應用遙測影像與空載光達資料推估森林分佈面積及樹冠體積

Estimation of Forest Region and Canopy Volume Using Airborne LiDAR Data and Remote Sensing Imagery

蕭淳伊(Chun-Yi Hsiao) ； 曾義星(Yi-Hsing Tesng)

《航測及遙測學刊》 14卷1期 (2009/03) Pp. 51-64

https://doi.org/10.6574/JPRS.2009.14(1).5

摘要

台灣森林資源豐富，傳統的森林調查方法費時耗工，而應用空載光達及遙測影像的資料結合能有效的快速獲得森林平面及高程資訊，得以三維空間的觀點來觀察森林的變化。本研究採用空載光達點雲及遙測影像來估算森林分佈面積及樹冠與地表間之體積，即樹冠體積(canopy volume)，估算樹冠體積之方法乃應用空載光達資料過濾非地面點雲後建立數值高程模型(Digital Elevation Model, DEM)，以DEM為計算樹冠體積的基面，再利用影像植物指標(vegetation index)結合光達資料過濾出樹冠點雲，以樹冠點雲與DEM產生樹冠高度模型（Canopy Height Model, CHM），計算樹冠網格面到地表網格面的體積得樹冠體積。實驗區為成大校園及南化水庫，分別推估實驗區內的森林分佈面積及樹冠體積。於成大校園中選擇七棵獨立樹，以地面光達資料分別觀測此七棵樹之樹高、樹冠幅、樹冠投影面積及樹冠體積，形成驗證比對之地真資料。實驗成果顯示空載光達資料能有效獲得森林分佈面積及樹冠體積，所得資料與地真資料比對之誤差多在10%以內，少數較大誤差也都在20%以下，數據顯示光達點雲密度不足是形成估算誤差的主要因素。實驗結果顯示南化水庫實驗區的森林樹冠體積密度約為成大實驗區的14～16倍左右。

關鍵字

光達 ； 遙測影像 ； 樹冠高度模型 ； 森林分佈面積 ； 樹冠體積

並列摘要

Efficiently obtaining information of forest regions and tree canopy volume is important for forestry management. Airborne Light Detection and Ranging (LiDAR) data is able to provide high resolution three dimensional coordinates of surface features, but does not contain spectrum information. In contrast, remote sensing imagery offers copious spectrum information that can be used to locate forest regions. Therefore, integrating the complementary LiDAR data and remote sensing imagery is an effective strategy for the estimation of forest area and canopy volume. Two data sets are required to estimate forest canopy volume: digital elevation models (DEMs) and canopy height models (CHMs). In this study, ground point clouds are first extracted from airborne LiDAR data to generate a DEM. Subsequently, the DEM is utilized as the basic datum for calculating the forest canopy volume. LiDAR data and remote sensing imagery are then combined to generate the canopy LiDAR data. The sub-grid volume accumulated between the canopy grid surface and the DEM provides the forest canopy volume. The study sites include the campus of National Cheng Kung University (NCKU) and Nan-Wha Reservoir forest area. The tree height, crown diameter, crown projected area, and canopy volume are determined for both study areas. Furthermore, the forest area and canopy volume are estimated over the study areas using the proposed techniques. The results show forest information can be acquired effectively using airborne LiDAR data and remote sensing imagery.

並列關鍵字

LiDAR ； Remote Sensing Imagery ； Canopy Height Model ； Forest Area ； Canopy Volume