空載光達系統可直接獲取高精度三維坐標的點雲資料，且其雷射光具有穿透樹葉縫隙的特性，能快速偵測得森林林分結構的三維空間資訊。透過其蘊涵的森林厚度及林木密度資訊，可用來估計樹冠高度模型(Canopy Height Model, CHM)和葉面積指數(Leaf Area Index, LAI)。本研究目的是探討如何應用空載光達資料估計森林地區之樹冠高度模型和葉面積指數。在推估CHM方面，本文是以點雲資料產製數值表面模型(Digital Surface Model, DSM)及數值高程模型(Digital Elevation Model, DEM)，將森林區域的DSM減DEM即得CHM。並以三種不同的空載光達系統產生之原始點雲及全波型資料進行實驗，比較六個推估得的CHM，實驗結果發現，整體差異均小，少數差異較明顯的地方主要發生在森林表面高度落差較大處。在LAI方面，則是以點雲資料計算五種雷射穿透率指標(Laser Penetration Index, LPI)來推估，LPI1是地面點占全部點的比例，LPI2是地面點強度值和全部點強度值的比例，LPI3是地面點與所有雷射光束的比值，LPI4是改良自LPI1，但增加單一回波地面點的權，LPI5則是以全波形資料計算的雷射光照射地物間面積與非地面的面積比。五種LPI與實際地面量測資料迴歸後的成果顯示，在本研究測區的低航高點雲資料中，LPI4都能得到高於0.5的R2值，說明LPI4具有較穩定且準確的LAI估計能力。而相較於即時解算的多重回波點雲，使用全波形的光達點雲穿透率指標，可提升對LAI的估計，R2可達到0.8以上，增加利用小範圍地面實測資料來推估大範圍森林區資料的可行性。

Efficiently obtaining the information in forest region such as forest structure, forest ecosystems is important for forest management. The purpose of this study is to estimate the Canopy Height Model (CHM) and the Leave Area Index (LAI) of a dense forest area by using airborne LiDAR data. CHM is estimated by taking the difference of DSM and DEM derived from LiDAR data. Estimation of LAI is achieved based on the calculation of Laser Penetration Index (LPI). Five calculations of LPI were applied in this paper: (1.) The ratio between the number of ground points and that of all the points; (2.) the ratio between the intensities of ground points and that of all the points; (3) the ratio between the number of ground points and the number of laser beams; (4) a weighting method modified from index (1); and (5) the ratio between the area of ground points and that of all the points. The study area is in a natural broadleaf forest of south Taiwan. In this study, we use three sets of airborne LiDAR data acquired with different full waveform LiDAR systems including Leica ALS60, Riegl LMS-Q680i and Optech Pegasus HD400. All of these LiDAR systems are capable of recording full waveform data, then we can get the waveform point clouds by the echo detector to do the comparison. Our experiments results show that the accuracy of CHM by different LiDAR data is about 1.5 meter. And the fourth LPI index has the highest coefficient of determination (about 0.8) and the estimation of LAI can be improved by using the waveform points.