空載雷射掃描為一可快速獲取地面物體三維空間資訊之技術，而新型發展之全波形（Full-Waveform）系統可完整記錄雷射回波訊號之波形，透過波形偵測與波形擬合等資料前處理，可得到代表地物獨特反射特性的波形參數資料，包括振幅值（Amplitude）、波形寬（Pulse-width）與後續計算之散射截面積係數（Backscatter cross-section coefficient）。 得到各點位之波形資料後，將以波形資料為主進行位於山區之實驗區地物分類，並將使用由實驗區航照影像提供之RGB波段光譜資料計算之綠度指數（Greenness）與計算影像灰階統計值之紋理參數如均質度（Homogeneity）、熵值（Entropy）與R波段平均值（Mean）等參數輔助分類。分類進行之前，透過抽樣實驗區候選地類包括樹林、草地、道路與樹種建物，並以貝氏定理（Bayes Theorem）分析計算不同地物類別在各分類參數區間內的貝氏機率，接著以多項式函數擬合各地類在不同參數之貝氏機率曲線，並以計算反曲點之方式自動化決定該分類參數之門檻值區間。 分類成果顯示，全波形系統提供之波形資料對於受上層植物遮蔽與陰影區之植物點與道路點之分類有顯著之成果，且透過物體對於波形資料之反射特性不同，具備應用於區別不同建築材質類別之潛力。 / Airborne Laser Scanning is a technique capable of acquiring 3D information of land objects. The latest full-waveform system is further improved with the ability of recording complete waveform of reflected laser signal. After the preprocessing procedures such as pulse detection and pulse fitting, the waveform information including amplitude, pulse width and backscatter cross-section were derived. Such information was valuable as they represented unique properties of land objects. In this study, waveform information of all scanned points were utilized to classify land cover in the test area located in mountain area. Additionally, the Greenness value as well as the texture parameters such as Homogeneity, Entropy and Mean of R band calculated from the ortho-image were used for classification. We aimed to classify the point cloud into vegetation, road and building categories. The Bayes Theorem was used to determine the threshold range of each parameters for classification. As a result, the waveform information were useful for classifying road points covered by upper vegetation points and also vegetation and road points located in shadow area. Moreover, through the analysis of reflective properties of different object using waveform parameters, it was of potential to be applied to distinguish material of buildings.

在植被覆蓋的山區中，由於空載雷射掃描可穿透植被間縫隙的特性，有較高機會收集到植被下的地面資訊，因此適合作為製作植被覆蓋地區數值高程模型的資料來源，而在過濾過程中，一般僅利用點雲間的三維位置關係進行幾何過濾，而全波形空載雷射掃描可另外提供點位的波形寬、振幅值、散射截面積以及散射截面積數等波形資料，本研究將透過波形資料分析進行點雲過濾。 首先經最低點採樣後，本研究利用貝氏定理自動分析並計算得到地面點的波形資料的特徵區間範圍，採用振幅值、散射截面積以及散射截面積係數得到的特徵區間範圍開始第一階段的波形資料過濾，完成後再以第二階段的一般幾何過濾濾除剩餘之非地面點，最後的成果將與航測以及只採用幾何過濾時的成果比較。 由研究成果中顯示，不同的植被覆蓋間的單一回波波形資料的差異較明顯，最後回波類似。同一植被覆蓋下的單一回波及最後回波反應不同。而在成果的比較中，本實驗的成果與不採用波形資料輔助的成果大致相同本研究的成果在部分植被覆蓋的區域成果稍差，但透過波形過濾，可將幾何過濾所需計算的點雲數減少許多，可以增進整理過濾的效率。本研究的成果與航測相比時，在植被覆蓋區域較航測成果貼近實際的地面起伏，數值高程模型成果較為正確。 / In mountain areas covered with vegetation, discrete airborne laser scanning is an appropriate technique to produce DEMs for its laser signal is able to reach the ground beneath the vegetation. Once the scanned data was derived, point cloud filtering was performed based on the geometry relationship between the points at the processing stage. With the development of the advanced full-waveform laser scanning system, the additional waveform data has been proved useful for improving the performance of point cloud filtering. This research therefore focused on using the waveform data to extract DEM over vegetation covered area. The amplitude, backscatter cross-section and backscatter cross-section coefficient were the waveform parameters used to do the filtering. After initial waveform analysis was accomplished, an automated method to determine threshold range of each parameter representing ground points was proposed. By applying the thresholds, the original point cloud was filtered. Geometric filtering method was then used to eliminate the remained non-ground points. As a result, the DEM over the target vegetated area was derived. With the comparison against photogrammetric DEM and DEM derived from traditional filtering method, it was demonstrated that the quality of the resultant DEM was improved.