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系統識別號 U0026-0812200912114122
論文名稱(中文) 應用衛星遙測影像進行大肚台地紅土範圍界定與中央山脈裸岩區之岩性分析
論文名稱(英文) Applications of satellite remote sensing imagery on mapping the laterite in DaDu Plateau and lithology analysis in outcrop areas of Central Mountain Range
校院名稱 成功大學
系所名稱(中) 地球科學系碩博士班
系所名稱(英) Department of Earth Sciences
學年度 94
學期 2
出版年 95
研究生(中文) 張維恕
研究生(英文) Wei-Shu Chang
學號 l4693406
學位類別 碩士
語文別 中文
論文頁數 82頁
口試委員 口試委員-謝璧妃
口試委員-王驥魁
口試委員-林慶偉
指導教授-劉正千
召集委員-楊純明
中文關鍵字 大肚台地  多光譜遙測影像  中央山脈  高光譜遙測影像  紅土  岩性 
英文關鍵字 lithology  Central Mountain Range  DaDu plateau  mutispectral imagery  hyperspectral imagery  laterite 
學科別分類
中文摘要 岩性分佈資料對於地質災害評估或礦產資源探勘均扮演著非常重要的角色。傳統地面地質調查工作之進行,不僅耗費大量人力、時間與金錢,在交通不便之處,資料之獲取尤其困難。若能善加利用衛星遙測技術之優勢,在大範圍獲取土壤與岩性分佈資料之應用上將有莫大潛力。從1980年代初期便開始有相關研究藉由分析空載高光譜影像,利用岩性之反射光譜特徵差異來進行岩性製圖,是一項發展成熟且廣泛應用之技術。惟台灣地區空載高光譜遙測影像來源貧乏,因此星載多、高光譜遙測影像,例如ASTER與Hyperion影像是現階段較理想之選擇。然而相同岩性或土壤於不同地區所包含之礦物成分也有所差異,現有國外研究單位所建立之岩性與土壤之光譜資料庫無法完全適用於台灣地區,故欲於台灣地區進行土壤或岩性判釋,須建立台灣地區岩性及土壤之電磁反射光譜資料庫,再進一步瞭解其不同成分與礦物組成。本研究分別以Rigaku 4056A2 B2701N型X光繞射儀與GER-2600手持式輻射光譜儀,量測紅土與不同岩石標本之礦物組成及電磁反射光譜資訊。再運用包括正射糾正、去條紋、大氣校正、及各種影像處理分類方法,分析ASTER多光譜與Hyperion高光譜遙測影像,完成了台灣地區大肚台地紅土分佈範圍之界定,以及中央山脈裸岩區岩性之判釋工作。
研究結果顯示,即使與衛星影像拍攝的時間不同,利用現地量測的高光譜反射光譜資訊仍可以有效去除ASTER影像中大氣效應,還原紅土反射光譜應具有的吸收特徵及整體反射光譜分佈趨勢。使用福爾摩沙衛星二號兩米彩色融合影像間接查核大肚台地紅土層範圍界定之結果顯示,光譜角度製圖法(SAM)會出現將紅色建物誤判為紅土之情形,而使用紅土光譜特徵指標法則可避免誤判,提高紅土範圍界定之正確性。Hyperion影像因本身具有水氣影響波段之詳細資訊,故可以直接使用FLAASH大氣校正模組進行校正,其結果與實際標本光譜相當一致。另外藉由動差擬合法可以大幅改善Hyperion影像因感測器校正異常產生垂直條紋現象,提供更多光譜資訊於岩性分析之應用。使用Kruse所提出之一系列高光譜影像分析標準程序可對中央山脈裸岩區域進行細部之岩性分析,提供未來進行大規模岩性製圖查核、比對所需之定點之岩性分佈資料。


英文摘要 The information of lithology and mineral composition plays a significant role in geohazard assessment and mineral exploration. In those unaccessable areas, however, it is not practical to employ the the traditional approach of geological survey to collect the information, in terms of time, money and labor. With the advantages of romote sensing, it would be of great potential to acquire the synoptic view of soil and rock from the airborne or spaceborne platform. The hyperspectral imagery obtained from the airborne platform had been applied in lithology mapping since 1980s. However, the airborne hyperspectral imagery is currently not available in Taiwan area. The mutispectral and hyperspectral imagery obtained from the spaceborne platform, such as ASTER and Hyperion imagery is therefore a better choice for the time being. The similar rock or soil might be comprised of very different mineral components in different area, resulting in a fact that the existing spectral libraries investigated and compiled in the past might not be useable in Taiwan area. This research measures the mineral component of various lithological samples using Rigaku 4056A2 B2701N type X-ray diffraction spectrometry and the spectral reflectances using hyperspectral spectroradiometer GER-2600. Through a series of image processing, including orthorectification, destriping, atmospheric correction, and various image classification techniques, this research successfully apply the ASTER and Hyperion imagery to mapping the laterite in DaDu plateau and classifying the lithology in outcrop areas of Central Mountain Range.
Results of this research indicate that the atmospheric effect on ASTER imagery can be removed and the spectral characteristics of laterite can be retrieved by measuring the in situ reflectance, even if the measurement is not made at the same time as the satellite imagery was taken. Validating with the high-spatial-resolution imagery taken by FORMOSAT-2, the laterite spectral feature index method gives a better classification than the spectral angle mapper method in mapping the laterite in DaDu plateau. As to the Hyperion hyperspectral imagery that covers the spectral bands influenced by water vapor, this research is able to employ the radiative-transfer-based model, FLAASH, to correct the atmospheric effect and retrieve the surface reflectance. The results of atmospheric correction were verified against the reflected spectra of samples. In addition, this research applies the moment matching method to process the stripped imagery due to variations in Hyperion sensor calibration. As a result, more spectral information for lithology classification can be restored. A series of hyperspectral image analysis processing described by Kruse is employed to estimate the lithological composition of each pixel in outcrop of Central Mountain Range. This research provides lithological information at various outcrop areas, which could be useful for verifying the accuracy of lithology mapping in Central Mountain Range in the future.


論文目次 目錄
摘要 i
Abstract ii
誌謝 iv
目錄 v
圖目錄 viii
表目錄 xi
第1章 緒論 1
1.1 研究動機 1
1.2 研究目的 5
1.3 論文架構 5
第2章 文獻回顧 7
2.1 礦物、岩性光譜 7
2.2 多、高光譜遙測影像於岩性製圖 11
2.3 小結 14
第3章 研究策略 15
3.1 研究步驟 15
3.1.1 使用ASTER影像進行大肚台地紅土範圍界定 15
3.1.2 使用Hyperion影像進行中央山脈裸岩區岩性分析 16
3.2 研究區域 17
3.2.1 大肚台地 17
3.2.2 中央山脈 19
3.3 遙測影像 21
3.3.1 ASTER多光譜衛星遙測影像 21
3.3.2 Hyperion高光譜衛星遙測影像 25
第4章 研究方法 28
4.1 標本XRD分析及電磁反射光譜量測 28
4.1.1 採集地點 28
4.1.2 X-光粉末繞射(XRD)礦物組成分析 31
4.1.3 電磁反射光譜量測 34
4.2 影像分析 39
4.2.1 ASTER影像之正射糾正 39
4.2.2 Hyperion影像去條紋處理 39
4.2.3 大氣校正 40
4.2.4 ASTER多光譜影像分析 43
4.2.5 Hyperion高光譜影像分析 46
第5章 研究結果 49
5.1 ASTER多光譜衛星遙測影像於大肚台地紅土範圍界定 49
5.1.1 紅土特性與光譜特徵 49
5.1.2 ASTER衛星遙測影像產製DTM及進行正射糾正 50
5.1.3 大氣校正 51
5.1.4 SAM分類結果 53
5.1.5 紅土光譜特徵指標法結果 55
5.1.6 討論 57
5.2 HYPERION高光譜衛星遙測影像於中央山脈裸岩區岩性分析 62
5.2.1 去條紋處理(Destriping) 62
5.2.2 大氣校正 64
5.2.3 高光譜分析 67
5.2.4 討論 69
第6章 結論與建議 71
6.1 結論 71
6.2 建議 72
參考文獻 74


圖目錄

圖 1.1 高光譜遙測影像記錄不同物體之光譜曲線[Green et al., 1998]。 3
圖 1.2 論文架構。 6
圖 2.1 礦物之光譜特徵(黑色區域為對應之吸收波段)[Hunt, 1977]。 8
圖 2.2 含鐵礦物之反射光譜。三種礦物在0.87 μm皆有吸收峰[Hunt and Ashley, 1979]。 9
圖 2.3 含水礦物之反射光譜。三種礦物在1.4 μm與1.9 μm皆有吸收峰[Hunt, 1980]。 10
圖 2.4 黏土礦物之反射光譜[Rowan et al., 1983]。 10
圖 2.5 碳酸鹽礦物反射光譜。在2.35 μm有特徵吸收峰[Whitney et al., 1983]。 11
圖 2.6 高光譜影像分析標準程序[Kruse, 1998]。 13
圖 3.1 使用ASTER影像進行紅土範圍界定之流程。 15
圖 3.2 使用Hyperion影像進行中央山脈裸岩區岩性分析之流程。 16
圖 3.3 大肚丘陵南段頭嵙山層頂部以下約200公尺厚的地層柱狀圖[何信昌與陳勉銘,2000]。 17
圖 3.3 大肚台地紅土判釋研究區(Date: 2001/03/06; R: band 3, G: band 2, B: band 1)。 18
圖 3.4 中央山脈研究區域之五十萬分之一地質圖[經濟部中央地質調查所地調所,2000]。 20
圖 3.5 Terra衛星軌道(http://terra.nasa.gov/)。 22
圖 3.6 ASTER感測儀各波段分佈圖(http://asterweb.jpl.nasa.gov/index.asp)。 23
圖 3.7 ASTER與Landsat波段分佈比較(http://asterweb.jpl.nasa.gov/index.asp)。 23
圖 3.8 VNIR次系統包含一個向下感測儀(3N)及向後感測儀(3B)(http://asterweb.jpl.nasa.gov/index.asp)。 23
圖 3.9 ASTER L1B影像(Date: 2001/03/06; R: band 3, G: band 2, B: band 1)。 24
圖 3.10 EO-1衛星與Landsat 7衛星[Pearlman et al., 2000]。 26
圖 3.11 Hyperion Level 1A研究區域標準假彩色影像,拍攝時間為2006/3/12。 27
圖 4.1 第一採集點,★為採集點;●為地標(高雄縣寶來附近)。 29
圖 4.2 第二採集點,★為採集點;●為地標(中央山脈研究區附近)。 30
圖 4.3 Rigaku 4056A2 B2701N型X光繞射儀。 32
圖 4.4 變質石灰岩X-ray繞射圖。 33
圖 4.5 量測標準灰卡反射光譜強度。上圖為量測實況,下圖為系統顯示畫面。 35
圖 4.6 量測樣本反射光譜強度。上圖為量測實況,下圖為系統顯示畫面。 36
圖 4.7 採集之岩石標本電磁反射光譜。 37
圖 4.7 採集之岩石標本電磁反射光譜(續)。 38
圖 4.8 ASTER影像大氣校正流程圖(修改自Rowan and Mars, 2003)。 41
圖 4.9 光譜向量夾角示意圖。 44
圖 4.10 RBD示意圖[Crowley et al., 1989]。 45
圖 4.11 Hughes現象[Hughes, 1968][徐百輝與曾義星,2000]。 47
圖 4.12 MTMF示意圖[Kruse et al., 2000]。 48
圖 5.1 現地量測紅土高光譜反射率(時間:2006/4/21,位置:120.6E, 24.2N)。 49
圖 5.2 紅土現地反射光譜(GER2600所量測之高光譜反射率及根據ASTER九個波段重新取樣後所得之多光譜反射率)。 50
圖 5.3 ASTER正射影像套疊道路圖層(Band 3)。 51
圖 5.4 ASTER大氣校正產品之精度評估。 52
圖 5.5 大氣校正前後影像紅土光譜及現地紅土光譜差異。 53
圖 5.6 大肚台地紅土分佈判釋(光譜角度製圖法)。 54
圖 5.7 大肚台地紅土分佈判釋(紅土光譜特徵指標法)。 56
圖 5.8 影像誤判之光譜與實際紅土光譜比對。 57
圖 5.9 大肚台地研究區域內選取之三個區域。 59
圖 5.10 區域1,(a) SAM及(b)紅土光譜特徵指標法紅土判釋結果、(c)福衛兩米彩色融合影像自然光及(d)標準假彩色。 60
圖 5.11 區域2,(a) SAM、(b)紅土光譜特徵指標法紅土判釋結果、(c)福衛兩米彩色融合影像自然光及(d)標準假彩色。 60
圖 5.12 區域3,(a) SAM、(b)紅土光譜特徵指標法紅土判釋結果、(c)福衛兩米彩色融合影像自然光及(d)標準假彩色。 61
圖 5.13 Hyperion影像去條紋處理前(左)後(右)影像(band 205)。 63
圖 5.14 Hyperion影像去條紋處理前後每一行之平均灰度值比較(band 205)。 63
圖 5.15 FLAASH基本參數設定。 65
圖 5.16 FLAASH進階設定。 65
圖 5.17 標準自然光光譜透射率曲線(修改自Schowengerdt, 1997)。 66
圖 5.18 標本光譜與大氣校正(FLAASH)前後之影像上光譜比對。 66
圖 5.19 成份豐度合成假彩色(R: 大理岩,G: 綠色片岩,B: 變質砂岩)。 68
圖 5.20 四主要裸岩區位置及其成份豐度合成假彩色。 69
圖 5.21 Hyperion與AVIRIS高光譜遙測影像之SNR比較[Kruse et al., 2003]。 70


表目錄
表 2.1 多、高光譜遙測影像應用於礦物、岩性判釋之方法統整 14
表 3.1 ASTER感測儀重要諸元(http://asterweb.jpl.nasa.gov/index.asp) 22
表 3.2 EO-1之三個感測儀重要諸元[Pearlman et al., 2001; Ungar et al., 2003] 26
表 4.1 岩性標本XRD分析結果 33
表 5.1 紅土光譜特徵指標說明 55

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