Abstract:

As one of the important components of desert ecosystem， the aboveground biomass （AGB） of Haloxylon ammodendron reflects the health of community and ecosystem to a certain extent， which is of great significance to the carbon cycle of desert ecosystem. In this paper， H. ammodendron in Ulan Buh Desert was taken as the research object. Based on the plant height （H）， crown width （C）， visible light vegetation index （VI） extracted by UAV laser radar and the three characteristic indexes of the combination of the two， multiple stepwise regression （MSR）， principal component regression （PCR） and partial least squares regression （PLSR） were used to estimate the above-ground biomass of H. ammodendron. The determination coefficient R² and root mean square error RMSE were used for evaluation. The results showed that： （1） The accuracy of plant height （R²=0.85， RMSE=0.32 m） and crown width （R²=0.80， RMSE=0.73 m） extracted from UAV LiDAR point cloud data was high. （2） MSR， PCR and PLSR models had good fitting effects， and R² was greater than 0.8， while the root mean square error of PLSR model was the smallest （2.86 kg·plant^-1）， which could be used as the optimal model for AGB estimation of H. ammodendron. The results show that the use of UAV LiDAR data can effectively extract the single tree parameter factors （H， C） of H. ammodendron， and carry out the estimation of aboveground biomass of low vegetation in desert.

Key words: aboveground biomass, Haloxylon ammodendron, UAV laser radar, plant height, crown width, vegetation index