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Carbon sink trading is an important aspect of carbon trading in China, and can have important significance in offsetting carbon emissions and improving ecological compensation. The use of unmanned aerial vehicles (UAVs) offers new opportunities for shrub carbon sink and accounts as a substitute for time-consuming and expensive plot investigations to estimate the carbon sink by using the aboveground carbon stock monitored by UAV. However, the UAV-based estimation of the aboveground carbon stock of densely planted shrubs still faces certain challenges. The specific objectives of this research are as follows: (1) to test the statistical relationship between the aboveground carbon stock and volume of a densely planted shrub belt, and (2) to develop a model to estimate aboveground carbon stock by monitoring the volume of the densely planted shrub belt using a UAV. The study showed that (i) the aboveground carbon stock would increase with the increase in the volume of the shrub belt, (ii) an estimation model of the aboveground carbon stock of the densely planted shrub belt was developed (R = 0.89,P < 0.01), and (iii) the validation assessment to estimate aboveground carbon stock by using the UAV-based estimation model produced a coefficient of determination of R2 = 0.74 and an overall root mean square error of 18.79 kg CO2e. Good prediction ability of the model was determined using leave-one-out cross-validation (LOOCV). This output information is valuable for the design of operations in the framework of precise carbon-sink accounting of shrubs. In addition, a method using an UAV was developed and validated for the quick estimation of aboveground carbon stock for densely planted shrubs, thereby providing a potential alternative to time-consuming and expensive plot investigations of aboveground carbon-stock accounting, which is necessary for shrub projects in the carbon trading market in China.

Quick Aboveground Carbon Stock Estimation of Densely Planted Shrubs by Using Point Cloud Derived from Unmanned Aerial Vehicle