Small-footprint airborne LIDAR data and large-scale aero photos of Liangshui National Nature Reserve were processed. Two sets of variables (ie, individual tree height variable group and individual tree crown diameter variable group) were extracted as independent variables, and the observed tree height and crown diameter of the 10 sample plots in Liangshui National Nature Reserve were used as the dependent variable. Regression models were constructed by correlation analysis , and then tree height and crown diameter were retrieved to test the accuracy. Results showed that the forest parameter extracted from the small-footprint LIDAR data combined with the large-scale aero photos had a very strong agreement with the observed forest parameter, and the correlation coefficients of tree height and crown diameter for individual tree were 0.9361 and 0.892 5. The accuracies for height and crown diameter of individual tree were more than 86% and 81%, and the accuracies on average reached 96% and 90% respectively. Therefore, the accuracy of retrieving tree height and crown diameter by the small-footprint LIDAR data combined with large-scale aerial photos is much improved than that by the traditional way.%以凉水国家级自然保护区为研究区,对小光斑机载LIDAR数据结合同步获取的大比例尺航片进行了处理,提取出两组变量(即单株木树高变量组和单株木冠幅变量组)作为自变量,用凉水保护区内10块样地的实测树高和冠幅作为因变量,进行相关性分析,建立回归模型进而反演树高和冠幅,以检验其精度.结果表明:小光斑机载LIDAR数据结合大比例足航片提取的林木参数与实测林木参数具有很好的相关性,单株木树高和冠幅的R2分别达到0.9361和0.8925；单株木树高和冠幅估测精度分别在86％和81％以上,平均估测精度高速96％和90％.利用机载LIDAR数据及大比例尺航片反演单木树高和冠幅的精度较传统方法有显著提升.
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