The invention relates to the technical field of
forestry protection, in particular to an intelligent pest prevention and control method for regional
forestry, which comprises the following four steps: shooting pest situation images and acquiring
environmental factor data through an intelligent measuring and reporting
station, generating a
cruise path by an unmanned aerial vehicle based on an A star
algorithm, and generating a pest density thermodynamic diagram by combining a
multispectral image and
Kriging interpolation; establishing a pest feature
template library, screening candidate types through Chebyshev distance and
cosine similarity, and identifying pest types through feature weighted voting; constructing a model based on an
entropy weight method and a matter-element extension
algorithm, fusing the environmental suitability correlation degree and a
forestry density risk value to obtain an
insect pest risk correlation degree, and performing early warning; and generating an optimal
power control instruction of the insecticidal lamp through rules and
reinforcement learning, and obtaining an optimal
pesticide spraying path of the unmanned aerial vehicle by adopting a
genetic algorithm. According to the method, full-process intelligentization of pest monitoring, recognition, early warning and prevention and control is achieved, and the actual requirement for efficient prevention and control of the forest region is met.