Quantitative Study On The Apparent Characteristic Of Phyllostachys Pubescens Expansion To Cunninghamia Lanceolata Forest By Remote Sensing

Phyllostachys pubescens and Cunninghamia lanceolata are important components of forest resources in China.Due to the similar site requirements and the interference of human factors,there are a lot of mixed states,which are mainly caused by the expansion and growth of phyllostachys pubescens underground stems.At present,there are many problems in the investigation of phyllostachys pubescens rhizomatous expansion.Unmanned aerial vehicle remote sensing is an effective means to obtain fine vegetation information,which can easily and quickly realize the monitoring of forest resources.However,due to the influence of forest and soil cover,remote sensing could not directly detect the growth direction of phyllostachys pubescens rhizomes.Changes in forest surface characteristics caused by phyllostachys pubescens underground stems,that is,apparent characteristics,can be monitored by remote sensing technology.Therefore,using remote sensing to monitor the process of phyllostachys pubescens expanding Cunninghamia lanceolata forest must rely on the apparent characteristics.Taking the phyllostachys pubescensCunninghamia lanceolata mixed forest in Tianbaoyan Nature Reserve,Yongan city,Fujian Province as the object,the quantifiable apparent factors(stand spectral characteristics,stand density,stand leaf area index)of phyllostachys pubescens expanding Cunninghamia lanceolata forest were analyzed and determined.The comprehensive index of apparent characteristics was established based on the apparent factors,and the apparent characteristics were quantified by remote sensing.The dynamic changes of the apparent characteristic composite index and its influencing factors were analyzed.In order to provide reference for effective monitoring and scientific regulation of phyllostachys pubescens expansion behavior.The main conclusions are as follows:(1)phyllostachys pubescens expansion mainly through underground stems.Although underground stems are difficult to detect directly,changes in vegetation growth and aboveground structure caused by changes in underground stem structure can be monitored.The expansion of phyllostachys pubescens is allelopathic,which changes the soil microenvironment and then affects the growth process of phyllostachys pubescens.At the same time,the number of standing trees increased and the density of mixed stand increased.The growth of Phyllostachys pubescens from new Phyllostachys pubescens directly promoted the increase of leaf area in mixed stand.These features can be identified and quantified by remote sensing technology.Therefore,the spectral characteristics,stand density and stand leaf area were determined as quantifiable apparent factors during the expansion of Phyllostachys pubescens to Cunninghamia lanceolata.(2)Complex Vegetation Index(CVI)and Yellow Factor(YF),which can reflect the growth and health status of vegetation,were selected as the expression factors of spectral characteristics of stand at mixed interface.The composite vegetation index was constructed by Normalized Difference Vegetation Index(NDVI),Green Normalized Difference Vegetation Index(GNDVI),Ratio Vegetation Index(RVI),Differnce vegetation index(DVI),Nitrogen Reflection Index(NRI),Modified Soil Adjustment Vegetation Index(MSAVI)and Wide Dynamic Range Vegetation Index(WDRVI).Green band(Green)and Red band(Red)were used to construct Yellow Factor.The expression of vegetation composite index constructed by principal component analysis is VCI=0.137×WDRVI+0.142×NDVI+0.140×NRI+0.146×GNDVI+0.120×RVI+0.156×DVI+0.159×MSAVI,and the expression of yellow factor is as follows:.(3)It is based on visible light image and DSM data acquired by UAV.According to the tree canopy shape characteristics,the appropriate segmentation scale was selected to carry out object-oriented multi-scale segmentation of the image.The results of object-oriented multi-scale segmentation are combined with the actual location of trees to select training samples.On this basis,remote sensing estimation of stand density was realized by K-nearest Neighbor method.The overall accuracy of stand density extraction in 2020 and 2021 was 78.40% and 73.60%,respectively.(4)In this study,different methods(logarithm,power,linear,exponential function,random forest model,and support vector machine model)were used to analyze the effects of vegetation indices with different spatial resolutions(0.06 m,0.1m,0.3m,0.5m)on the inversion results of LAI.The results show that the random forest model with spatial resolution of 1m has the best estimation effect.The average relative accuracy of this model in 2020 and 2021 is 86.75% and 86.08%.(5)At different stages of Phyllostachys pubescens expansion of Cunninghamia lanceolata forest,the changes of spectral characteristics,stand density and stand leaf area were different to some extent.Based on the apparent factors obtained by remote sensing,the apparent characteristics composite index(apparent characteristics composite index=0.558× stand leaf area index +0.348× composite vegetation index+0.054× yellow factor +0.041× stand density)constructed by principal component analysis was used to quantify the apparent characteristics by remote sensing.There was a significant positive correlation between the apparent characteristic composite index and the degree of expansion,and the correlation coefficient reached 0.574.It was reasonable to use the apparent characteristic to indicate the degree of expansion of phyllostachys pubescens.On this basis,the dynamic changes of the apparent characteristic composite index and its influencing factors are analyzed.The overall apparent feature composite index from 2020 to 2021 shows an upward trend.With the deepening of the expansion degree of phyllostachys pubescens,the comprehensive index of apparent characteristics and the interannual growth of each expansion stage increased gradually.From 2020 to 2021,the vegetation composite index,yellow factor,stand density and leaf area index all showed an increasing trend.With the deepening of bamboo expansion,the interannual growth of composite vegetation index,stand density,stand leaf area index and each expansion stage increased gradually,while the interannual growth of yellow factor and each expansion stage decreased gradually.