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摘要： 波形激光雷达（Light Detection And Ranging， LiDAR）已经大量用于森林叶面积指数（Leaf Area Index， LAI）估算，但是波形LiDAR数据估算森林LAI易受地形影响。地形坡度引起的波形展宽使得地面回波和植被冠层回波信息混合在一起，难以得到准确的地面回波和冠层回波，进而影响到LAI估算精度。为了估算不同地形坡度条件下的LAI，本文采用一种坡度自适应的方法处理机载LVIS和星载GLAS波形数据。通过坡度自适应的方法得到地面波峰位置，基于高度阈值来区分地面回波和冠层回波，进而得到能量比值用于LAI估算。基于LVIS和GLAS数据，估算了不同森林站点的LAI，并利用实测LAI数据进行检验。结果表明：利用波形LiDAR数据可以估算森林LAI，坡度自适应方法可以改善地形的影响，提高LAI估算精度。对于机载LVIS，估算新英格兰森林LAI精度为R2=0.77和RMSE=0.21；对于星载GLAS，估算塞罕坝森林LAI精度为R2=0.81和RMSE=0.28。无论机载还是星载数据，该方法都有着较高的精度，对于复杂地形估算LAI具有一定潜力。 关键词： 地形坡度;  激光雷达;  叶面积指数;  LVIS;  GLAS     Abstract: Estimation of forest Leaf Area Index （LAI） using waveform LiDAR has been performed in many studies. However， the LAI estimation from waveform LiDAR was affected by terrain slope. Terrain slopes can blur the boundary between ground and canopy returns in a waveform LiDAR， and it is difficult to obtain accurate ground return and canopy return. In order to estimate the LAI under different terrain slopes， a slope-adaptive method was used to process the airborne LVIS and spaceborne GLAS waveform data. First， the ground peak position was obtained by slope-adaptive method. Subsequently， the ground return and canopy return were separated based on the height threshold. Finally， the energy ratios were calculated for LAI estimation. For the LVIS and GLAS data， LAI of different forest sites was estimated and validated with the field LAI. The result shows that forest LAI was successfully estimated with waveform LiDAR data， and the slope-adaptive method can overcome the effect of terrain and improve the accuracy of LAI estimation. For airborne LVIS， the accuracy of LAI in New England is R2 = 0.77 and RMSE = 0.21. For spaceborne GLAS， the accuracy of LAI in the Saihanba is R2 = 0.81 and RMSE = 0.28. No matter on the airborne or spaceborne data， the proposed method indicates high accuracy and shows potential for LAI estimation over complex topography.

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