空載光達推估樹冠孔隙之研究

Abstract

空載光達可有效蒐集點雲三維座標以及回訊強度等數據，是一種快速獲取空間資訊的有效方法，對於數值地形模型製作及森林資訊萃取，具有極高之應用價值。本研究嘗試由不同的思維，研擬森林樹冠孔隙之萃取，包括：以光達點雲過濾地面點為基礎的「地面點法」；利用多重回訊特性為基礎的「多重回訊法」。將分別探討二種方式對樹冠孔隙萃取之效果，以及影響萃取成果的原因及分析，並以航空像片建置立體模型，並於立體環境下進行樹冠孔隙製圖，將立製樹冠孔隙成果與本研究之空載光達萃取樹冠孔隙進行比對分析。 研究成果顯示「地面點法」因軟體自動過濾之地面點密度過於稀少，使得萃取之樹冠孔隙成果較差；「多重回訊法」與立製量測成果比對，則有82%以上的萃取成果相似。在針對差異部份進一步分析之結果顯示，多重回訊法成果表現較佳，應可作為樹冠孔隙萃取之用。

Airborne LiDAR provides an effective means for collecting the three-dimensional coordinate and signal intensity of point clouds. Information gathered is highly useful for extracting forest information and generating digital terrain model. This research studied the extraction of forest canopy gap with both photogrammetric and lidar approaches. The ground point method is based on the ground points obtained from lidar point clouds with filtering. The “Multi-return method” utilizes the characteristics of multi-return signal. These two methods are compared with the results digitized from stereo models of aerial photography. It is concluded that “Ground point method” is less effective due to the limited number of ground points after filtering, while “Multi-return method” provided good result. Over 82% of the extracted area from multi-return method is identical to those obtained from photogrammetric approach. The differences between the gaps obtained with different approaches are further analyzed and several observations are documented. It is proposed that the multi-return method with lidar data may provide an alternative to the photogrammetric method.