## 2 Test Sites and Data Preparation
### Forest AGB Maps from Lidar Data  
The lidar system onboard Yun-5 aircraft was the Leica ALS60 (Leica Geosystems, Heerbrugg, Switzerland) system working at 1064 nm and a 166 kHz pulse rate at 1800 m above ground level (AGL). The Yun-5 aircraft carried both the GPS receivers and Inertial Navigation System (INS) simultaneously for recording accurate positions and attitudes of the platform. Three returns were recorded, i.e. first, second and last. The positioning accuracy was estimated as vertical error \(<\)15 cm and horizontal error \(<\)50 cm by comparing with the ground control points (GCPs) from Real Time Kinematic (RTK) measurements. The Lidar data used in this study was collected from 30 August to 14 September 2012 with a point density of about 2\(\sim\)4 points/m\({}^{2}\). Please refer to [36] for more details on Lidar data acquisition. The lidar point clouds were classified as ground, vegetation, and others using TerraScan software (TerraSolid Ltd, Helsinki, Finland, [[http://www.terrasolid.com/home.php](http://www.terrasolid.com/home.php)]([http://www.terrasolid.com/home.php](http://www.terrasolid.com/home.php))) [37]. The DTM of the ground surface with a pixel size of 0.5 m was produced through the rasterization of the ALS ground points. The first return of the ALS point cloud was rasterized to produce a digital surface model (DSM) with a pixel size of 0.5m. If only one point was located within a pixel, the elevation of the point was used as the pixel value. If there were more than one point within a pixel, the mean height of vegetation \begin{table}
\begin{tabular}{c c} \hline \hline
**Species** & **Allometric Equations * \\ \hline white birch & \(\text{Wt}\;=\;0.1193\big{(}DBH^{2}\text{H}\big{)}^{0.8372}\) \\  & \(\text{Ws}\;=\;0.04607\big{(}DBH^{2}\text{H}\big{)}^{0.8722}\) \\  & \(\text{Wb}\;=\;0.0356\big{(}DBH^{2}\text{H}\big{)}^{0.5624}\) \\  & \(\text{Wl}\;=\;0.01397\big{(}DBH^{2}\text{H}\big{)}^{0.5628}\) \\  & \(\text{Wt}\;=\;\text{Ws}+\text{Wb}+\;\text{Wl}\) \\ \hline \hline \end{tabular}  
* \(\star\)Wt, Ws, Wb, WI are biomass of total, stem, branch, and leaves respectively.  
\end{table} 
Table 1: Allometric equations used in this study. Figure 1: The shape and spatial distribution of field sampling plots within the coverage of lidar data. The background true color image was from GoogleEarthTM. (**a**) the shape and size of field sampling plots; (**b**) the spatial distribution of field sampling plots, the white polygon was the area covered by Unmanned Aerial Vehicle (UAV) stereo imagery. points was used as the pixel value. The difference between DSM and DTM was the mean canopy height model (MCHM). The pixels with heights of \(<\)2.0 were set as 0.0 m to exclude shrubs and non-woody vegetation. The mean forest height of each plot was calculated by averaging all MCHM pixels, including both bare ground and vegetation pixels. The mean forest height of each subplot was correlated with the corresponding biomass density to build an estimation model of forest AGB. There were, in total, 63 subplots from 7 sampling plots. All subplots were numbered from 1 to 63 according to their serial number within each plot and the serial number of each plot. The 32 subplots with odd numbers were used to develop an estimation model of forest AGB and the rest of the 31 subplots were used for model validation. Considering that the forest AGB is linearly correlated with forest stocking volume, which is correlated with forest height in the power form as indicated in [38], the power function was chosen to develop an estimation model of forest AGB. Figure 2a shows that the determination coefficient (R\({}^{2}\)) between mean forest heights and field-measured forest AGB was 0.80, with a root mean square error (RMSE) of 24.4 Mg/ha, while Figure 2b shows that the R\({}^{2}\) between field measurement and model predicted forest AGB of the validation plots was 0.74 with a RMSE of 16.9 Mg/ha. The MCHM map with a resolution of 15 m was produced in the same way as the calculation of the mean forest height of each plot.