期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2021
卷号：V-3-2021
页码：211-217
DOI：10.5194/isprs-annals-V-3-2021-211-2021
语种：English
出版社：Copernicus Publications
摘要：Shadow fraction is essential for improving the estimation of gross primary production, but it is difficult to be observed by satellite due to the diurnal variations. Therefore, it is necessary to estimate the 3D model with physical parameters by simulating virtual forest reflectance. In this study, we aim to estimate the optimal combination of canopy shape and Crown Coverage (CC) through simulating virtual forests reflectance. First, satellite-derived Tree Height (TH) and CC for virtual forests were compared with the ones obtained by Canopy Hight Model (CHM). Second, virtual forests with different CC and canopy shapes were created, and the reflectance and shadow fraction were simulated. The canopy shape used were cylinder, ellipsoid, half-ellipsoid, and inverted half-ellipsoid. Finally, the simulated reflectance and shadow fraction were validated with Sentinel-2 reflectance and shadow fraction from voxel model. Our results show that the mean TH is 15thinsp;plusmn;thinsp;2thinsp;m, and the CC was increased from 10% to 60% in 10% intervals. TH and CC obtained from the satellite had the Root Mean Square Error (RMSE) of 5m and 40%. Ellipsoid with 20% CC shows the lowest RMSE and the smallest discrepancy for shadow fractions at the same sun position. However, other combinations were more accurate in estimating mean daily shadow fraction. This would be caused by only one image adopted in validation, which could be improved by using multi-season images in the future.
