Bursaphelenchus xylophilus infection early-stage pine tree identification method

The invention provides a pine wood nematode disease-infected early-stage pine tree identification method, which comprises the following steps of S1, shooting remote sensing images of pine tree samples in different time periods by utilizing a spectrum camera, and processing the spectrum images to obtain a spectrum curve of each pine tree; s2, measuring wave band characteristics of the spectrum curve by using a first-order derivative, and screening out three characteristic wave bands lambda 1, lambda 2 and lambda 3 sensitive to the pine wood nematode disease; s3, calculating a bursaphelenchus xylophilus vegetation decline disease index (PWDERI) according to the following formula according to the spectral reflectivity value of the characteristic wave band; and S4, establishing a decision tree analysis model for early-stage pine wood nematode disease monitoring by combining ENVI with a pine wood nematode disease vegetation decline disease index PWDERI, and discriminating pine tree samples. The method is simple in