Abstract:

Remote sensing monitoring of forest biomass under climate change is a hot topic of current research.As an important remote sensing information source,airborne LiDAR's sampling size has a certain influence on the estimation accuracy of biomass.In this paper,the airborne LiDAR data is sampled in different sizes(21 sampling sizes,side length from 10m to 30m,interval is 1m),the LiDAR parameters of different sampling sizes are extracted,and the PLSR model is established with the biomass on the rubber forest.The effect of airborne LiDAR sampling size on the estimation accuracy of biomass on rubber forest was studied.The results show that the estimation accuracy of the aboveground biomass of rubber forest is affected by the sampling size of airborne LiDAR data.The results showed a certain regularity,but the difference was not significant.When the sampling size is less than 18m,the estimation accuracy increases with the increase of sampling size,while the sampling size is larger than 18m.The estimation accuracy decreases as the sampling size increases,and thus tends to be gentle.When the sampling size is 18m,the estimation result is the best.The model determination coefficient R ² is 0.718,the root mean square error RMSE is 17.830 t/hm ²,and the cross-validation accuracy P and RMSEcv are 82.741% and 18.874t/hm ².Compared to the estimated results at the actual sample size(30m), R ² increased by 1.989% and RMSE decreased by 2.611% at the 18m sample size.Thus,the biomass estimation process for an actual case study and research of the sampling area size is selected,thereby increasing the biomass estimation accuracy.

Key words: sample, LiDAR, biomass, rubber forest