unmanned aerial vehicle visible light and thermal infrared remote sensing, and belongs to the technical field of agricultural information. In order to solve the problems that existing canopy temperature-based water stress condition monitoring is time-consuming, labor-consuming and relatively high in cost, and thespatial variability of soil, crops and the like is not considered. Based on a newest unmanned aerial vehicle multi-spectral remote sensing technology, and in combination with a visible light and thermal infrared remote sensing technology, a low-cost and rapid obtaining method for a high-temporal-spatial-resolution field maize water stress condition distribution diagram is provided, so that the technical support is provided for field irrigation management, and the agricultural informatization is promoted. The method mainly comprises the six main steps of designing an unmanned aerial vehicle remote sensing data collection route; arranging a ground control point (GCP); collecting and preprocessing unmanned aerial vehicle remote sensing data; performing unmanned aerial vehicle remote sensing image splicing, geometric correction and geographic information matching; extracting the field maize coverage degree based on the unmanned aerial vehicle visible light remote sensing; and extracting afield maize canopy temperature based on an unmanned aerial vehicle thermal infrared remote sensing image.