A Novel Spatial-Spectral Random Forest Algorithm for Pine WILT Monitoring

Pine wilt disease is one of the most dangerous forest diseases. Because of its strong infectivity and harm, it is very important to find out and stop it in time. In this paper, a novel spatial-spectral random forest (SRF) algorithm for pine wilt monitoring is proposed, for solving the problem of small manual detection range, long investigation time, and untimely discovery of the diseased tree. The proposed method organically combines spatial features with spectral information to quickly and efficiently mark the location of diseased trees. In this way, the online monitoring of the target area using the data of the Beijing-2 satellite is realized. This paper analyses the location of diseased trees and provides early warnings for disease-prone trees. The accuracy of the proposed algorithm is 86.66%, by the confusion matrix analysis.