## 4 Results
### Effect of Scanning Angle on Foliage Profile Estimation  
To investigate the influence of the airborne LiDAR scanning angle on foliage profile retrieval, we estimated the forest foliage profiles from the LiDAR data at scanning angles from 0\({}^{\circ}\) to 30\({}^{\circ}\) at 5\({}^{\circ}\) intervals. The retrieved forest foliage profiles at all scanning angles are shown in Figure 6a, and the histograms of the retrieved foliage profiles at each scanning angle are shown in Figure 6b-h. Figure 6a indicates that when the scanning angle was 0\({}^{\circ}\), the foliage profile was smallest at lower canopy heights and largest at higher canopy heights. When the scanning angle was 30\({}^{\circ}\), the foliage profile was largest at the lower canopy heights and smallest at higher canopy heights. In the lower canopy, which was lower than 18 m, the foliage profile increased with the increase of the scanning angle. However, in the upper canopy, which was higher than 18 m, the foliage profile decreased with the increase of the scanning angle, and the rate of change was low. The _RMSEs_ of the simulated foliage profiles and the estimated foliage profiles and the _Diff_s of the simulated total _LAIs_ and the retrieved total _LAIs_ at all scanning angles were calculated to quantitatively assess the accuracy of the foliage profile estimation, and the results are shown in Figure 7. Figure 7a demonstrates that the _RMSE_ decreased when the scanning angle increased from 0\({}^{\circ}\) to 20\({}^{\circ}\), and it increased when the scanning angle increased from 20\({}^{\circ}\) to 30\({}^{\circ}\). Therefore, when the scanning angle was 20\({}^{\circ}\), the estimated foliage profile had the lowest _RMSE_. Figure 7b showed that the _Diff_ decreased when the scanning angle increased from 0\({}^{\circ}\) to 20\({}^{\circ}\), and it increased when the scanning angle increased from 0\({}^{\circ}\) to 20\({}^{\circ}\). The estimated foliage profile decreased with the increase of the scanning angle, and the rate of change was low. Figure 5: An example of foliage profile processing stages for the plot when the scanning angle, flying altitude, and pulse density are 20\({}^{\circ}\), 2000 m, and one pulse/m\({}^{2}\), respectively: (**a**) return energy profile; (**b**) cumulative canopy closure profile; (**c**) cumulative _LAI_ profile; (**d**) foliage profile. 20\({}^{\circ}\) to 30\({}^{\circ}\). The total _LAI_ estimated at the scanning angle of 20\({}^{\circ}\) was the closest to the simulated _LAI_. Therefore, when the scanning angle was 20\({}^{\circ}\), the estimated foliage profile had the highest accuracy. To investigate whether the optimal scanning angle is dependent on the flying altitude, we estimated the forest foliage profiles from the LiDAR data at all scanning angles at flying altitudes of 2000 m and 4000 m. The _RMSEs_ and the _Diff_s are shown in Figures 7 and 8, respectively. Figure 8a,b show that the _RMSE_ and _Diff_ both decreased when the scanning angle increased from 0\({}^{\circ}\) to 20\({}^{\circ}\), and they increased when the scanning angle increased from 20\({}^{\circ}\) to 30\({}^{\circ}\). Therefore, when the forest foliage profile was estimated from the LiDAR data at a flying altitude of 4000 m, the optimal scanning angle was 20\({}^{\circ}\), which was the same as the results at a flying altitude of 2000 m. In conclusion, these results indicated that the optimal scanning angle is unrelated to the flying altitude. Figure 6: The estimated foliage profiles at the scanning angles from 0\({}^{\circ}\) to 30\({}^{\circ}\) at 5\({}^{\circ}\) intervals (the flying altitude and pulse density are 2000 m and one pulse/m\({}^{2}\), respectively). (**a**) The estimated foliage profiles at all scanning angles; (**b–h**) the histograms of the estimated foliage profiles at the scanning angles of 0\({}^{\circ}\), 5\({}^{\circ}\), 10\({}^{\circ}\), 15\({}^{\circ}\), 20\({}^{\circ}\), 25\({}^{\circ}\), 30\({}^{\circ}\).