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研究生:許華宇
研究生(外文):Hua-Yu Hsu
論文名稱:應用船載水面高光譜擷取系統遙測近岸及內陸水體水質
論文名稱(外文):Remote Sensing of Inland and Costal Waters Quality Using Shipborne Hyper Surface Acquisition System (HyperSAS)
指導教授:劉正千劉正千引用關係
指導教授(外文):Cheng-Chien Liu
學位類別:碩士
校院名稱:國立成功大學
系所名稱:衛星資訊暨地球環境研究所
學門:自然科學學門
學類:地球科學學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:104
中文關鍵詞:GA-SA演算法水面高光譜獲取系統(HyperSAS)水質監測智慧光譜影像儀(ISIS)多平台遙測
外文關鍵詞:Hyper Surface Acquisition System (HyperSAS)genetic algorithm and semi-analytical algorithmIntelligent Spectral Imaging System (ISIS)monitoring water qualitymulti-platform remote sensing
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近岸及內陸水體對人們生活息息相關,但傳統方式耗時費力且資料在時空上均受到限制,不足以顯示整體水質的空間分佈,遙測方式雖可達成大範圍監測的目標,惟一般水色衛星對於觀測近岸與內陸地區水質的光譜及空間解析度均顯不足,而大量使用飛機平台又耗費過高成本。本研究使用船載水面高光譜擷取系統(Hyper Surface Acquisition System, HyperSAS)獲取光譜資料以監測水質,並做為機載拍攝影像大氣校正時之地面真實光譜。
HyperSAS經多項敏感度實驗及實測與模擬光譜驗證後,建立其穩定擷取光譜的最佳設置條件。本研究自中華民國97年3月至98年7月共進行五次野外調查,包含:曾文水庫(內陸水體)、高屏溪口(近岸水體)、台灣西南沿海(近岸水體),其中民國97年11月28日曾文水庫航次同步有機載智慧光譜影像儀( Intelligent Spectral Imaging System, ISIS )進行拍攝。將獲得之遙測反射率(remote sensing reflectance, Rrs)代入GA-SA演算法反算水質參數,包含:葉綠素a (chlorophyll-a, Chl-a)、水中懸浮固體物(suspended solids, SS)、水中無生命微粒(non-algal particle, NAP)、有色溶解性有機物質(coloured dissolved organic matter, CDOM; yellow substances; gelbstoff)等,過程中會先進行波段選取以增進其效能。

HyperSAS最佳設置條件
為取得準確的Rrs,感測器必須離水面超過1.5 m,並使太陽方位角位於135°-180°間。兩輻射儀之天頂角與天底角於30°-50°間均可,另要注意輻照度計須避免被高突物的陰影遮蔽。

以GA-SA反算水質之精度評估
HyperSAS
若架設符合最佳條件,應用在曾文水庫反算水質參數相當準確,Chl-a與SS平均絕對誤差(MAE)均在35%以內。台灣西南沿海因包含了一類與二類水體性質,因此反算結果較曾文水庫為差。但發現以Rrs之405 nm與550 nm之比值作為兩類水體的分類依據,先分類再代入相對應之生光模式(bio-optical models)進行反算,可提高水質參數的準確度,Chl-a與SS之MAE分別由137%、57%降至58%、47%。

HyperSAS之其他應用
當有HyperSAS 於ISIS拍攝時在水面進行同步光譜量測,利用同步光譜建立之回歸公式對影像進行大氣校正,能大幅提高各項水質參數之反算結果,Chl-a與SS的MAE均小於50%,便可利用ISIS來進行大範圍的水質監測。於高屏河口航次中,發現可藉由HyperSAS所測之Rrs光譜曲線對羽狀水團(plume)之泥沙含量進行分類,並能將此法應用至衛星影像上,如高空間、高時間解析度的福爾摩沙衛星二號(Formosat-2)。
Inland and coastal waters are the most important water resources for human beings, however, general approaches for assessing the water qualities of such an important water resource all rely on the data collected at a few sampling point. Those data are usually insufficient to identify the spatiotemporal variations of water-quality parameters. Water quality parameters derived from the remote sensing techniques may have potential to extend current monitoring results to comprehensively assess the water status. Although the progressing in remote sensing technology has enabled the observations of ocean color to be made from space, the existing spaceborne ocean color sensors are inappropriate for monitoring the water quality of inland water because of the limited spatial resolutions. Monitoring the inland water quality using airborne hyperspectral sensor is better but costly on a regular basis. The newly developed shipborne Hyper Surface Acquisition System (HyperSAS) can be deployed as a primary tool to monitor the water quality or a ground truth collector for calibrating airborne and spaceborne sensors.
Several in-situ and numerical experiments were conducted to test the data sensitivity of HyperSAS in different operation conditions and thus the standard operation procedures (SOP) were made to give reliable measurements of water-surface reflectance in ships. Five field campaigns to Tsengwen Reservoir (TWR) (inland water), Gao-Ping (Kao-Ping) River mouth (coastal water), and southwest coastal of Taiwan (SW) (coastal water) were conducted during March 2008 to July 2009. In the cruise of 11/28/2008, field campaign to TWR was conducted simultaneously with an airborne imager (Intelligent Spectral Imager System, ISIS). A newly developed water color retrieval algorithm, GA-SA, was applied to derive the concentration of chlorophyll-a (Chl-a), color dissolved organic matter (CDOM), suspended solids (SS) and non-algal particles (NAP) from the HyperSAS-measured reflectance (Rrs). Additionally, the optimal spectral bands of HyperSAS for water constituent retrieval were obtained using band selection methods for improving the efficiency of GA-SA.

SOP of HyperSAS
For a reliable measurement of Rrs, the distance between water surface and the sensor for measuring the surface radiance should be 1.5m or larger. A significant direct sun-glint effect was found in the measured Rrs when the radiance sensors are pointed at the azimuth angle between 0° and 135° to the solar plane. An optimal range 30° to 50° is suggested for the zenith angle of sky radiance measurement (also the nadir angle for measuring the surface radiance). Finally, the irradiance sensor should not be shaded when the Rrs is measuring.

Accuracy assessment of water quality inversion using GA-SA and shipborne HyperSAS
In two TWR cruises that HyperSAS were operated as the SOP given above, the measured Rrs gives good retrievals of Chl-a and SS using GA-SA and Case2 bio-optical models, as the mean absolute error (MAE) are all within 35%. The SW region contains not only optically Case 1 but also Case 2 waters in one cruise, thus the overall water quality inversion in this area is not as good as TWR where the optical properties are relatively consistent. Therefore, we developed a band ratio index using Rrs measured at 405 nm and 550 nm to determine the suitable bio-optical model for GA-SA before the retrieval. The overall accuracy for water quality inversion are improved significantly by this new approach, as the MAE for Chl-a and SS were improved from 137% to 58% and from 57% to 47%, respectively.

Other applications of HyperSAS
The shipborne HyperSAS can be deployed as a ground truth collector to provide reliable surface reflectance data for the atmospheric correction of airborne and spaceborne sensors. In the case of ISIS mission, the deviation of Chl-a and SS inversion from atmospheric corrected ISIS image were improved, as the MAE were all within 50% and the ISIS image was capable to mapping the reservoir water quality. In the case of Gao-Ping River mouth, the river plume can be classified in terms of the particle contents using the Rrs spectrum measured by HyperSAS. This newly developed classification method can be further applied in satellite imagery, such as the high temporal/spatial resolution Formosat-2 imagery.
摘要 i
Abstract iii
致謝 vi
目錄 vii
表目錄 x
圖目錄 xi
第1章 緒論 1
1.1 研究背景 1
1.2 研究目的 4
1.3 研究架構 5
第2章 文獻回顧 8
2.1 海洋水色遙測與水質反算 8
2.2 高光譜於水色之應用 11
2.3 多平台、多感測器遙測之應用 17
2.4 小結 18
第3章 研究區域 19
3.1 曾文水庫 20
3.2 高屏溪口 23
3.3 台灣西南沿海 25
第4章 研究方法 27
4.1 HYPERSAS資料擷取及前處理 27
4.2 水質分析 31
4.3 GA-SA演算法 33
第5章 HyperSAS資料處理與分析 36
5.1 Rrs計算 36
5.2 HyperSAS敏感度測試 37
5.3 波段選取 42
5.4 水質反算 47
5.5 小結 49
第6章 HyperSAS之應用 50
6.1 內陸水體 50
6.2 近岸水體 57
第7章 結論與建議 70
7.1 結論 70
7.2 建議 72
參考文獻 74
附錄一 各航次採樣點光譜曲線 81
附錄二 各航次採樣點水質資料 85
附錄三 ISIS 88
附錄四 Formosat-2 90
附錄五 羽狀水團四類水體邊界 93
附錄六 ac-s 95
附錄七 ECO VSF3 99
附錄八 GPS 100
附錄九 DH-4 101
Abbott, M. R., and Center, G. S. F.: Ocean Color in the 21st Century: A Strategy for a 20-year Time Series, National Aeronautics and Space Administration, Godard Space Flight Center, (1994).
Aguilar, M. A., Aguilar, F. J., Aguera, F., and Sanchez, J. A.: Geometric accuracy assessment of QuickBird basic imagery using different operational approaches, Photogrammetric Engineering and Remote Sensing, 73, 1321-1332, (2007).
Bajcsy, P., and Groves, P.: Methodology for hyperspectral band selection, Photogrammetric Engineering and Remote Sensing, 70, 793-802, (2004).
Bajwa, S. G., Bajcsy, P., Groves, P., and Tian, L. E.: Hyperspectral image data mining for band selection in agricultural applications, Transactions of the Asae, 47, 895-907, (2004).
Barale, V., and Folving, S.: Remote sensing of coastal interactions in the Mediterranean region, Ocean & Coastal Management, 30, 217-233, (1996).
Brando, V. E., and Dekker, A. G.: Satellite hyperspectral remote sensing for estimating estuarine and coastal water quality, Ieee Transactions on Geoscience and Remote Sensing, 41, 1378-1387, (2003).
Bricaud, A., Babin, M., Morel, A., and Claustre, H.: Variability in the Chlorophyll-Specific Absorption-Coefficients of Natural Phytoplankton - Analysis and Parameterization, Journal of Geophysical Research-Oceans, 100, 13321-13332, (1995).
Campo, L., Caparrini, F., and Castelli, F.: Use of multi-platform, multi-temporal remote-sensing data for calibration of a distributed hydrological model: an application in the Arno basin, Italy, Hydrological Processes, 20, 2693-2712, (2006).
Carder, K. L., Reinersman, P., Chen, R. F., Mullerkarger, F., Davis, C. O., and Hamilton, M.: AVIRIS CALIBRATION AND APPLICATION IN COASTAL OCEANIC ENVIRONMENTS, Remote Sensing of Environment, 44, 205-216, (1993).
Carter, R. W. G.: Coastal Environments: An Introduction to the Physical, Ecological, and Cultural Systems of Coastlines, Academic Press, Orelands, (1989).
Chang, C. H., Liu, C. C., and Wen, C. G.: Integrating semianalytical and genetic algorithms to retrieve the constituents of water bodies from remote sensing of ocean color, Optics Express, 15, 252-265, (2007).
Chavez, P. S., Berlin, G. L., and Sowers, L. B.: Statistical method for selecting landsat MSS ratios, Journal of applied photographic engineering, 1, 23-30, (1982).
Chester, R.: Marine Geochemistry, Unwin Hyman LTD., London, (1990).
Chiu, H. Y., and Collins, W.: A spectroradiometer for airborne remote sensing, Photogramm. Eng. Remote Sensing, 44, 507-517, (1978).
Chua, T. E.: Lessons Learned from Practicing Integrated Coastal Management in Southeast Asia, Ambio, 27, 599-610, (1998).
Dadson, S. J., Hovius, N., Chen, H. G., 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 orogen, Nature, 426, 648-651, (2003).
Dekker, A. G., Malthus, T. J., and Hoogenboom, H. J.: The remote sensing of inland water quality. In: Danson, F. M., and Plummer, S. E., eds. Advances in Environmental Remote Sensing, John Wiley & Sons, Chichester, (1995).
Du, K. P., Zhao, F., Lee, Z. P., and He, M. X.: Effects of Raman scattering and CDOM fluorescence to the multi-band Quasi-Analytical Algorithm (QAA). paper presented at: Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International, (2004).
Forget, P., Ouillon, S., Lahet, F., and Broche, P.: Inversion of reflectance spectra of nonchlorophyllous turbid coastal waters, Remote Sensing of Environment, 68, 264-272, (1999).
Fraser, C. S., Hanley, H. B., and Yamakawa, T.: Three-dimensional geopositioning accuracy of Ikonos imagery, Photogrammetric Record, 17, 465-479, (2002).
Gagnon, P., Scheibling, R. E., Jones, W., and Tully, D.: The role of digital bathymetry in mapping shallow marine vegetation from hyperspectral image data, International Journal of Remote Sensing, 29, 879-904, (2008).
George, D. G.: Bathymetric mapping using a Compact Airborne Spectrographic Imager (CASI), International Journal of Remote Sensing, 18, 2067-2071, (1997).
GESAMP: Land/sea boundary flux of contaminants: contributions from rivers. In: Unesco, ed. GESAMP Reports and Studies NO. 32, Paris, (1987).
Giardino, C., Brando, V. E., Dekker, A. G., Strombeck, N., and Candiani, G.: Assessment of water quality in Lake Garda (Italy) using Hyperion, Remote Sensing of Environment, 109, 183-195, (2007).
Goetz, A. F. H., and Rowan, L. C.: GEOLOGIC REMOTE-SENSING, Science, 211, 781-791, (1981).
Goetz, A. F. H., Vane, G., Solomon, J. E., and Rock, B. N.: IMAGING SPECTROMETRY FOR EARTH REMOTE-SENSING, Science, 228, 1147-1153, (1985).
Goldberg, D. E.: Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, New York, (1989).
Gordon, H. R., and Morel, A.: Remote Assessment of Ocean Color for interpretation of Satellite Visible Imagery, a Review; Lecture Notes on Coastal and Estuarine Studies, Volume 4., Springer Verlag, New York, (1983).
Green, R. O., Eastwood, M. L., Sarture, C. M., Chrien, T. G., Aronsson, M., Chippendale, B. J., Faust, J. A., Pavri, B. E., Chovit, C. J., Solis, M. S., Olah, M. R., and Williams, O.: Imaging spectroscopy and the Airborne Visible Infrared Imaging Spectrometer (AVIRIS), Remote Sensing of Environment, 65, 227-248, (1998).
Hair, J. F., Anderson, R. E., Tatham, R. L., and Black, W. C.: Multivariate data analysis, Prentice-Hall, Upper Saddle River, (1998).
Hamilton, M. K., Davis, C. O., Rhea, W. J., Pilorz, S. H., and Carder, K. L.: ESTIMATING CHLOROPHYLL CONTENT AND BATHYMETRY OF LAKE TAHOE USING AVIRIS DATA, Remote Sensing of Environment, 44, 217-230, (1993).
Hayes‪, C. J. H., Moon, P. T., and Wayland, J. W.: 世界通史, 東方書店, 台北市, (1952).
Hoogenboom, H. J., Dekker, A. G., and Althuis, I. A.: Simulation of AVIRIS sensitivity for detecting chlorophyll over coastal and inland waters, Remote Sensing of Environment, 65, 333-340, (1998).
Hooker, S. B., Lazin, G., Zibordi, G., and McLean, S.: An evaluation of above- and in-water methods for determining water-leaving radiances, Journal of Atmospheric and Oceanic Technology, 19, 486-515, (2002).
Joshi, P. K., Gupta, B., and Roy, P. S.: Spectral evaluation of vegetation features using multi-satellite sensor system (Terra ASTER, Landsat ETM+ and IRS 1D LISS III) in man-made and natural landscape, Sensor Review, 28, 52-61, (2008).
Kallio, K., Kutser, T., Hannonen, T., Koponen, S., Pulliainen, J., Vepsalainen, J., and Pyhalahti, T.: Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons, Science of the Total Environment, 268, 59-77, (2001).
Koseff, J. R., Holen, J. K., Monismith, S. G., and Cloern, J. E.: COUPLED EFFECTS OF VERTICAL MIXING AND BENTHIC GRAZING ON PHYTOPLANKTON POPULATIONS IN SHALLOW, TURBID ESTUARIES, Journal of Marine Research, 51, 843-868, (1993).
Lahet, F., Ouillon, S., and Forget, P.: Water quality and optical properties of coastal waters from hyperspectral data. paper presented at: Oceans'98 - Conference Proceedings, Vols 1-3, (1998).
Lee, Z. P., Carder, K. L., and Arnone, R. A.: Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters, Applied Optics, 41, 5755-5772, (2002).
Lee, Z. P., Carder, K. L., Mobley, C. D., Steward, R. G., and Patch, J. S.: Hyperspectral remote sensing for shallow waters. I. A semianalytical model, Applied Optics, 37, 6329-6338, (1998).
Lee, Z. P., Carder, K. L., Mobley, C. D., Steward, R. G., and Patch, J. S.: Hyperspectral remote sensing for shallow waters: 2. Deriving bottom depths and water properties by optimization, Applied Optics, 38, 3831-3843, (1999).
Lee, Z. P., Carder, K. L., Steward, R. G., Peacock, T. G., Davis, C. O., and Mueller, J. L.: Remote sensing reflectance and inherent optical properties of oceanic waters derived from above-water measurements. In: Ocean Optics XIII, Halifax, Nova Scotia, Canada, (1997).
Lee, Z. P., and International Ocean-Colour Coordinating, G.: Remote sensing of inherent optical properties: fundamentals, tests of algorithms, and applications, International Ocean-Colour Coordinating Group, Dartmouth, (2006).
Leonard, C. L., Bidigare, R. R., Seki, M. P., and Polovina, J. J.: Interannual mesoscale physical and biological variability in the North Pacific Central Gyre, Progress in Oceanography, 49, 227-244, (2001).
Li, Y. H.: DENUDATION OF TAIWAN ISLAND SINCE PLIOCENE EPOCH, Geology, 4, 105-108, (1976).
Liu, C. C.: Processing of FORMOSAT-2 daily revisit imagery for site surveillance, Ieee Transactions on Geoscience and Remote Sensing, 44, 3206-3214, (2006).
Liu, C. C., Chang, C. H., Wen, C. G., Huang, C. H., Hung, J. J., and Liu, J. T.: Using satellite observations of ocean color to categorize the dispersal patterns of river-borne substances in the Gaoping (Kaoping) River, Shelf and Canyon system, Journal of Marine Systems, 76, 496-510, (2009).
Liu, J. T., Chao, S. Y., and Hsu, R. T.: The influence of suspended sediments on the plume of a small mountainous river, Journal of Coastal Research, 15, 1002-1010, (1999).
Manuel C. Molles, J.: 生態學 - 概念與應用, 美商麥格羅•希爾國際股份有限公司 台灣分公司, 臺北市, (2002).
McCabe, M. F., Wood, E. F., Wojcik, R., Pan, M., Sheffield, J., Gao, H., and Su, H.: Hydrological consistency using multi-sensor remote sensing data for water and energy cycle studies, Remote Sensing of Environment, 112, 430-444, (2008).
Miranda, P. J., and Granados, H. D.: Fast hazard evaluation employing digital photogrammetry: Popocatepetl glaciers, Mexico, GEOFISICA INTERNACIONAL-MEXICO-, 42, 275-283, (2003).
Mobley, C. D.: Light and Water: radiative transfer in natural waters, Academic Press, Inc., San Diego, (1994).
Morel, A., and Prieur, L.: ANALYSIS OF VARIATIONS IN OCEAN COLOR, Limnology and Oceanography, 22, 709-722, (1977).
Ostlund, C., Flink, P., Strombeck, N., Pierson, D., and Lindell, T.: Mapping of the water quality of Lake Erken, Sweden, from Imaging Spectrometry and Landsat Thematic Mapper, Science of the Total Environment, 268, 139-154, (2001).
Pegau, S., Zanefeld, J. R. V., Mitchell, B. G., Mueller, J. L., Kahru, M., Wieland, J., and Stramska, M. eds.: Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume IV: Inherent Optical Properties: Instruments, Characterizations, Field Measurements and Data Analysis Protocols, Greenbelt, Maryland: National Aeronautics and Space Administration (NASA), Maryland, (2003).
Pernetta, J. C., and Milliman, J. D.: Land ocean interactions in the coastal zone. implementation plan. IGBP report No. 33, Stockholm, (1995).
Robinson, I. S.: Measuring the oceans from space: the principles and methods of satellite oceanography, Springer, New York, (2004).
Ruberg, S. A., Guasp, E., Hawley, N., Muzzi, R. W., Brandt, S. B., Vanderploeg, H. A., Lane, J. C., Miller, T., and Constant, S. A.: Societal Benefits of the Real-Time Coastal Observation Network (ReCON): Implications for Municipal Drinking Water Quality, Marine Technology Society Journal, 42, 103-109, (2008).
Salomons, W., and Forstner, U.: Metals in the hydrocycle, Springer-Verlag. Berlin, New York, (1984).
Sandidge, J. C., and Holyer, R. J.: Coastal bathymetry from hyperspectral observations of water radiance, Remote Sensing of Environment, 65, 341-352, (1998).
Sathyendranath, S.: Remote sensing of ocean colour in coastal, and other optically-complex, waters. IOCCG Report. 3. 140 p., Canada, (2000).
Satlantic Incorporated: Operation Manual for the HyperSAS. Halifax, (2003).
Satlantic Incorporated: ProSoft User Manual 7.7. Halifax, (2004a).
Satlantic Incorporated: SatView Data Logging / Display Program Users Guide Version 2.8. Halifax, (2004b).
Schlesinger, W. H.: Biogeochemistry: An Analysis of Global Change, Academic Press, San Diego, (1991).
Sears, F. W.: Optics, Addison-Wesley, Cambridge, (1949).
Secretariat, I.: IGBP in Action: Work Plan 1994~ 1998. IGBP Report No. 28, Stockholm, (1994).
Shannon, C. E.: Communication Theory and Secrecy Systems, (1949).
Shannon, C. E.: A mathematical theory of communication, The Bell Syst Tech J, 27, 379-423, (1948).
Shih, H. H.: Recent Advances in In-Situ Ocean Observation, Proceedings of the 27th International Conference on Offshore Mechanics and Archtic Engineering - 2008, Vol 4, 983-994, (2008).
Stumpf, R. P., Gelfenbaum, G., and Pennock, J. R.: WIND AND TIDAL FORCING OF A BUOYANT PLUME, MOBILE-BAY, ALABAMA, Continental Shelf Research, 13, 1281-1301, (1993).
Syvitski, J. P. M., Vorosmarty, C. J., Kettner, A. J., and Green, P.: Impact of Humans on the Flux of Terrestrial Sediment to the Global Coastal Ocean, Science, 308, 376-380, (2005).
Thomas, A. C., and Weatherbee, R. A.: Satellite-measured temporal variability of the Columbia River plume, Remote Sensing of Environment, 100, 167-178, (2006).
Turekian, K. K.: The fate of metals in the oceans, Geochimica et Cosmochimica Acta, 41, 1139-1144, (1977).
Vane, G., and Goetz, A. F. H.: TERRESTRIAL IMAGING SPECTROMETRY - CURRENT STATUS, FUTURE-TRENDS, Remote Sensing of Environment, 44, 117-126, (1993).
WET Labs, I.: ac-9 Protocol Document. Philomath, (2005).
WET Labs, I.: DH-4 Data Handler User's Guide. Philomath, (2006a).
WET Labs, I.: Spectral Absorption and Attenuation Meter (ac-s) User's Guide. Philomath, (2006b).
WET Labs, I.: WET Labs Archive File Processing User's Guide. Philomath, (2006c).
Yu, H. S.: Contrasting tectonic style of a foredeep with a passive margin: southwest Taiwan and south China, Petrol. Geol. Taiwan, 28, 97–118, (1993).
Yu, H. S., Huang, C. S., and Ku, J. W.: Morphology and possible origin of the Kaoping submarine canyon head off south-west Taiwan, Acta Oceanogr. Taiwanica, 27, 40–50, (1991).
Zoej, M. J. V., and Sadeghian, S.: Rigorous and Non-Rigorous Photogrammetric Processing of IKONOS Geo Image. paper presented at: Joint Workshop of ISPRS WG I/2, I/5, IC WG II/IV, High Resolution Mapping from Space, Hannover, Germany, (2003).
山地農牧局: 山坡地土壤調查報告-嘉義縣、雲林縣. 臺灣省政府農林廳山地農牧局, 南投, (1981).
中央氣象局: http://www.cwb.gov.tw/. (2009).
內政部營建署: http://gisapsrv01.cpami.gov.tw/fcu-gis/. 區域計畫地理資訊查詢系統, (2009).
王建宇: 高光譜遙感--給人類配上一副神眼, 世界科學, 32-33, (1999).
王薏雯: 整合福衛二號高時間解析度和高空間解析度衛星影像與田間光譜資料監測水稻生長和預測產量, 國立成功大學: 地球科學系研究所, 碩士, 台南市, (2007).
行政院環境保護署: 地球難以承受之熱-全球溫暖化, 行政院環境保護署, 台北市, (1999).
西拉雅國家風景區: www.siraya-nsa.gov.tw. (2009).
李龍正: 高光譜影像儀 ISIS 及 FUHSI, 科儀新知, 29, 12-21, (2007).
李龍正: 高光譜影像儀發展及影像市場前景, 科儀新知, 26, 50-57, (2004).
周魯閩, and 盧昌義: 東亞海區的海岸帶綜合管理經驗:從地方性示範到區域性合作, 台灣海峽, 25, 452-458, (2006).
浦瑞良, and 宮鵬: 高光譜遙測及其應用, 五南圖書出版股份有限公司, 台北市, (2002).
國家太空中心: http://www.nspo.org.tw. (2009).
崔連仲, 劉明翰, and 劉祚昌: 世界通史, 人民出版社, 北京, (1997).
張智華: 非點源污染負荷模式及水質生光模式之結合與應用, 國立成功大學: 環境工程學系研究所, 博士, 台南市, (2008).
莊世仁: 運用蒙地卡羅光束追蹤技術模擬水槽中的輻射傳輸過程, 國立成功大學: 地球科學系研究所, 碩士, 台南市, (2008).
郭晉安, 簡仲和, and 黃建維: 台南海岸觀測調查分析. In: 九十一年度河海調查規劃委辦計劃成果發表會, (2002).
郭慧君: ”綠中有綠, 藍中有藍-儀科中心高光譜儀為您解讀知識影像” 記者會紀要, 國研科技, 15, 98-99, (2007).
陳建良: 海岸生態環境保護策略之探討. In: 資源與環境學術研討會, 花蓮, (2005).
黃嘉慧: 以HSPF營養鹽模組討論農業對非點源污染負荷之貢獻, 國立成功大學: 環境工程學系研究所, 碩士, 台南市, (2005).
黃慶祥: 水庫水質與光學性質模式之建立及其應用, 國立成功大學: 環境工程學系研究所, 碩士, 台南市, (2006).
溫清光, and 郭振泰: 曾文水庫水質調查及改善後計畫. 經濟部水利署南區水資源局, 台南, (2003).
經濟部水利署: www.wra.gov.tw. (2009).
經濟部水利署南區水資源局: www.wrasb.gov.tw. (2009).
農業委員會: 山坡地土壤調查報告-台南縣. 行政院農業委員會, 台北市, (1986).
臺灣南區氣象中心: http://south.cwb.gov.tw/index1.php. (2009).
儀器科技研究中心: http://www.itrc.org.tw/. (2009).
劉正千, 張智華, 許華宇, 譚子健, and 溫清光: 應用ISIS高頻譜光學遙測影像於曾文水庫之水質監測, 科儀新知, 29, 29-42, (2007).
劉春紅, 趙春暉, and 張凌雁: 一種新的高光譜遙感圖像降維方法, 中國圖象圖形學報, 10, 218-222, (2005).
潘國樑: 遙測學大綱:遙測概念、原理與影像判釋技術, 科技圖書股份有限公司, 臺北市, (2006).
蔡在宗, 柯欽彬, and 劉正千: 國立成功大學福爾摩沙衛星二號應用推廣中心介紹 - 影像處理、應用、標準與加值產品及其訂購方法. In: 2005年衛星遙測於地質環境與災害應用國際研討會, 台南, (2005).
鄭蘭芬, and 王晉年: 成像光譜遙感技術及其圖像光譜信息提取的分析研究, 環境遙感, 7, 49-58, (1992).
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