Inversion Of Canopy Closure Of Artificial Coniferous Forest Based On 4-scale Model

Canopy density refers to the ratio of the vertical projection area of the stand canopy to the area of the forest,which is an important index to reflect the canopy canopy density in the stand and the space utilization of trees,and is also an important investigation factor in the survey planning and design of forest resources.In forest management,canopy density is an important index to determine the intensity of cultivation and cutting,and an indispensable factor to estimate the forest stock through remote sensing images.In the present research,canopy density is not only an important factor to determine forest status and estimate forest stock quantity,but also an important index to evaluate stand quality,divide stand type,divide land type.Accurate canopy density measurement is of great significance for precise forest management planning,accurate forest growth prediction and accurate forest management decision optimization.There are many ways to obtain forest canopy closure.Traditional measurement methods include sample point method,sample line method,visual measurement method,and tree crown projection method.The development of remote sensing technology provides a better way to estimate forest canopy closure,but the spectral resolution of multispectral remote sensing data is limited,different forest types have similar spectral characteristics,and the lighting conditions that optical remote sensing depends on vary greatly.It also caused different spectral characteristics of the same forest type.Lidar(Light Detection And Ranging,Li DAR)is an active remote sensing technology that has developed very rapidly internationally in recent years.Degree and above-ground biomass,etc.)However,the collection cost of Li DAR data is too high,and the canopy of broad-leaved tree species is easily lost.In recent years,the method of inverting forest parameters based on physical optical geometry models has gradually become the mainstream,and the inversion accuracy has been continuously improved,providing a new method for quantitative inversion of forest canopy closure.In this paper,the artificial coniferous forest in Wangyedian Experimental Forest Farm,Chifeng City,Inner Mongolia was used as the research area.The 4-Scale geometric optical model and remote sensing data were used to reflect the forest canopy density in the research area.Finally,the closedness measured by the fish-eye camera and the sample point method were used to verify the model simulation results.This paper discusses an effective method to obtain the canopy canopy density of forest canopy with 4-Scale geometric optical model combined with remote sensing imagery,and provides a reference and basis for inverting canopy density using mechanism model.The specific research contents are as follows:(1)Based on the measured leaf area index of the plot,use the hyperspectral remote sensing image to retrieve the regional leaf area index.(2)The background visibility probability in the 4-Scale model is introduced.The background scale is used to simulate the background visibility probability and canopy reflectance under different leaf area indexes and different tree structure parameters.(3)Using remote sensing data,using the LAI value of the pixel-scale leaf area index as the control variable,based on the canopy reflectance data to invert the canopy canopy closure of the forest to find the background visible probability corresponding to the LAI,and then inverse the study area Forest canopy closure.(4)The results obtained by using three methods of measuring canopy closure(spot point method,transect method,fish-eye photo method)are compared with the inversion canopy closure results obtained from the 4-Scale model:At the same time,the trunk's effect on fisheye is considered.Photo effects.Finally,The relationship between the estimated LAI value and the real LAI value by the unary linear model was analyzed.The correlation coefficient R2 of the two is 0.649,and the root mean square error RMSE is 1.6082.There is a good linear relationship between them,which indicates that it is feasible to estimate leaf surface index with a linear model of one variable.it is concluded that the 4-Scale model can well retrieve the canopy density of artificial coniferous forest.Compared with the other three methods for measuring canopy density,the 4-Scale model can invert the melancholia and the canopy extracted from fish-eye photos.The degree of linearity has a good linear relationship,the determination coefficient R2 is 0.6280,the standard error RMSE=0.0476,and the depression degree R2 and RMSE calculated by the sample point method and the sample line method are 0.5591,0.0518,0.5395,and 0.0529,respectively.The overall analysis of the canopy degree after removing the trunk from the fish-eye photo and the inversion degree obtained from the 4-Scale model R2 was 0.6847;for the artificial larch forest,R2 increased from 0.4226 to 0.6153;for the artificial pine forest,R2 increased from 0.7646 Becomes 0.7561.It further illustrates that the trunk will have a certain effect on the canopy closure result of fish-eye photos extraction.In the end,it can be concluded that the 4-Scale model needle can well retrieve the canopy closure of artificial coniferous forests.There is a good relationship between the result of inverting canopy closure using the 4-scale model and the canopy extraction extracted from fish-eye photos.