Studying On The Reconstruction Of Vegetation Cover And Management Factor(C Factor)Based On Remote Sensing In Southern Red Soil Water And Soil Loss Region

The reasonable estimate of vegetation coverage and management factor(C)is the basis of pplication to the Universal Soil Loss Equation(USLE)and the Revised Universal Soil Loss Equation(RUSLE)for regional soil erosion accurately forecasting.But in the current study,single vegetation coverage was usually used as the input parameter of model to extract C value,there were some errors about final evaluation results when USLE or RUSLE was used to forecast soil and water loss in terms of forest resources.The measure process of improving forest cover and management factor C reflected rainfall erosion slowed down by forest vegetation,which was an important prerequisite of USLE or RUSLE applied to monitoring soil and water loss of forest resources.In view of this,The quantitative relationship among Leaf Area Index(LAI),soil based respiration value and vegetation cover was studied on the basis of LAI reflecting the forest canopy vertical structure and the spatial distribution differences of soil respiration implicitly indicating understory vegetation and litter by considering the reduction effect of vertical structure of forest canopy,understory vegetation and litter based on Remote Sensing Technology.And then the internal relation of forest vegetation vertical structure slowing down rainfall kinetic energy was expressed.The relationship between remote sensing data with factor C was established by improving factor C estimation process on the basis of measured data of runoff plot.The main results as follows:(1)Leaf Area Index(LAI)inversion model was established by using Modified Soil adjusted vegetation index(MSAVI),Normalized Difference Vegetation Index(NDVI),Renormalized difference vegetation index(RDVI),Ratio vegetation index(RVI)and Soil adjusted vegetation index(SAVI)on the basis of 5 models including regression model,including linear model,logarithmic model,quadratic model,exponentiation model and exponential model,meanwhile,the accuracy was checked.The result showed that there were highest predicted precision of Leaf Area Index(LAI)estimated by power function model on the basis of NDVI that was 82.99%and it s RMSE was 0.5862.(2)Soil base respiration was inverted by Van,t Hoff soil respiration model after improved and accuracy was validated by using soil respiration measured data.Results showed that the average of the spatial distribution of soil respiration was 10.17gC·m-2/months;the average relative accuracy of Masson pine,Chinese FIR and broad leaved was respectively 77.9%,82.45%,72.5%;the average relative accuracy was 77.83%throughout the region;Masson pine,Chinese FIR,broad leaved,and region wide average estimation accuracy was greater than 89%.(3)Soil base respiration was inverted by Van,t Hoff so1l respiration model after improved and accuracy was validated by using soil respiration measured data.Results showed that the average of the spatial distribution of soil respiration was 10.17gC·m-2/months;the average relative accuracy of Masson pine,Chinese FIR and broad leaved was respectively 77.9%,82.45%,72.5%;the average relative accuracy was 77.83%throughout the region;Masson pine,Chinese FIR,broad leaved,and region wide average estimation accuracy was greater than 89%.(4)The relationship among soil respiration with organic carbon content,total nitrogen content,shrub and herb layer coverage,litter thickness and stand canopy density were analyzed.And statistical models between soil respirationand each foctor was established and the applicability of Soil respiration implicitly indicating the understory vegetation was discussed.Results showed that every factor were significantly positively correlatedwith soil respiration(P<0.01);the relationship of RMSE was stand canopy density(2.21)>total nitrogen content(2.17)>organic carbon content(2.13)>litter thickness(1.96)>LAI(1.69)>shrub and herb layer coverage(1.67);The rank of average relative accuracy was that LAI(86.41%)>litter thickness(83.87%)>organic carboncontent(83.87%)=total nitrogen content(83.87%)>shrub and herb layer coverage(83.41%).It showed that undergrowth vegetation and litter thickness were better depicted by soil respiration.(?)(5)By using runoff plot measured data in natural rainfall slope and by mean of using LAI to reflect the general conditions of forest canopy vertical structure with soil respiration to embody the condition of undergrowth vegetation and litter,forest vegetation structure factor(Cs)was brought forward and it was taking comprehensive analysis of soil and water conservation effect under different levels of forest vegetation through manytests.After repeated testing,the cCoupling model of quantitative of factor C and forest vegetation structure factor was constructed:The rationality was qualitatively validated combining with land use thematic map on the basis of the factor C of forest vegetation structure factor.Combing calculated values of factor C with the measured soil loss of runoff plot,the result showed that the precision of factor C model based on vegetation coverage was the highest(R2=0.358).