Study On Phenology Monitoring And Pest Response Of Pinus Yunnanensis Based On Multi-source Remote Sensing Data Fusion

Pinus yunnanensis forms a large area of natural forests and artificial forests in the southwestern region of China.It integrates important functions such as afforestation,ecological construction,and environmental protection.It is the most precious forest resource and natural environment protection system in Yunnan Province.However,due to the continuous expansion of plantation area and severe drought disturbance,the health of Pinus yunnanensis forests in Yunnan is rapidly declining,and pests are becoming increasingly serious.Therefore,it is necessary to take corresponding measures.Key phenological parameters of vegetation,such as the beginning of the growing season,the end of the growing season and the length of the growing season,are important indicators to describe the response of the forest to changes in the ecological environment.In light of the cloudy rain conditions in Yunnan,this paper first attempted to build a remote sensing data set with higher spatial and temporal resolution by integrating multi-source remote sensing data(optics and optics,optics and microwaves)for time series remote sensing monitoring to Pinus yunnanensis;Further,based on TIMESAT remote sensing phenology monitoring software,to identify the differences in key phenological parameters of healthy forests and affected forests;Finally,to explore the differences in phenology between the two,and to study the response relationship with pest occurrence.Provide support for the prevention and control of the bark beetles monitoring,so as to maintain the economic value and ecological benefits of the pine forest in Yunnan.The main conclusions of this article include:(1)The results demonstrate that it is feasible to fuse the data of PROBA-V and MODIS.The fused data can improve the feasibility of PROBA-V optical data in vegetation dynamic remote sensing and phenology monitoring.(2)The time-series fusion of optical data PROBA-V and microwave data Sentinel-1A can make up for the current status of cloudy rain in the study area,thus creating a higher time resolution remote sensing data set.Compared to the use of optical or remote sensing data alone,the fusion data set can better serve forest dynamic monitoring;(3)Based on the TIMESAT phenology monitoring software,the key phenological parameters such as the beginning of the growing season,the end of the growing season,and the length of the growing season were extracted from the healthy pine forests and the damaged forests of Yunnan,which filled up the remote sensing monitoring of Pinus yunnanensis remote sensing in cloudy rain regions of China.(4)The analysis of phenological parameter differences and response to insect pests found that the start time of the growing season of the affected forest was about 40 days later than that of the healthy forest,and the end time of the growing season was delayed by about 12 days.Combined with the ground measurement data,the feasibility of the phenological monitoring method was confirmed.The analysis and study of the relationship between the differences in phenology and the occurrence of pests can provide support for the monitoring,prevention,and control of bark beetles,so as to maintain the economic value and ecological benefits of pine forests in Yunnan.