跳到主要內容

臺灣博碩士論文加值系統

(44.212.99.248) 您好!臺灣時間:2023/01/28 12:28
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:葉冠儀
研究生(外文):Yeh, Guan-I
論文名稱:以中尺度地球資源衛星影像分析台灣主要民生水庫枯水期水質分佈、藻類生長限制因子與可能人為影響來源
論文名稱(外文):Mapping dry-season water quality parameters and information for eutrophication control on water supply reservoirs of Taiwan from moderate resolution satellite imagery
指導教授:張智華張智華引用關係
指導教授(外文):Chang, Chih-Hua
口試委員:劉大綱朱宏杰陳起鳳
口試委員(外文):Liu, Ta-KangChu, Hone-JayChen, Chi-Feng
口試日期:2021-07-16
學位類別:碩士
校院名稱:國立成功大學
系所名稱:環境工程學系
學門:工程學門
學類:環境工程學類
論文種類:學術論文
論文出版年:2021
畢業學年度:109
語文別:中文
論文頁數:218
中文關鍵詞:中尺度地球資源衛星遙感探測台灣主要民生水庫藻類生長限制因子
外文關鍵詞:Meso-scale satellite images of earth resourcesRemote sensingMajor supply reservoirs in TaiwanAlgae growth limiting factors
相關次數:
  • 被引用被引用:0
  • 點閱點閱:55
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
台灣每年非雨季期間之民生、農業、水力與工業用水幾乎全都仰賴水庫供應,水庫水量水質是否安全與穩定,是影響社會民生與經濟發展的重要因素。水庫優養化是營養物質與沉積物長期累積,使浮游植物過量生長並導致各種民生用水水質問題的主要成因。目前水庫水質管理單位透過透明度、葉綠素、營養鹽與濁度等物化水質參數之長期、定點監測,建立指標評估多座水庫優養狀態,再篩選出時-空分佈上較具風險之水庫蓄水區域,進行深入的污染調查與擬定營養負荷削減策略。現行監測雖能提供準確的實驗室水質檢測成果,不過,花費甚多卻僅能提供低頻度、低點數、時-空分佈極為有限的資訊。
近年陸續升空執行任務之地球資源衛星,包括2013年升空的Landsat-8 (簡稱L-8)及2015年升空的Sentinel-2AB (簡稱S-2),不僅可提供10m解析度、再訪率5-9天的高品質中尺度陸地資源研究資料,其參考水色衛星所設定之可見光、近紅外與短波紅外波段非常適合用以偵測薄雲、移除大氣干擾並解析水色。本研究利用2017-2019年非雨季期間(水質穩定期)無雲之L8及S2的影像,共有449天的影像,選用海洋水色學界常用之嚴謹大氣校正方法及水質演算法分析全台18座蓄水面積達60 ha以上民生水庫(每座水庫平均25幅)。經文獻彙整後本研究選用Dogliotti、海洋水色半解析模式與NASA的OC3遙測水質方法分別推估水庫表層濁度(TB)、沙奇盤透明度(ZSD)與葉綠素-a (Chl-a)等3項與優養相關之水質參數,並產製18座水庫水質分布圖。
本研究收集2017-2019年環保署實測水質資料,並由18座水庫水質分布影像提取可與實測值匹配之遙測水質,以實測與遙測日期差距5天內及排除遙測濁度80 FNU為準則,建立共466對遙測與實測匹配水質資料庫,匹配結果顯示TB相關性最佳(R=0.6)但均為高估,因此Dogliotti法應用於台灣水庫需乘0.3-0.5倍;海洋水色半解析ZSD模式推估值與實測值相比互有高低,但特別適用於透明度時空變異(以實測ZSD變異係數表示,CVSD)中等的13座水庫,其相關性可達0.57,若CVSD>35%或CVSD<20%則相關性變差。本研究發現Chl-a匹配相關性最差,有10座水庫的OC3遙測值較接近實測(R=0.32),其他8座水庫誤差較大且共同特徵為TB值>3.1 FNU,顯示高濁水庫較不適合使用OC3推估Chl-a,亦驗證應用於海洋之演算法僅能適用於低TB水庫之Chl-a推估。根據匹配水質資料庫分析結果,本研究以簡線性回歸模式修正Dogliotti、海洋水色半解析模式與OC3演算法,針對不同水庫群建立修正係數,使遙測水質濃度較為接近實測水質。
本研究將修正後的三年逐幅水質分佈圖以中位數整合,分析18座台灣主要民生水庫於枯水期的「透明度與濁度」與「葉綠素」空間分佈特性,發現遙測水質呈現之空間變化遠優於點測站所計算之變異係數,小型離槽水庫之TB與ZSD空間變化較為明顯,大型在槽水庫則有較顯著的Chl-a空間變化,研判影響水庫上下游水質空間變化的重要因子有操作型態、規模或水力停留時間、水庫幾何形狀及水深。本研究提出的TB、ZSD與Chl-a空間分佈型態交互分類準則,建立藻類生長限制因子研判指標,大多數水庫分類結果顯示上游或越域引水匯入處資訊不足(因OC3在濁度高時誤判)、中游為光限制、下游為水質相對較佳處且光照為影響藻類是否能持續生長的重要條件;較為特別者為翡翠、德基、明德及阿公店水庫,其上游可能受營養鹽控制。
本研究評估海洋水色演算法推估中尺度水庫水質時空分布之適用性,提出修正方法並分析台灣18座水庫在枯水期的水質空間分佈與藻類生長限制因子,能提供「具有空間分佈特性之決策支援訊息」,協助管理機關精進水庫優養化改善策略。
Eutrophication is one of the problems of reservoirs in Taiwan. However, the traditional ship sampling for several measuring stations can not represent the water quality of the overall water reservoir. Remote sensing of water quality has the advantages of time-space distribution and has been widely used.The main purpose of this study is to analyze the applicability of remote sensing of water quality, establish correction formula through simple linear regression models for different reservoir groups, let the remote sensing of water quality close to water quality measurement.Through integrated images analyze the spatial distribution of water quality of reservoir in dry seasons and determine limiting factors of algal growth.We use images from Landsat-8 and Sentinel-2. The study area is 18 water major supply reservoirs in Taiwan. The time of images are the dry season from 2017 to 2019. There are totally 449 days images, compared with the observed values of the EPA in Taiwan. The results show that, the correlation of TB is the best, all telemetry TB is greater than the actual measurement TB.When applying the algorithm, the telemetry TB need to multiply 0.3-0.5. ZSD is the second place.Chl-a has the worst correlation simultaneous show the algorithm suitable for low TB reservoirs. It is found that the spatial distribution of the remote sensing of water quality is superior to the variation calculated by the point measurement station. Most of the upstream reservoirs misjudged when the turbidity is high due to the algorithm, the middle reaches are limited by light, the downstream water quality is relatively good, and light is an important condition that affects the growth of algae.
摘要 I
致謝 VI
目錄 VIII
表目錄 XI
圖目錄 XIII
第 1 章 緒論 1
1.1 研究動機 1
1.2 研究目的 2
1.3 論文架構 2
第 2 章 文獻回顧 4
2.1 衛星影像遙測水庫水質技術 4
2.1.1 衛星遙測水質原理 4
2.1.2 遙測監測與傳統船採監測水庫水質的優缺點 5
2.2 水庫優養化的原因 6
2.2.1 水庫的藻類生長限制因子 6
2.2.2 水庫周圍的可能人為影響 8
2.3 台灣水庫水質監測與水質指標 9
2.3.1 台灣水庫水質監測現況與水庫優養化指標 9
2.3.2 遙測應用於台灣水庫水質監測 12
2.4 水庫水質測繪圖之分析與應用 15
第 3 章 研究材料與方法 17
3.1 研究區域 17
3.2 中尺度地球資源衛星 23
3.2.1 Landsat8衛星 23
3.2.2 Sentinel2衛星 27
3.2.3 衛星影像資料取得 29
3.3 衛星影像處理 36
3.3.1 大氣校正方法 36
3.3.2 水庫的衛星影像資料庫建立 41
3.3.3 水質演算法與水色產品 45
3.3.4 水庫水質分布圖之製作 51
3.3.5 地真資料之收集 53
3.3.6 影像水質之提取 56
第 4 章 結果與討論 59
4.1 建立地真與遙測水質匹配資料庫 59
4.1.1 環保署的實測水質枯水期數據統計分析 59
4.1.2 影像水質篩選與水質匹配資料庫建立 64
4.2 遙測水質產品的驗證與修正 74
4.2.1 遙測水質與實測水質之比較 74
4.2.1.1 18個水庫分析 74
4.2.1.2 各別水質分析 93
4.2.2 建立適用於台灣水庫之遙測水質產品修正公式與誤差分析 99
4.2.2.1 修正公式 99
4.2.2.2 誤差分析 104
4.3 台灣水庫枯水期水質空間分佈特性之討論 107
4.3.1 多期水質分佈圖整合 107
4.3.2 藻類生長限制因子研判指標 109
4.3.3 水質空間分佈特性之討論 111
4.3.4 空間分布結論 156
第 5 章 結論與建議 165
5.1 結論 165
5.2 建議 168
第 6 章 參考文獻 169
附錄 177
附錄一 下載衛星影像的日期 177
附錄二 衛星影像資料庫 179
附錄三 實測原始數據統計分析 195
附錄四 遙測原始數據統計分析 198
附錄五 水質匹配資料庫 201
附錄六 盒鬚圖與統計分析 214
Baeye, M., Quinn, R., Deleu, S., & Fettweis, M. (2016). Detection of shipwrecks in ocean colour satellite imagery. Journal of Archaeological Science, 66, 1-6. doi:10.1016/j.jas.2015.11.006
Bulgarelli, B., Kiselev, V., & Zibordi, G. (2014). Simulation and analysis of adjacency effects in coastal waters: a case study. Applied Optics, 53(8), 1523-1545. Retrieved from http://ao.osa.org/abstract.cfm?URI=ao-53-8-1523. doi:10.1364/AO.53.001523
Carlson, R. (1977). A Trophic State Index for Lakes. Limnology and Oceanography - LIMNOL OCEANOGR, 22, 361-369. doi:10.4319/lo.1977.22.2.0361
Chang, C. H., Cai, L. Y., Lin, T. F., Chung, C. L., van der Linden, L., & Burch, M. (2015). Assessment of the Impacts of Climate Change on the Water Quality of a Small Deep Reservoir in a Humid-Subtropical Climatic Region. Water, 7(4), 1687-1711. Retrieved from ://WOS:000353715100020. doi:10.3390/w7041687
Chang, C. H., Liu, C. C., Wen, C. G., Cheng, I. F., Tam, C. K., & Huang, C. S. (2009). Monitoring reservoir water quality with Formosat-2 high spatiotemporal imagery. Journal of Environmental Monitoring, 11(11), 1982-1992. Retrieved from ://WOS:000271476600009. doi:10.1039/b912897b
Chang, K. W., Shen, Y., & Chen, P. C. (2004). Predicting algal bloom in the Techi reservoir using Landsat TM data. International Journal of Remote Sensing, 25(17), 3411-3422. Retrieved from https://doi.org/10.1080/01431160310001620786. doi:10.1080/01431160310001620786
Chang, N.-B., Wen, C. G., & Wu, S. L. (1995). Optimal Management of Environmental and Land Resources in a Reservoir Watershed by Multiobjective Programming. Journal of Environmental Management, 44(2), 144-161. Retrieved from https://www.sciencedirect.com/science/article/pii/S0301479785700369. doi:https://doi.org/10.1006/jema.1995.0036
Chang, S. P., & Chuang, S. M. (2001). Eutrophication study of twenty reservoirs in Taiwan. Water Sci Technol, 44(6), 19-26.
Chawira, M., Dube, T., & Gumindoga, W. (2013). Remote sensing based water quality monitoring in Chivero and Manyame lakes of Zimbabwe. Physics and Chemistry of the Earth, 66, 38-44. Retrieved from ://WOS:000328927500006. doi:10.1016/j.pce.2013.09.003
Chen, L., Tan, C.-H., Kao, S.-J., & Wang, T.-S. (2008). Improvement of remote monitoring on water quality in a subtropical reservoir by incorporating grammatical evolution with parallel genetic algorithms into satellite imagery. Water Research, 42(1), 296-306. Retrieved from https://www.sciencedirect.com/science/article/pii/S0043135407004733. doi:https://doi.org/10.1016/j.watres.2007.07.014
Cheng, G., Han, J., & Lu, X. (2017). Remote Sensing Image Scene Classification: Benchmark and State of the Art. Proceedings of the IEEE, 105(10), 1865-1883. doi:10.1109/JPROC.2017.2675998
Cheng, K.-S., & Lei, T. C. (2001). Reservoir trophic state evaluation using Landsat TM images. JAWRA Journal of the American Water Resources Association, 37, 1321-1334. doi:10.1111/j.1752-1688.2001.tb03642.x
Chu, H.-J., Liu, C.-Y., & Wang, C.-K. (2013). Identifying the Relationships between Water Quality and Land Cover Changes in the Tseng-Wen Reservoir Watershed of Taiwan. International journal of environmental research and public health, 10, 478-489. doi:10.3390/ijerph10020478
Cunha, D. G. F., & Calijuri, M. D. (2011). Limiting factors for phytoplankton growth in subtropical reservoirs: the effect of light and nutrient availability in different longitudinal compartments. Lake and Reservoir Management, 27(2), 162-172. Retrieved from ://WOS:000291853900006. doi:10.1080/07438141.2011.574974
Dörnhöfer, K., Klinger, P., Heege, T., & Oppelt, N. (2018). Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake. Science of The Total Environment, 612, 1200-1214. Retrieved from https://www.sciencedirect.com/science/article/pii/S0048969717322179. doi:https://doi.org/10.1016/j.scitotenv.2017.08.219
Dogliotti, A. I., Ruddick, K. G., Nechad, B., Doxaran, D., & Knaeps, E. (2015). A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters. Remote Sensing of Environment, 156, 157-168. Retrieved from https://www.sciencedirect.com/science/article/pii/S0034425714003654. doi:https://doi.org/10.1016/j.rse.2014.09.020
Doi, H., Akamatsu, Y., Watanabe, Y., Goto, M., Inui, R., Katano, I., . . . Minamoto, T. (2017). Water sampling for environmental DNA surveys by using an unmanned aerial vehicle. Limnology and Oceanography: Methods, 15(11), 939-944. Retrieved from https://aslopubs.onlinelibrary.wiley.com/doi/abs/10.1002/lom3.10214. doi:https://doi.org/10.1002/lom3.10214
Evans, D. M., Schoenholtz, S. H., Wigington, P. J., Jr., Griffith, S. M., & Floyd, W. C. (2014). Spatial and temporal patterns of dissolved nitrogen and phosphorus in surface waters of a multi-land use basin. Environ Monit Assess, 186(2), 873-887. doi:10.1007/s10661-013-3428-4
Feaster, L., Poli, C., & Kirchhoff, R. (1977). Dynamics of a slung load. Journal of Aircraft, 14(2), 115-121. Retrieved from https://arc.aiaa.org/doi/abs/10.2514/3.44578. doi:10.2514/3.44578
Feng, M., & Shen, Z. (2021). Assessment of the Impacts of Land Use Change on Non-Point Source Loading under Future Climate Scenarios Using the SWAT Model. Water, 13, 874. doi:10.3390/w13060874
Franz, B. A., Bailey, S. W., Kuring, N., & Werdell, P. J. (2015). Ocean color measurements with the Operational Land Imager on Landsat-8: implementation and evaluation in SeaDAS. Journal of Applied Remote Sensing, 9(1), 096070.
Gernez, P., Doxaran, D., & Barillé, L. (2017). Shellfish Aquaculture from Space: Potential of Sentinel2 to Monitor Tide-Driven Changes in Turbidity, Chlorophyll Concentration and Oyster Physiological Response at the Scale of an Oyster Farm. Frontiers in Marine Science, 4(137). Retrieved from https://www.frontiersin.org/article/10.3389/fmars.2017.00137. doi:10.3389/fmars.2017.00137
Gianesella-Galvão, S. M. F. (1985). Primary production in ten reservoirs in southern Brazil. Hydrobiologia, 122(1), 81-88. Retrieved from https://doi.org/10.1007/BF00018962. doi:10.1007/BF00018962
Gibson, P., Gibson, P. J., Power, C., & Power, C. H. (2000). Introductory Remote Sensing: Digital Image Processing and Applications: Routledge.
Gippel, C. (1995). Environmental Hydraulics of Large Woody Debris in Streams and Rivers. Journal of Environmental Engineering-asce - J ENVIRON ENG-ASCE, 121. doi:10.1061/(ASCE)0733-9372(1995)121:5(388)
Gordon, H. R., & Castaño, D. J. (1987). Coastal Zone Color Scanner atmospheric correction algorithm: multiple scattering effects. Applied Optics, 26(11), 2111-2122. Retrieved from http://ao.osa.org/abstract.cfm?URI=ao-26-11-2111. doi:10.1364/AO.26.002111
Guo, H., Goodchild, M. F., & Annoni, A. (2020). Manual of Digital Earthnull: Springer Nature.
Hestir, E. L., Brando, V. E., Bresciani, M., Giardino, C., Matta, E., Villa, P., & Dekker, A. G. (2015). Measuring freshwater aquatic ecosystems: The need for a hyperspectral global mapping satellite mission. Remote Sensing of Environment, 167, 181-195. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938999023&doi=10.1016%2fj.rse.2015.05.023&partnerID=40&md5=461c7059f3e646606e99a53fb6fbb16f. doi:10.1016/j.rse.2015.05.023
Hu, C., Muller-Karger, F. E., Biggs, D. C., Carder, K. L., Nababan, B., Nadeau, D., & Vanderbloemen, J. (2003). Comparison of ship and satellite bio-optical measurements on the continental margin of the NE Gulf of Mexico. International Journal of Remote Sensing, 24(13), 2597-2612. Retrieved from https://doi.org/10.1080/0143116031000067007. doi:10.1080/0143116031000067007
Huszar, V. (2006). Nutrient–chlorophyll relationships in tropical– subtropical lakes: do temperate models fit? Biogeochemistry, 79, 239. doi:10.1007/s10533-006-9007-9
Jackson, R. B., Carpenter, S. R., Dahm, C. N., McKnight, D. M., Naiman, R. J., Postel, S. L., & Running, S. W. (2001). Water in a changing world. Ecological Applications, 11(4), 1027-1045. Retrieved from ://WOS:000170209200008. doi:10.1890/1051-0761(2001)011[1027:Wiacw]2.0.Co;2
Kutser, T. (2004). Quantitative detection of chlorophyll in cyanobacterial blooms by satellite remote sensing. Limnology and Oceanography, 49(6), 2179-2189. Retrieved from https://aslopubs.onlinelibrary.wiley.com/doi/abs/10.4319/lo.2004.49.6.2179. doi:https://doi.org/10.4319/lo.2004.49.6.2179
Lee, Z. P., Shang, S. L., Hu, C. M., Du, K. P., Weidemann, A., Hou, W. L., . . . Lin, G. (2015). Secchi disk depth: A new theory and mechanistic model for underwater visibility. Remote Sensing of Environment, 169, 139-149. Retrieved from ://WOS:000363815900010. doi:10.1016/j.rse.2015.08.002
Lewis Jr, W. M. (2000). Basis for the protection and management of tropical lakes. Lakes & Reservoirs: Science, Policy and Management for Sustainable Use, 5(1), 35-48. Retrieved from https://doi.org/10.1046/j.1440-1770.2000.00091.x. doi:https://doi.org/10.1046/j.1440-1770.2000.00091.x
Lillesand, T., Kiefer, R., & Chipman, J. (2004). Remote Sensing and Image Interpretation (Fifth Edition) (Vol. 146).
Lin, T.-C., Shaner, P.-J., Wang, L. J., Shih, Y.-t., Wang, C.-P., Huang, G. H., & Huang, J.-C. (2015). Effects of mountain tea plantations on nutrient cycling at upstream watersheds. Hydrology and Earth System Sciences, 19, 4493-4504. doi:10.5194/hess-19-4493-2015
Liu, C. C., Nakamura, R., Ko, M. H., Matsuo, T., Kato, S., Yin, H. Y., & Huang, C. S. (2017). Near Real-Time Browsable Landsat-8 Imagery. Remote Sensing, 9(1), 13. Retrieved from ://WOS:000395492600078. doi:10.3390/rs9010079
Mishra, S., & Mishra, D. R. (2012). Normalized difference chlorophyll index: A novel model for remote estimation of chlorophyll-a concentration in turbid productive waters. Remote sensing of environment., 117, 394-406. Retrieved from http://europepmc.org/abstract/AGR/IND600875842
https://doi.org/10.1016/j.rse.2011.10.016. doi:10.1016/j.rse.2011.10.016
Morel, A., & Prieur, L. (1977). Analysis of variations in ocean color1. Limnology and Oceanography, 22(4), 709-722. Retrieved from https://aslopubs.onlinelibrary.wiley.com/doi/abs/10.4319/lo.1977.22.4.0709. doi:https://doi.org/10.4319/lo.1977.22.4.0709
Nechad, B., Ruddick, K., & Neukermans, G. (2009). Calibration and validation of a generic multisensor algorithm for mapping of turbidity in coastal waters (Vol. 7473): SPIE.
Nechad, B., Ruddick, K. G., & Park, Y. (2010). Calibration and validation of a generic multisensor algorithm for mapping of total suspended matter in turbid waters. Remote Sensing of Environment, 114(4), 854-866. Retrieved from ://WOS:000274982700014. doi:10.1016/j.rse.2009.11.022
Nguyen, H. H., Recknagel, F., Meyer, W., Frizenschaf, J., Ying, H., & Gibbs, M. S. (2019). Comparison of the alternative models SOURCE and SWAT for predicting catchment streamflow, sediment and nutrient loads under the effect of land use changes. Sci Total Environ, 662, 254-265. doi:10.1016/j.scitotenv.2019.01.286
O'Reilly, J. E., Aeronautics, U. S. N., & Administration, S. (2000). SeaWiFS Postlaunch Calibration and Validation Analyses, Part 3: NASA Center for AeroSpace Information.
Olem, H., & Flock, G. (1990). Lake and Reservoir Restoration Guidance Manual : Second Edition. doi:https://doi.org/doi:10.7282/T3JD4WCD
Olmanson, L. G., Brezonik, P. L., & Bauer, M. E. (2011). Evaluation of medium to low resolution satellite imagery for regional lake water quality assessments. Water Resources Research, 47(9). Retrieved from https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2011WR011005. doi:https://doi.org/10.1029/2011WR011005
Olmanson, L. G., Brezonik, P. L., & Bauer, M. E. (2015). Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and Limitations of Current and Upcoming Satellite Systems. In T. Younos & T. E. Parece (Eds.), Advances in Watershed Science and Assessment (pp. 111-140). Cham: Springer International Publishing.
Ouyang, W., Hao, F. H., Wang, X. L., & Cheng, H. G. (2008). Nonpoint source pollution responses simulation for conversion cropland to forest in mountains by SWAT in China. Environ Manage, 41(1), 79-89. doi:10.1007/s00267-007-9028-8
Pahlevan, N., & Schott, J. R. (2013). Leveraging EO-1 to Evaluate Capability of New Generation of Landsat Sensors for Coastal/Inland Water Studies. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(2), 360-374. doi:10.1109/JSTARS.2012.2235174
Pahlevan, N., Schott, J. R., Franz, B. A., Zibordi, G., Markham, B., Bailey, S., . . . Strait, C. M. (2017). Landsat 8 remote sensing reflectance (Rrs) products: Evaluations, intercomparisons, and enhancements. Remote Sensing of Environment, 190, 289-301.
Pahlevan, N., Wei, J., Schaaf, C. B., & Schott, J. R. (2014, 13-18 July 2014). Evaluating radiometric sensitivity of Landsat 8 over coastal/inland waters. Paper presented at the 2014 IEEE Geoscience and Remote Sensing Symposium.
Pahlow, M., & Oschlies, A. (2009). Chain model of phytoplankton P, N and light colimitation. Marine Ecology Progress Series, 376, 69-83. Retrieved from https://www.int-res.com/abstracts/meps/v376/p69-83/.
Phiri, D., Simwanda, M., Salekin, S., Nyirenda, V. R., Murayama, Y., & Ranagalage, M. (2020). Sentinel-2 Data for Land Cover/Use Mapping: A Review. Remote Sensing, 12(14), 2291. Retrieved from https://www.mdpi.com/2072-4292/12/14/2291.
Portney, L. G., & Watkins, M. P. (2000). Foundations of Clinical Research: Applications to Practice: Prentice Hall Health.
Shyu, G.-S., Cheng, B.-Y., & Fang, W.-T. (2012). The Effect of Developing a Tunnel across a Highway on the Water Quality in an Upstream Reservoir Watershed Area—A Case Study of the Hsuehshan Tunnel in Taiwan. International journal of environmental research and public health, 9, 3344-3353. doi:10.3390/ijerph9093344
Su, T.-C. (2017). A study of a matching pixel by pixel (MPP) algorithm to establish an empirical model of water quality mapping, as based on unmanned aerial vehicle (UAV) images. International Journal of Applied Earth Observation and Geoinformation, 58, 213-224. Retrieved from https://www.sciencedirect.com/science/article/pii/S0303243417300375. doi:https://doi.org/10.1016/j.jag.2017.02.011
Su, T.-C., & Chou, H.-T. (2015). Application of Multispectral Sensors Carried on Unmanned Aerial Vehicle (UAV) to Trophic State Mapping of Small Reservoirs: A Case Study of Tain-Pu Reservoir in Kinmen, Taiwan. Remote Sensing, 7(8), 10078-10097. Retrieved from https://www.mdpi.com/2072-4292/7/8/10078.
Thornton, K. W., Kimmel, B. L., & Payne, F. E. (1990). Reservoir limnology : ecological perspectives. New York: Wiley.
van Breemen, N., Burrough, P. A., Velthorst, E. J., van Dobben, H. F., de Wit, T., Ridder, T. B., & Reijnders, H. F. R. (1982). Soil acidification from atmospheric ammonium sulphate in forest canopy throughfall. Nature, 299(5883), 548-550. Retrieved from https://doi.org/10.1038/299548a0. doi:10.1038/299548a0
Vanhellemont, Q., & Ruddick, K. (2014). Turbid wakes associated with offshore wind turbines observed with Landsat 8. Remote Sensing of Environment, 145, 105-115. Retrieved from ://WOS:000335113200010. doi:10.1016/j.rse.2014.01.009
Vanhellemont, Q., & Ruddick, K. (2015). Advantages of high quality SWIR bands for ocean colour processing: Examples from Landsat-8. Remote Sensing of Environment, 161, 89-106. Retrieved from ://WOS:000351654500007. doi:10.1016/j.rse.2015.02.007
Vanhellemont, Q., & Ruddick, K. (2021). Atmospheric correction of Sentinel-3/OLCI data for mapping of suspended particulate matter and chlorophyll-a concentration in Belgian turbid coastal waters. Remote Sensing of Environment, 256, 112284. Retrieved from https://www.sciencedirect.com/science/article/pii/S003442572100002X. doi:https://doi.org/10.1016/j.rse.2021.112284
Wang, D., Ronghua, M., Xue, K., & Li, J. (2019). Improved atmospheric correction algorithm for Landsat 8–OLI data in turbid waters: a case study for the Lake Taihu, China. Optics Express, 27(20), A1400-A1418. Retrieved from http://www.opticsexpress.org/abstract.cfm?URI=oe-27-20-A1400. doi:10.1364/OE.27.0A1400
Woodcock, C., Allen, R., Anderson, M., Belward, A., Bindschadler, R., Cohen, W., . . . Wynne, R. (2008). Free Access to Landsat Imagery. Science (New York, N.Y.), 320, 1011. doi:10.1126/science.320.5879.1011a
World Health, O. (2017). Water quality and health - review of turbidity: information for regulators and water suppliers. Retrieved from Geneva: https://apps.who.int/iris/handle/10665/254631
Xu, Z. X., Pang, J. P., Liu, C. M., & Li, J. Y. (2009). Assessment of runoff and sediment yield in the Miyun Reservoir catchment by using SWAT model. Hydrological Processes, 23(25), 3619-3630. Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.7475. doi:https://doi.org/10.1002/hyp.7475
Yang, M. D., Sykes, R. M., & Merry, C. J. (2000). Estimation of algal biological parameters using water quality modeling and SPOT satellite data. Ecological Modelling, 125(1), 1-13. Retrieved from https://www.sciencedirect.com/science/article/pii/S0304380099000654. doi:https://doi.org/10.1016/S0304-3800(99)00065-4
Yip, H. D., Johansson, J., & Hudson, J. J. (2015). A 29-year assessment of the water clarity and chlorophyll-a concentration of a large reservoir: Investigating spatial and temporal changes using Landsat imagery. Journal of Great Lakes Research, 41, 34-44. Retrieved from ://WOS:000367359900004. doi:10.1016/j.jglr.2014.11.022
Zilberg, B. (1966). Gastroenteritis in Salisbury. European children--a five-year study. Cent Afr J Med, 12(9), 164-168.
王鑫. (1986). 遙測研習班講義 (初版 ed.): [出版者不詳].
行政院環境保護署. (2020). 民國108年環境水質監測年報. Retrieved from file:///C:/Users/Win10/Downloads/2019%E5%B9%B4%E7%92%B0%E5%A2%83%E6%B0%B4%E8%B3%AA%E7%9B%A3%E6%B8%AC%E5%B9%B4%E5%A0%B1%20(3).pdf
張智華. (2008). 非點源污染負荷模式及水質生光模式之結合與應用. (博士), 國立成功大學, 台南市. Retrieved from https://hdl.handle.net/11296/rvu92z
黃兆慧. (2002). 台灣的水庫: 遠足文化事業有限公司.
經濟部水利署. (2019). 2019年台灣水文環境情勢專刊.
雷祖强. (2006). 遙感探測理論與分析實務: 文魁資訊股份有限公司.
電子全文 電子全文(網際網路公開日期:20241222)
連結至畢業學校之論文網頁點我開啟連結
註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top