Early Warning Of Bursaphelenchus Xylophilus Based On Remote Sensing Technology

Bursaphelenchus xylophilus was a kind of destructive forest pests and diseases which was caused by Bursaphelenchus xylophilus. In recent years, it had brought tremendous losses to our pine forest resources, natural environment, national economy and even social development. Fujian Province was a high incidence area of Bursaphelenchus xylophilus, so it was an urgent task and had great significance to carry out Bursaphelenchus xylophilus monitoring and prediction. Using remote sensing technology could effectively achieve the dynamic monitoring and prediction of the occurrence and development of Bursaphelenchus xylophilus, in order to make timely and effective mitigation measures to minimize the loss brought by the occurrence and spread of Bursaphelenchus xylophilus as far as possible.This paper chose Sanming City and Taining County of Fujian Province as research area and chose Pinus massoniana infected by Bursaphelenchus xylophilus as research object, combining with SPOT5remote sensing image, making wood seized scale, ecological factors survey, transpiration rate determination, and spectral characteristics acquisition to Pinus massoniana in different disease infecting periods. According to the typical vegetation spectral differences in the study area, use Decision Tree Method based on Knowledge Rules to classify and extract the information of Pinus massoniana. According to the wild-collected spectral characteristics of Pinus massoniana, draw the curve of the spectral features to identify the best band of Pinus massoniana remote sensing monitoring. The results showed that near infrared band was the most sensitive band to show the changes of spectral reflectance while plants were infected by pests and diseases. According to the transpiration rate determination of Pinus massoniana, transpiration rate variation of Pinus massoniana between healthy ones and infected ones was obtained. And the transpiration rate could be an effective early diagnosis factor. Making canonical correlation analysis between Pinus massoniana and ecological factors, the results showed that, plants with shorter height, smaller diameter, lower elevation, worse site quality, growing in sunny side and growing in upper slope were more likely to be infected by Bursaphelenchus xylophilus.