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  • 學位論文

以空載光達資料推估森林生物量與碳儲存量

Estimating Forest Biomass and Carbon Storage Using Airborne Laser Scanning Data

指導教授 : 陳朝圳

摘要


京都議定書中已肯定森林對減緩全球暖化的功效,並規定森林碳儲存的定義與量化方式,因此如何快速準確的進行森林碳儲存量的調查,為一項重要工作。由於以取樣方式,進行碳儲存的地面人工調查,並以樣區生物量推算空間性的生物量,其在時效上不但費時費力,且其調查精確度亦難提高,因此各國皆致力如何應用衛星或空載遙測,進行碳儲存的估算,以解決碳儲存推估之時效及準確度等相關問題。隨著遙測技術的發展,目前已廣泛應用於森林經營,其中空載光達系統對於林分結構中之各項性態值推估,已有相當程度的研究成果,成為近年來應用於森林調查之新技術,光達系統具有穿透性與多重反射之特性,可收集三維的點雲資料,由國內外許多研究得知,光達資料可直接或間接地對森林生物量及碳儲存量進行估算。本研究以溪頭營林區70年生柳杉不同栽植距離之生長量試驗區為研究對象,進行地面林木材積量調查,並依照IPCC推估方法,進行地面生物量估算與碳儲存量的轉換。光達資料取得為工研院能資所於2006年6月於溪頭樣區所拍攝。資料經過過濾以及正規化處理後,建構樹冠高度模型,進而推估林分高、林分枝下高、回波比例等相關衍生變數,並將光達所推估之變數與地面調查所推估之林分生物量進行多元迴歸分析,建立以光達CHM模型為基礎之林分生物量推估模式。本研究另引用三維像元的概念,依照1 m等間距高度、分割研究樣區範圍內點雲資料,計算各分層中每一個1 m×1 m網格內出現之點雲數佔該立方柱內總點雲數量之比值,輸出成網格式影像,再以15個樣區邊界為範圍,計算每個分層中各樣區之林分高、林分枝下高、回波比例平均值等變數,並與地面15個調查樣區所推估之林分生物量,進行迴歸分析,建立以三維像元為基礎之森林生物量及碳儲存量推估模式,並探討不同取樣體積(1 × 1 × 1 m、2 × 2 × 2 m、3 × 3 × 3 m、4 × 4 × 4 m、5 × 5 × 5 m)對推估模式之準確度影響。研究結果顯示CHM衍生變數所建立之生物量推估模式,以光達之樹冠基礎高與60%林分高兩變數之相關性最高R=0.84,判定係數R2=0.70;三維像元變數之生物量推估模式,則以取樣體積1 m3配合高度21、22、23與28 m處之點雲資料所計算之比例等變數,其相關係數最理想R=0.86,判定係數R2=0.74。未來對兩種模式之運用,可根據林地狀況與光達點雲分布情形,來獲得更加準確之森林生物量及碳儲存量推估。

並列摘要


Kyoto Protocol had declared that forest could mitigate the greenhouse effect of climate change and provided the definition of forest carbon storage and quantitative methods. At present, how to carry out the survey methodology of forest carbon storage is an important issue. Using the sampling ground survey to estimate biomass for regional level is time consuming and difficult to improve the accuracy, therefore, every country were committed to the application of satellite or airborne remote sensing data for estimating the carbon storage to solve the problems of timeliness and accuracy. In forestry, remote sensing provided many kinds of matured technology to use, such as Airborne LiDAR which could detect the variables of stand structure and estimating carbon storage directly or indirectly that was a new application for forest survey in rent years. The 70 years old, different planting density of Cryptomeria japonica experiment area was selected for this study in Chitou area. The timber volume was measured by ground survey and the carbon storage was transferred from the volume and biomass by the conversion coefficient of IPCC method. A small-footprint LiDAR dataset was acquired by Industrial Technology Research Institute (ITRI) over the study area in June 2006. The raw data was processed by the filtering and normalized, and constructed the parameters of stand height, crown base height, echo ratio with CHM. Multiple regression analysis was used for establishment the relationship between the biomass and parameters of estimating from the LiDAR CHM. The results indicated that the LiDAR crown base and 60% stand height were high correlation with biomass (R2=0.70). LiDAR height bins were generated as multiband images of 1m height intervals and 1 m × 1 m pixel dimensions, i.e., 1 × 1 × 1 m voxels. A pixel value represents the number of laser points as a percentage of the total number of points summed up for all pixels in the stack at this position. Average pixel value of different dimension voxels (1 × 1 × 1 m, 2 × 2 × 2 m, 3 × 3 × 3 m, 4 × 4 × 4 m, 5 × 5 × 5 m) were calculated with 15 plots as independent variable for regression with stand biomass. The results indicated that average pixel value of 1×1×1 m voxels of 21, 22, 23, 28 bins were the best fitting with biomass (R2=0.74). In this study, we had two different methods to predicate carbon storage by Airborne LiDAR. How to select adaptive method to estimate the biomass and carbon storage will follow the site situation and status of point cloud distribution.

參考文獻


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