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系統識別號 U0026-0812200911560950
論文名稱(中文) 福爾摩沙衛星二號遙測影像應用於河川砂石資源開採區域判釋
論文名稱(英文) Application of FORMOSAT-2 Remote Sensing Imagery on Interpreting the Mining Area of Gravel Resources in the Rivers
校院名稱 成功大學
系所名稱(中) 水利及海洋工程學系碩博士班
系所名稱(英) Department of Hydraulics & Ocean Engineering
學年度 94
學期 2
出版年 95
研究生(中文) 吳教安
研究生(英文) Chiao-An Wu
學號 n8693413
學位類別 碩士
語文別 中文
論文頁數 97頁
口試委員 口試委員-陳怡睿
口試委員-吳岸明
指導教授-謝正倫
指導教授-劉正千
口試委員-王驥魁
中文關鍵字 指數合成假彩色影像  影像判釋法  梯度影像法  正規化砂石指數  時序列分析法  影像相減法  福衛二號影像自動處理系統  河川砂石資源開採區域  遙測影像  福爾摩沙衛星二號  變異監測 
英文關鍵字 image interpretation  index-based false color composite  gradient image  image differencing  mining area of gravel resources in the rivers  FORMOSAT-2  remote sensing image  change detection  FORMOSAT-2 automatic image processing system  time-series analysis  Normalized Difference Gravel Index 
學科別分類
中文摘要   台灣地處於亞洲大陸板塊和菲律賓板塊碰撞擠壓交接之處,山脈高聳且岩層破碎,河川流域短小而水流急湍,再加上颱風、地震頻繁以及亞熱帶氣候豐沛的雨量,使得台灣成為全世界河川高侵蝕率的地區之一。大量的砂石在河床上堆積,往往在暴雨後因泥砂淤積而引起水災、潰堤及橋樑沖毀等嚴重災害。因此政府在河川相關之整治計畫中,投入大量的人力和物力進行河道疏濬清淤工程,並在河川旁興建堤防,以提升河防安全。但另一方面,這些河床上的砂石資源都是建築材料的理想來源,所以有些砂石業者會在河床上過度開採,嚴重危害了河床和其上防洪設施的結構安全,亦影響人民生命財產安全。為了避免因過度開採砂石而導致重大災情,現行河川砂石資源開採管理策略主要是派遣河川流域巡防人員定期巡視各河川流域,需要相當多的人力。因此有效的監測河川砂石資源開採區域是臺灣地區河川流域管理中最緊急且重要的任務之一。
  衛星遙測技術具有長時間、大範圍拍攝的特性,在監測河川砂石資源開採區域之應用上極具潛力。福爾摩沙衛星二號(福衛二號)是我國自主控制的第二枚遙測衛星,具有每日再訪的高時間解析度與兩米的高空間解析度。國立成功大學防災研究中心不僅為國家太空中心所簽訂全世界第一個福衛二號影像應用推廣中心,擁有台灣地區所有的福衛二號影像,更已針對福衛二號影像特性發展了一套包括錯位修正、正射糾正、大氣校正及彩色融合等功能的「福衛二號影像自動處理系統」,可以快速而自動地產製高品質的彩色融合正射影像,是監測河川砂石資源開採區域的理想資料來源。本研究在成大防災研究中心的支持之下,應用大量的福衛二號遙測影像進行砂石資源開採區域變異分析之相關研究。
  本研究使用包含曾文溪、陳有蘭溪和荖濃溪三大河川流域共計三十幅不同時期的福衛二號遙測影像,並配合無人遙控旋翼機低空拍攝所得之影像作為地面真實資料,又根據河川砂石資源開採區域之特徵,共提出了九種應用福衛二號遙測影像進行砂石資源開採區域變異分析之方法。本研究結果顯示所提出的九種方法在曾文溪研究區域的判釋結果均非常理想,應用這些方法進行變異分析之準確性亦得到驗證。在陳有蘭溪和荖濃溪研究區域則選擇四種具有代表性的影像判釋法,包括本研究創新之「正規化砂石指數(Normalized Difference Gravel Index, NDGI)」,再加上「NDGI影像相減法及時序列分析法」、「梯度影像法」和「指數合成假彩色影像」,亦驗證本研究所使用四種影像判釋法之準確性。靈巧結合這四種影像判釋法,可以應用福衛二號遙測影像快速而準確地圈繪出河川砂石資源開採區域。
  現階段福衛二號遙測影像之處理雖受到台灣地區數值地形模型解析度不足(40米)及缺乏現地地物反射頻譜資料等因素之限制,但本研究之結果顯示所建立之「河川砂石資源開採區域影像判釋法」,仍可以快速而準確地對不同時期影像進行大範圍河川砂石資源開採區域監測工作,以提供河川流域相關管理人員,利用影像變異分析後的結果與公告法定範圍進行比對圈繪,針對公告法定範圍外有變異區域進行現地考核,以確認是否為自然變化,抑或是人為破壞所造成的,便可大量減少目前河川巡邏所需之人力資源。應用「河川砂石資源開採區域影像判釋法」進行監測工作時,時序列影像時間間隔愈短愈好,然而目前福衛二號取像頻率不均且平均取像間隔亦往往超過一週,但未來配合福衛二號取像排程規劃,將可達成有效監測河川砂石資源開採區域的目標。


英文摘要  Taiwan is located in the center of the East-Asian island arc formed by the slow collision of the Asian continental plate and the Philippine plate. The lofty mountains, broken terrain and frequent earthquakes, together with the heavy rainfall during the raining and typhoon season, makes Taiwan a region that has one of the highest erosion rates in the world. Typical rivers in Taiwan are short with small drainage basins and steep with rapid flows. A tremendous amount of gravel is washed into the rivers and heavily deposited on the riverbed every year. As a result, serious disasters such as flood, the protecting embankment broke, and the bridge destroyed by rush of water after waterspout are frequently reported. To manage the watershed and prevent flooding in the raining season, Taiwan government spends a considerable amount of manpower and resource to fix the course of river by dredging gravel and building embankments along the rivers. Since the excavated gravel is an ideal source of construction materials, some gravel dealers might overmine the gravel on riverbed, which inevitably modifies the topography of riverbed and changes the pattern of river flow. As a result, an unpredictable transportation of sediment frequently arises to reach a new status of balance. This could have a devastating impact on piers or other structures rooted in the riverbed. The general strategy to prevent overmining is to send patrolmen, which requires a considerable amount of manpower and is not very effective in the past. Therefore, effectively monitoring the mining area of gravel resources in the rivers (MAGRR) is one of the most urgent tasks to be accomplished in the management of rivers and watersheds in Taiwan.
 The characteristics of a long-term and synoptic observation give the satellite remote sensing technique great potential in monitoring MAGRR. FORMOSAT-2 is the second satellite owned and operated by the National Space Organization (NSPO) of Taiwan. Based on the cooperative agreement between the Disaster Prevention Research Centre (DPRC) of National Cheng Kung University and NSPO, DPRC serves as the first image application and distribution centre (IADC) in the world that receives, processes and archives FORMOSAT-2 imagery on a daily basis. After more than two years of operation, DPRC has successfully applied FORMOSAT-2 imagery to disaster preparedness, rescue and environment monitoring, such as in the aftermath the South Asia tsunami. DPRC has also developed a FORMOSAT-2 automatic image processing system (F-2 AIPS), including band-to-band registration, orthorectification, atmosphere calibration and data fusion. Fully supported by DPRC, this research employs the F-2 AIPS to process a large amount of FORMOSAT-2 images, and then applies these images to develop an effective way to monitor MAGRR.
 This research uses a total of thirty FORMOSAT-2 images of Tseng-Wen River, Chen-You-Lan River and Lao-Nong River, which were taken at different periods of time. The ground truths were collected by the unmanned helicopter flying at low altitude. Based on the characteristics of MAGRR, a total of nine approaches were employed to analyze the changing of MAGRR on FORMOSAT-2 images. The results show that all approachs are able to detect the changing of MAGRR to a satisfied level of accuracy. This research proposes a new index, namely Normalized Difference Gravel Index (NDGI), to indicate the possibility of MAGRR. This research also recommends four of those nine approaches to effectively delineate the MAGRR from FORMOSAT-2 images, including NDGI image differencing, NDGI time-series analysis, gradient image, and index-based false color composite. Carefully combining those four approaches enables a fast and accurate delineation of MAGRR from FORMOSAT-2 images.
 In spite of the limitations in the coarse resolution of Digital Terrain Model (40m) in Tiawan area and the lack of ground reflection spectra in the vicinity of study sites, the image interpretation approaches proposed by this research enables a fast and accurate delineation of MAGRR from FORMOSAT-2 images. This information can be quickly compared to the MAGRR with permission to identify the suspecious areas. This would save the patrolmen a lot of time and effort to manage the watershed. Ideally, the frequency of monitoring MAGRR should be kept as small as possible. The current sampling frequency of FORMOSAT-2, however, is not only fluctuated but usually much longer than a week. To achieve an effective monitoring of MAGRR, the scheduling scheme of taking FORMOSAT-2 images needs to be further optimized in the future.

論文目次 目錄

摘要 I
Abstract III
誌謝 VI
目錄 VIII
圖目錄 XII
表目錄 XV
第1章 緒論 1
 1-1 研究背景 1
 1-2 研究目的 2
 1-3 文獻回顧 2
  1-3-1 砂石開採 2
  1-3-2 衛星遙測 5
  1-3-3 影像處理 5
  1-3-4 變異監測 8
 1-4 研究架構 10
第2章 研究方法 12
 2-1 研究資料 12
  2-1-1 衛星遙測影像 12
  2-1-2 地面真實資料 16
 2-2 福衛二號影像自動處理系統 18
  2-2-1 錯位修正 18
  2-2-2 正射糾正 21
  2-2-3 大氣校正 22
  2-2-4 彩色融合 23
 2-3 河川砂石資源開採區域影像判釋法 24
  2-3-1 正規化差異植生指數(NDVI) 25
  2-3-2 正規化差異水指數(NDWI) 25
  2-3-3 近紅外光(NIR) 26
  2-3-4 梯度影像法 26
  2-3-5 正規化差異砂石指數(NDGI) 27
  2-3-6 指數合成假彩色影像 27
  2-3-7 標準假彩色影像 28
  2-3-8 視覺說明法 28
  2-3-9 影像相減法 28
  2-3-10 小結 29
第3章 變異分析與監測應用 30
 3-1 曾文溪河川砂石開採區域監測 30
  3-1-1 監測背景 30
  3-1-2 監測資料 30
  3-1-3 監測結果 38
  3-1-4 討論 50
 3-2 陳有蘭溪河川砂石開採區域監測 51
  3-2-1 監測背景 51
  3-2-2 監測資料 51
  3-2-3 監測結果 57
  3-2-4 討論 61
 3-3 荖濃溪河川砂石開採區域監測 62
  3-3-1 監測背景 62
  3-3-2 監測資料 62
  3-3-3 監測結果 69
  3-3-4 討論 76
 3-4 監測河川砂石資源開採區域之標準作業程序 76
第4章 結論與建議 80
 4-1 結論 80
 4-2 建議 81
參考文獻 84
附錄A 影像處理軟體 89
附錄B 小波理論 90
自述 96

圖目錄

圖 1-1 研究架構 11
圖 2-1 福爾摩沙衛星二號 14
圖 2-2 無人遙控旋翼機 17
圖 2-3 Level-2 影像不均勻錯位 20
圖 2-4 Level-2 影像錯位修正 21
圖 2-5 正射糾正步驟 22
圖 2-6 輻射校正例子 23
圖 2-7 彩色融合SSIM 例子 24
圖 3-1 曾文溪時序列福衛二號影像 34
圖 3-2 曾文溪衛星影像相關位置及現地空照圖 35
圖 3-3 曾文二號橋堤段時序列變化情形 36
圖 3-4 北勢洲橋堤段時序列變化情形 37
圖 3-5 NDVI 影像 39
圖 3-6 局部放大之NDVI 影像 40
圖 3-7 NDWI 影像 41
圖 3-8 NIR 影像 42
圖 3-9 多解析力梯度影像(94/4/18) 43
圖 3-10 NDGI 影像 44
圖 3-11 指數合成假彩色影像 45
圖 3-12 標準假彩色影像 46
圖 3-13 視覺說明法(紅:93/9/30、綠:93/10/12、藍:93/11/8) 47
圖 3-14 94/4/18 與93/12/17 之影像相減所得之結果 48
圖 3-15 曾文二號橋堤段砂石開採區 49
圖 3-16 陳有蘭溪時序列福衛二號影像 53
圖 3-17 陳有蘭溪衛星影像相關位置(93/7/12)及現地空照圖(93/7/30) 54
圖 3-18 陳有蘭溪郡坑溪匯流處時序列變化情形 56
圖 3-19 NDGI 影像 57
圖 3-20 94/7/10 與93/12/6 之NDGI 影像相減所得之結果 58
圖 3-21 陳有蘭溪砂石開採區 59
圖 3-22 梯度影像(94/7/10) 60
圖 3-23 指數合成假彩色影像 61
圖 3-24 荖濃溪時序列福衛二號影像 65
圖 3-25 荖濃溪衛星影像相關位置(95/4/19)及現地照片(95/5/25) 66
圖 3-26 六龜大橋時序列變化情形 67
圖 3-27 三友橋旁時序列變化情形 68
圖 3-28 濁口溪匯流時序列變化情形 69
圖 3-29 NDGI 影像 71
圖 3-30 95/4/19 與94/12/24 之NDGI 影像相減所得之結果 72
圖 3-31 三友橋旁砂石開採區 73
圖 3-32 梯度影像G3 (95/4/19) 74
圖 3-33 指數合成假彩色影像 75
圖 3-34 變異監測之操作介面 79
圖 3-35 標準作業程序 79
圖 4-1 福衛二號在台灣地區取像的時間解析度格網(單位:天) 83
圖 B-1 Vj⊕Oj=Vj+1 之示意圖 91
圖 B-2 訊號的分解與重建示意圖 93
圖 B-3 二維離散小波分解例子 93
圖 B-4 Haar小波的父函數φ(左)與母函數ψ(右) 94

表目錄

表 1-1 砂石開採相關報導 4
表 2-1 各個衛星基本資料 13
表 2-2 福衛二號基本資料 15
表 2-3 無人遙控旋翼機及2.4Ghz 無線影像傳送器基本資料 17
表 2-4 河川砂石資源開採區域特徵與影像判釋法 24
表 3-1 曾文溪研究區之研究資料 31
表 3-2 陳有蘭溪研究區之研究資料 51
表 3-3 荖濃溪研究區之研究資料 62
參考文獻 1. 洪如江,初等工程地質學大綱。財團法人地工技術研究發展基金會,台北,2001。

2. 國家太空中心,http://www.nspo.gov.tw/,2006。

3. 經濟部水利暑,http://www.wra.gov.tw/,2004。

4. 劉正千,運用福衛二號進行定點監控之影像處理,2005 年衛星遙測於地質環境與災害應用國際研討會,146-156,2005。

5. Bell, W. B., Devarajan, V. and Apollo, S. J., Analysis of area-based image matching under perspective distortion for a planar object model. Journal of Electronic Imaging, 8(1), 112-125, 1999.

6. Campbell, J. B., Introduction to remote sensing, 3th edition, Taylor & Francis, London, 2002.

7. Conel, J. E., Green, R. O., Vane, G., Bruegge, C. J., Alley, R. E. and Curtiss, B. J., Airborne imaging spectrometer-2 - Radiometric spectral characteristics and comparison of ways to compensate for the atmosphere. In Proceedings, SPIE, 384, 140-157, 1987.

8. Crippen, R. E., Measurements of subresolution terrain displacements using SPOT panchromatic imagery. Episodes, 15, 56-61, 1992.

9. Dadson, S. J., Hovius, N., Chen, H., Dade, W. B., Hsieh, M. L., Willett, S. D., Hu, J. C., Horng, M. J., Chen, M. C., Stark, C. P., Lague, D. and Lin, J. C., Links between erosion, runoff variability and seismicity in the Taiwan rogen. Nature, 426, 648-651, 2003.

10. Dai, X. and Khorram, S., A feature-based image registration algorithm using improvedchain-code representation combined with invariant moments. IEEE Transactions on Geoscience and Remote Sensing, 37(5), 2351-2362, 1999.

11. De Jong, S. and Van der Meer, F., Remote Sensing Image Analysis: 85 Including the Spatial Domain. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2004.

12. ERSDAC, http://www.ersdac.or.jp/todayData/EDS/00.1/pict_e.html, 2005.

13. Gillespie, A. R., Kahle, A. B. and Walker, R. E., Color enhancement of highly correlated images: II. Channel ratio and chromaticity transformation techniques. Remote Sensing of Environment, 22, 343-365, 1987.

14. Haydan, R., Dalke, G. W., Henkel, J. and Bare, J. E., Applications of the IHS colour transform to the processing of multisensor data and image enhancement. International Symposium on Remote Sensing of Arid and Semi-arid and Lands, Cairo, Egypt, 599-616, 1982.

15. Kruse, F. A., Use of Airborne Imaging Spectrometer data to map minerals associated with hydrothermally altered rocks in the northern Grapevine Mountains, Nevada and California. Remote Sensing of Environment, 24(1), 31-51, 1988.

16. Kruse, F. A., Raines, G. L., Watson, K., Analytical techniques for extracting geologic information from multichannel airborne spectroradiometer and airborne imaging spectrometer data. International Symposium on Remote Sensing of Environment, Thematic Conference on Remote Sensing for Exploration Geology, 4th, Environmental Research Institute of Michigan, 309-324, 1985.

17. Kruse, F. A., Kierein-Young, K. S. and Boardman, J. W., Mineral mapping at Cuprite, Nevada with a 63 channel imaging spectrometer. Photogrammetric Engineering and Remote Sensing, 56(1), 83-92, 1990.

18. Lambin, E. F. and Strahler, A. H., Indicators of land-cover change for changevector analysis in multitemporal space at coarse spatial scales. International Journal of Remote Sensing, 15, 2099-2119, 1994.

19. Lewis, J. P., Fast normalized cross-correlation. Fast template matching, 120-123, 1995.

20. Lillesand, T. M., Kiefer, R. W. and Chipman, J. W., Remote sensing and image interpretation, 5th edition edn, John Wiley & Sons, 2004.

21. Liu, C.-C., Processing of FORMOSAT-2 daily revisit imagery for site surveillance. IEEE Transactions on Geoscience and Remote Sensing, (accepted), 2006.

22. Liu, C.-C., Processing of FORMOSAT-2 imagery for site surveillance, The 26th Asian Conference on Remote Sensing, Hanoi, Vietnam, 2005.

23. Liu, C., Wu, S.-C., Hwang, F.-T., Wu, A.-M. and Chen, H., Radiometric and geometric calibration of ROCSAT-2 image. The 25th Asian conference on remote sensing,Chiang Mai, Thailand, 465-470, 2004.

24. Liu, C.-C., Liu, J.-G., Lin, C.-W., Wu, A.-M., Liu, S.-H. and Shieh, C.-L., Image processing of FORMOSAT-2 data for monitoring South Asia tsunami. International Journal of Remote Sensing, accepted, 2005a.

25. Liu, C.-C., Wu, C.-A., Shieh, M.-L., Liu, J.-G., Lin, C.-W. and Shieh, C.-L., Monitoring the illegal quarry mining of gravel on the riverbed using daily revisit FORMOSAT-2 imagery. IGARSS '05, Seoul, Korea, 3, 1777-1780, 2005b.

26. Liu, J. G., Smoothing filter based intensity modulation: a spectral preserve image fusion technique for improving spatial details. International Journal of Remote Sensing, 21(18), 3461-3472, 2000.

27. Liu, J. G. and Ma, J., Imageodsey on MPI & GRID for co-seismic shift study using satellite optical imagery. The UK e-Science All Hands Meeting 2004, 232-239, 2004.

28. Lu, D., Mausel, P., Brondizio, E. and Moran, E., Change detection techniques. International Journal of Remote Sensing, 25, 2365-2407, 2004.

29. MacLeod, R. D. and Congalton, R. G., A quantitative comparison of change detection algorithms for monitoring eelgrass from remotely sensed data. Photogrammetric Engineering and Remote Sensing, 64, 207-216, 1998.

30. McFeeters, S. K., The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17 (7), 1425-1432, 1996.

31. Mallat, S. G., A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. Pattern Anal. Machine Intell, 11, 674-693, 1989.

32. Prakash, A. and Gupta, R. P., Land-use mapping and change detection in a coal mining area—a case study in the Jharia coalfield, India. International Journal of Remote Sensing, 19, 391–410, 1998.

33. Roberts, D. A., Yamaguchi, Y. and Lyon, R. J. P., Calibration of Airborne Imaging Spectrometer data to percent reflectance using field measurements. The 19th International Symposium on Remote Sensing of Environment, 679–688, 1985.

34. Roberts, D. A., Yamaguchi, Y. and Lyon, R. J. P., Comparison of various techniques for calibration of AIS data. The 2nd Airborne Imaging Spectrometer Data Analysis workshop, Jet Propulsion Laboratory, Pasadena, CA, 21-30, 1986.

35. Shih, M.-Y. and Tseng, D.-C., A wavelet-based multiresolution edge detection and tracking. Image and Vision Computing, 23, 441-451, 2005.

36. Singh, A., Digital change detection techniques using remotely sensed data. International Journal of Remote Sensing, 10, 989–1003, 1989.

37. Vane, G. and Goetz, A. F. H., Introduction to the proceedings of the Airborne Imaging Spectrometer (AIS) data analysis workshop. The Airborne Imaging Spectrometer Data Analysis Workshop, Jet Propulsion 88
Laboratory, Pasadena, CA, 1-21, 1985.

38. Goetz, A. F. H. and Srivastava, V., Mineralogical mapping in the Cuprite Mining District, Nevada. The Airborne Imaging Spectrometer Data Analysis Workshop, Jet Propulsion Laboratory, Pasadena, CA, 22-31.
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