Estimation of Forest Carbon Storage in Chinese Fir Plantation by UAV-Lidar
Forest carbon storage is an important index to measure the basic characteristics of forest ecosys-tem.Traditional carbon storage estimation method requires a lot of time,manpower and material re-sources.In this study,unmanned aerial vehicle equipped with lidar was used to acquire airborne laser data and establish a forest carbon storage estimation model to provide reference for obtaining forest carbon stor-age within the region,so as to better monitor forest resources.Chinese fir plantation was taken as the re-search object,and the airborne lidar point cloud data were used to obtain the point cloud characteristic vari-ables,which were used as modeling variables for model establishment.The modeling variables were select-ed through different screening variables,and the nonlinear regression model,linear regression model and random forest model were established,respectively.The optimal model was selected by comparing R2,RMSE and MAE of the models for subsequent research.The results showed that 1)The best fitting effect of the three models was random forest model,whose R2,RMSE and MAE were 0.95,0.53 and 0.44 t/hm2,respectively.In the non-linear regression model,R2,RMSE,and MAE were 0.71,0.66 and 0.56 t/hm2,while in the linear regression model,R2,RMSE,and MAE were 0.67,0.88 and 0.80 t/hm2.2)In this study,a total of 101 point cloud characteristic variables were extracted.Through variable screening,it was found that height variables and density variables were greater than intensity variables in both correla-tion and importance.3)The effect of adding preferred variables on the accuracy of random forest was com-pared.After adding preferred variables,model R2 did not change,but RMSE and MAE were smaller than those without adding preferred variables.The point cloud characteristic variables obtained by airborne Li-DAR point cloud data were used to establish a model.Compared with nonlinear regression and linear re-gression models,the random forest model had the highest accuracy,and the carbon storage in the study are-a was estimated to be 480.65 t by using it,which was the closest to the measured value.Therefore,the sto-chastic forest model is more suitable for estimating regional forest carbon storage.
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