The invention relates to the technical field of image or
video recognition or understanding, and discloses an
areca yellows early warning method based on regular economic forest multi-dimensional symptom analysis, in the method, the unique morphology of
areca and various morphological changes which are invisible under trees but visible in
remote sensing during the period that
areca suffers from yellows are fully utilized, and the areca yellows early warning effect is achieved. And the multiple symptoms are combined to form a multi-symptom matching degree, so that the misrecognition problem can be eliminated in an auxiliary manner when specific symptoms exist. When the specific symptoms do not exist, whether the
disease of the current areca-nut forest belongs to the infectious
disease or not is indirectly judged according to the distribution characteristics of the multi-symptom matching degree in time and space by utilizing the distribution characteristics and the
disease course development rule when the areca-nut is cultivated as an economic arbor, and if yes, the disease of the current areca-nut forest belongs to the infectious disease; and considering that the areca yellows occupy a large proportion in the areca infectious diseases, the
pathogen detection cannot be infeasible due to entrainment of a large number of irrelevant
diseased plant samples when the
pathogen detection is carried out at the moment. The above points are combined to realize early warning of areca yellows.