簡易檢索 / 詳目顯示

回結果列表
研究生： 鄭詠心
Cheng, Youn-Sin
論文名稱： 利用LiDAR對第一生產力資源參數與林相自動判識差異分析
Variance Analysis of Net Primary Production Parameters and Automatic Identification of Different Forest Stands with LiDAR
指導教授： 陳昭旭
Chen, Chao-Shi
余騰鐸
Yu, Ting-To
學位類別： 碩士
Master
系所名稱： 工學院 - 資源工程學系
Department of Resources Engineering
論文出版年： 2009
畢業學年度： 97
語文別： 中文
論文頁數： 103
中文關鍵詞： 光達 、正規化 、物件式分類法 、穿透率 、反射強度 、第一生產力
外文關鍵詞： Object-Oriented Classification, Normalize, Penetration rate, Intensity, Net Primary Productivity (NPP), LiDAR
相關次數： 點閱：103  下載：4 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • 隨著科技的快速發展，遙測技術廣泛的運用於森林資源調查，傳統多以AVHRR、MODIS、SPOT等衛星影像對全球或是大區域尺度進行植被冠層第一生產力估算，鮮於考慮植生穿透率及林相之差異。
    研究中以兩米高解析度之福衛二號(FORMOSAT-2)影像進行第一生產力估算，配合物件式分類法進行林相植生區域之分割與區塊分類，並運用空載光達的高密度測點與可分離植生多重回波訊號之特性，迅速獲取林相植生之穿透率與反射強度。其流程主要分為五個階段，第一階段為資料前處理。第二階段以物件式分類法進行單一林相植生區域萃取。第三階段以光達資料進行林相植生區穿透率運算以及第一回波反射強度萃取。第四階段為各林相冠層與穿透層之第一生產力估算。第五階段進行林相第一回波回波反射強度比對。
    研究結果顯示，各個高程之穿透率，平均以檳榔樹林16.06%為最大，竹林3.49%為最小。高程100公尺及400公尺處之第一生產力估算結果，平均以檳榔樹林66.36(gC/m2/月)為最高，竹林52.08(gC/m2/月)為最低；高程600公尺處NPP檳榔樹林高於相思樹林；高程850公尺處NPP則以相思樹林高於檳榔樹林。而各林相的反射強度長條圖結果具有相似性，以高程100公尺及400公尺之結果進行回歸得相關係數值皆為0.9以上。並利用相同航帶所取得之雷射強度值，可反推演算得飛航高度並進行反射強度值之正規化。

    Due to the rapid development of science and technology, the remote sensing technology had widely used in evaluating the forest resource inventory. Traditional method to estimate the global or large scale Net Primary Production with AVHRR or MODIS or SPOT satellite images. The penetrating rate and different forest stand of plantation did not considered in such process.
    We estimate the NPP with 2m-spatial resolution images of FORMOSAT-2 and extract regional plantation with object-oriented classification. LiDAR is capable of measuring objects with very high density and multiple return signal among tree crowns, therefore it can rapidly obtain the penetration rate and intensity about forest stands. The proposed schema in the study comprises five major steps: (1) LiDAR data preprocessing, (2) vegetated regional extraction with Obgect-Oriented Classification, (3)LiDAR data in vegetated regional penetration rate calculation and first echo intensity extraction, (4)Estimate canopy NPP and sub-region NPP, (5)Contrast the intensity of first echo with different forest stands.
    Consequently, there are three study stands, Betal nut, Bamboo and Taiwan acacia, in the study. The maximum average penetration rate is 16.08% with Betel nut, and the minimum is 3.49% with Bamboo. Betal nut has the most NPP, 66.36(gC/m2/month), and Bamboo has the least NPP, 52.08 (gC/m2/month), at height 100m and 400m, respectively. At height 600m, the NPP of Betal nut is larger than Taiwan acacia. At height 850m, the NPP of Taiwan acacia is larger than Betal nut. The reasult of intensity is similar with histogram of stands, and the R square of study region at 100m and 400m is over 0.9. The fly height can be calculated by extracted intensity from same stripe, and we use such result to nomalize the value of intensity between two different region at same stripe.

    摘要 ...................................................................................................................I Abstract............................................................................................................. II 誌謝................................................................................................................IV 目錄.................................................................................................................V 圖目錄..........................................................................................................VIII 表目錄.............................................................................................................XI 第一章緒論.....................................................................................................1 1.1 研究動機與背景................................................................................1 1.2 研究目的............................................................................................2 1.3 研究內容與流程................................................................................3 第二章文獻回顧.............................................................................................6 2.1 第一生產力模型(Net Primary Production, NPP) .............................6 2.1.1 氣候生產力模型.....................................................................6 2.1.2 生理生態模型.........................................................................7 2.1.3 光能利用率模型.....................................................................8 2.2 LiDAR(Light Detection and Ranging) .............................................14 2.2.1 空載光達簡介.......................................................................14 2.2.2 LiDAR訊號特性....................................................................16 2.2.3 LiDAR於林地之應用............................................................19 2.3 小結..................................................................................................25 第三章研究方法...........................................................................................26 3.1 試驗區範圍選取..............................................................................28 3.2 光達(LiDAR)資料處理...................................................................28 3.2.1 前處理(動態差分GPS 處理與POS 數據處理) .................29 3.2.2 航帶平差...............................................................................30 3.2.3 點雲分類...............................................................................31 3.2.4 光達資料網格化...................................................................37 3.3 植生區域萃取(物件式分類法) .......................................................38 3.3.1 影像分割(Image segmentation)............................................39 3.3.2 知識庫區塊分類...................................................................44 3.3.3 樹植生區套繪.......................................................................48 3.4 第一生產力(NPP)估算....................................................................49 3.4.1 樹植生區地面點分類分析...................................................52 3.4.2 樹植生區穿透率分析...........................................................53 3.4.3 第一生產力相關參數求取與反演-CASA模型...................55 3.4.4 總第一生產力(NPP)求取與估算.........................................58 3.5 反射強度(Intensity)比較.................................................................59 3.5.1 第一回波萃取.......................................................................59 3.5.2 反射強度統計與相關性.......................................................59 3.5.3 葉面積指數(Leaf Area Index, LAI) .....................................59 第四章研究成果...........................................................................................61 4.1 研究區域..........................................................................................61 4.2 LiDAR資料前處理成果...................................................................63 4.3 植生區萃取及穿透率估算成果......................................................66 4.3.1 影像分割...............................................................................66 4.3.2 知識庫區塊分類...................................................................67 4.3.3 樹植生區穿透率運算結果...................................................71 4.4 第一生產力(NPP)估算成果............................................................76 4.4.1 林相冠層NPP估算成果.......................................................76 4.4.2 穿透層NPP估算成果...........................................................80 4.4.3 試驗區總NPP估算...............................................................81 4.5 林相反射強度比較..........................................................................83 4.5.1 第一回波萃取.......................................................................83 4.5.2 植被種類反射強度相關性...................................................85 4.5.3 雷射強度正規化...................................................................92 4.5.4 雷射反射強度與葉面積指數相關性...................................93 第五章結論與建議.......................................................................................95 5.1 結論..................................................................................................95 5.2 建議..................................................................................................97 參考文獻.........................................................................................................98 自述

    1. 財團法人工業技術研究院，辦理LiDAR測區之高精度及高解析度數值地形測繪、資料庫建置與應用推廣工作案－期中報告，工業技術研究院能源與資源研究所，新竹縣，2005。
    2. 中央氣象局全球資訊網(2008)，農業氣象觀測網月資料，2008年11月05日，取自：http://www.cwb.gov.tw/V6/index.htm。
    3. 王宗明、梁銀麗，植被淨第一性生產力模型研究進展，西北林學院學報，17(2)，PP.25，2002。
    4. 王文俊，認識Fuzzy，台北市，全華科技圖書，1986。
    5. 史天元、何心瑜，數值高程模型及數值覆蓋模型產製品質研究，內政部辦理LiDAR測區之高精度及高解析度數值地形測繪、資料庫建置與應用推廣工作案，PP.129-142，2005。
    6. 朱文泉、陳云浩、徐丹、李京，陸地植被淨初級生產力計算模型研究進展，生態學雜誌，24(3)，PP.296-300，2005。
    7. 朱文泉、潘耀忠、何浩、于德永、扈海波，中國典型植被最大光利用率模擬，科學通報，51(6)，PP.700-706，2006。
    8. 李世華、牛錚、李壁成，植被淨第一性生產力遙感過程模型研究，水土保持研究，12(3)，PP.126-128，2005。
    9. 行政院農委會林務局(2008)，森林永續經營-森林的呼吸，2009年5月10日，取自：http://www.coa.gov.tw/nam/suggest.php?issue=11719
    10. 吳志遠，利用LiDAR資料探討物件式分類法對第一生產力資源參數萃取之研究，國立成功大學資源工程所碩士論文，2008。
    11. 徐歷鵬(2006)，生態系生態學Ecosystem Ecology，2009年03月10日，取自http://www.dyu.edu.tw/~lphsu/htm/ecosystem.htm。
    12. 孫睿、朱啟疆，中國陸地植被淨第一性生產力及季節變化研究，地理學報，55(1)，PP.36-45，2000。
    13. 張小紅，機載機光掃瞄測高數據率波及地物提取，武漢大學大地測量學院測量工程博士論文，2002。
    14. 陳良健、江采薇、張智安，融合光達及空照影像建立三維森林覆蓋模型，內政部辦理LiDAR測區之高精度及高解析度數值地形測繪、資料庫建置與應用推廣工作案，PP.169-178，2005。
    15. 陳建德(2004)，蘭陽溪集水區森林生態系與人為干擾生態系植物碳素淨固定量的研究，2009年07月30日，取自http://www.taibif.org.tw/lanyoung/doc/20.pdf
    16. 曾小平，趙平，饒興權和蔡錫安，鶴山丘陵3種人工林葉面積指數的測定及其季節變化，北京林業大學學報，30(5)，pp.1000-1522，2008。
    17. 彭炳勳，應用空載光達資料推測林木樹高與葉面積指數，屏東科技大學森林所碩士論文，2007。
    18. 經濟部水利署，白河水庫蓄水範圍及保護帶保育計畫，2006。
    19. 廖大牛，森林資源經營學，台北市，國立編譯館，2000。
    20. 鄭鼎耀、王弘基、鄒慶敏、劉正倫，空載光達系統應用不同掃描參數於密植被區穿透率研究，第五屆海峽兩岸測繪發展研討會，2007。
    21. 鄭進烜，董文淵，陳沖和段春香，海子坪天然毛竹林葉面積指數及稈形結構，林業科技開發，23(3)，pp.44-48，2009。
    22. 劉治中，蕭國鑫和李元炎，遙測與資訊結合應用於土地利用分類探討-以水稻田判釋為例，第十八屆測量學術及應用研討會論文集，pp.673-682，1999。
    23. 顏宏宇，LiDAR 直接量測數值地形資料精度分析與應用，國立成功大學地球科學所碩士論文，2005。
    24. Axelsson, P., Processing of laser scanner data – algorithms and applications. ISPRS Journal of Photogrammetry and Remote Sensing, 54(2-3), PP.138-147, 1999.
    25. Baltsavias, E.P., Airborne laser scanning: basic relations and formulas. ISPRS Journal of Photogrammetry and Remote Sensing. , 54(2-3), PP.199-214, 1999.
    26. Daniel, N.M., Donoghue, P. J. Watt, Nicholas J. Cox, jimmy Wilson, Remote sensing of species mixture in conifer plantations using LiDAR height and intensety data, Remote Sensing of Environment, 110, PP.509-522, 2007.
    27. DEFINIENS AG, eCoginition user’s guide. http://www.definiens.com. (accessed 23, Dec, 2003), 2003.
    28. Field C B, Randerson J T, Malmstrom CM, Global net primary production: Combining ecology and remote sensing, Remote Sensing Environ., 51, PP.74-88, 1995.
    29. Hofmann, A.D., Mass, H., and Streilein, A., Knowledge-based building detection based on laser scanner data and topographic map information, International Archives of Photogrammetry and Remote Sensing, Vol.34, Part 3A+B, PP.163-169, 2002.
    30. Juan C. Suárez, Tree counting analysis using eCognition, 2004.
    31. Kaduk J , Heimann M ., A prognostic phenology scheme for global terrestrial carbon cycle models., Clim. Res., 6, PP.1-19, 1996.
    32. Kergoat L ., A model for hydrologic equilibrium of leaf area index on a global scale. , J . Hydro. , PP.212-213, PP.267-286, 1999.
    33. Knorr, W., and M. Heimann, Impact of Drought Stress and Other Factors on Seasonal Land Biosphere CO2, Exchange Studied Through an Atmospheric Tracer Transport Model,, 47, PP.471-489, 1995
    34. Kristian, W. M.. Calibration of Airborne Laser Scanners. Master thesis, Department of Geomatics Engineering, Calgary, Alberta, 2002
    35. Matsushita B., M. Xu, J. Chen, S. Kameyama, M. Tamura., Estimation of regional net primary productivity (NPP) using a process-based ecosystem model: How important is the accuracy of climate data, Ecological Modelling 178, PP.371-388, 2004.
    36. Lieth H F H., Modeling the primary productivity of the world. Neture and Resources, 8 (2), PP.5-10, 1972.
    37. McGuire AD, Melilo J M , Kickilghter D W et al.,Equilibrium responses of global net primary production and carbon storage to doubled atmospheric carbon dioxide., Global Biogeochem. Cyc.11(2), PP.173189, 1997.
    38. Parton W J, Scurlock J MO ,Ojima D S. et al..Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide., Global Biogeochem .Cy.,7, PP.785-890, 1993.
    39. Potter, C., J. Randerson, C. Field, P. Matson, P. Vitousek, H. Mooney, and S. Klooster, Terrestrial ecosystem production-a processs model based on global satellite and surface data, Global Biogeochemical Cycles, 7, PP.811-841,1993
    40. Prince, S., and S. Goward, Global net primary production: a remote sensing approach, Journal of Biogeography, 22, PP.815-835, 1995.
    41. Randall, D., P. Sellers, and J. Berry, A revised land surface parameterization (SiB2) for atmospheric GCMs. Part Ⅲ: the greening of the Colorado State University General Circulation Model, Journal of Climate, 9, PP.738-763, 1996.
    42. Ruimy A, Saugier B., Methodology for the estimation of terrestrial net primary production from remotely sensed data. Journal of Geophysical Research, 97, PP.18515-18521, 1994.
    43. Ruimy, A., F. Dedieu, and B. Saugier, TURC: a diagnostic model of continental gross primary productivety and net primary productivety., Global Biogeochemical Cycles, 10, PP.269-286, 1996
    44. Running S W, H unt E R., Generailzation of a forest ecosystem process model for other biomes, BIOME-BGC ,and an application for global-scale models[A]. In : Ehleringer JR ,eds . Scailng Physiological Processes :Leaf to Globe[C].San Diego, CA, Academic Press, PP.141-158, 1993.
    45. Sithole, G. and G. Vosselman. Experimental comparison of filter algorithms forbare-Earth extraction from airborne laser scanning point clouds, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 59, P PP.85-101, 2004.
    46. Sooyoung Kim, Tree species differentiation using intensity data derived from leaf-on and leaf-off airborne laser scanner data. Remote Sensing of Environment, 113, pp.1575-1586, 2009.
    47. St-Onge, B. A. and N. Achaichia.. Measuring forest canopy height using a combination of LIDAR and aerial photography data, Workshop on Land Surface Mapping and Characterization Using Laser Altimetry, Annapolis, Maryland, USA,2001.
    48. Terrasolid , TerrScan User Guide (18.11.2004), Terrasolid , 2004a.
    49. Terrasolid, TerrMatch User Guide , Terrasolid, 2004b.
    50. Uchijima Z, Seino H., An agroclimating net primary productivity of natural vegetation., J Agric. Res. Q. , 214, PP.244-250, 1985.
    51. Warnant P, Francois L, Strivay D. et al., CARAIB: A global model of terrestrial biological productivity, Global Biogeochem. Cyc., 8, PP. 255-270, 1994.
    52. Wolfgang Cramer et al. Net Primary Productivity Model Intercomparison Activity (NPP), IGBP/GAIM Report Series , Report 5, 1995.

    下載圖示 校內：立即公開
    校外：2009-08-20公開
    QR CODE