The leaf area index (LAI) is a key forest parameter which can be used for the estimation of forest ecosystems or forest fire activity. Since to investigate all the trees or vegetation in forestry for LAI measurements in field surveying is almost impossible, one way to measurement LAI is to take some samples to represent the whole forest in the study area. To acquire the geometric structure of forestry, the Light Detection And Ranging (LiDAR) system has been considered as an efficient technique due to the effective data collection of a large area. The penetration of forest canopy is also an important characteristic compared with other surveying technique such as Photogrammetry. LiDAR data directly provides the three dimensional points which can be classified as ground points and non-ground points. The purpose of this research is to compare two kinds of data sources: waveform data and multi-return LiDAR data for the LAI estimation. Since the waveform data records the intensity values along the laser lighting path, more physical features and echoes can be extracted. Some weak or overlapping echoes can be therefore further extracted by a developed echo detector. Those extra-points are expected to improve the estimation of LAI values compared with only using the multi-return points. The study area is located in Nanrenshan of Pingtung County, Taiwan. In this study we use two kinds of laser penetration index (LPI) which can be translated into LAI values. The first type of LPI is calculated by the ratio of the numbers between ground points (< 1m height) and total points. The second is the ratio of the intensity between ground points and total points. After compared with the in-situ measurements of LAI which were measured by the LI-COR LAI-2000 Plant Canopy Analyzer, our preliminary results show the LAI values can be better estimated by the waveform LiDAR data than the multi-return LiDAR data.