簡易檢索 / 詳目顯示

研究生: 鐘浩齊
Chung, Hao-Chi
論文名稱: 利用空間資訊技術進行紅樹林藍碳量估算
Estimation of blue carbon in mangroves based on spatial information technology
指導教授: 張國楨
Chang, Kuo-Chen
口試委員: 張國楨
Chang, Kuo-Chen
譚智宏
Tan, Zhi-Hong
陳俊愷
Chen, Chun-Kai
口試日期: 2022/01/15
學位類別: 碩士
Master
系所名稱: 地理學系空間資訊碩士在職專班
Department of Geography_Continuing Education Master's Program of Geospatial Information Science
論文出版年: 2022
畢業學年度: 110
語文別: 中文
論文頁數: 57
中文關鍵詞: 衛星影像支持向量機(SVM)常態化植生指標(NDVI)紅樹林藍碳
英文關鍵詞: Satellite image, Support vector machine, Normalized difference vegetation index, Mangrove, Blue carbon
研究方法: 調查研究田野調查法
DOI URL: http://doi.org/10.6345/NTNU202200074
論文種類: 學術論文
相關次數: 點閱:211下載:26
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
  • 聯合國環境署於2009年公布的藍碳報告顯示藍碳海岸生態系統中鹽澤、紅樹林及海草床儲存了大量的藍碳。這些藍碳的面積相對於陸地森林面積相比之下少了許多,但卻蘊藏著是兩倍以上之多的高效固碳。然而這些藍碳每年以34萬至98萬公頃的速度消失,當這些環境被破壞時,估計每年釋放多達10.2億噸二氧化碳,並成為溫室氣體的來源之一。紅樹林是藍碳中地上部密度最高的,更提供供給、支持、調節、文化生態系統服務,持續的推動環境監測、資源調查以及環境教育在紅樹林上是有助於人類福祉與生態系統。
    淡水河流域有兩個重要的溼地分別為淡水河紅樹林自然保留區和關渡自然保留區,有大範圍的紅樹林出現,但其自然保留區主要保護的對象分別不同,淡水河紅樹林自然保留區主要為保護水筆仔,關渡自然保留區主要為保護水鳥。本研究使用1984至2021年使用Landsat-5、Formosat-2、Landsat-8及Sentinel-2四顆不同衛星載具,使用遙測技術利用光譜在不同地物有不同的光譜之特性作為判釋,本研究使用監督式分類支持向量機(SVM)演算法探討紅樹林分布,並透過影像相減法探討兩個自然保留區近三十年多時序的紅樹林變遷之情形,依照分類後的影像計算紅樹林覆蓋之面積,結合現地調查生物數據,推估藍碳儲存於活株的紅樹林的樹體中的量。
    本研究成果顯示,淡水河紅樹林自然保留區和關渡自然保留區的紅樹林從1984至2021年的有明顯的變遷之情形,且面積也有成長的趨勢,淡水河紅樹林自然保留區的紅樹林從40.9公頃變遷到49.81公頃的範圍,關渡自然保留區從沼澤地發現紅樹林1.4公頃變遷到39.21公頃的範圍。淡水河紅樹林自然保留區的紅樹林樹體碳儲存有49,216噸的藍碳,關渡自然保留區紅樹林樹體碳儲存有45,109噸的藍碳,顯示有大量的碳儲存於紅樹林樹體之中。

    In 2009, the United Nations Environment Programme (UNEP) published the Blue Carbon Report and the results showed that a large amount of blue carbon is stored of the coastal ecosystem in the three habitats include salt marshes, mangroves, seagrass beds. The area of these blue carbons is much smaller than that of terrestrial forests, but they contain more than twice as much efficient carbon sequestration. But there are a lot of blue carbon disappear at a rate of 340,000 to 980,000 hectares per year, and when these environments are destroyed, it is estimated that as much as 1.02 billion tons of carbon dioxide is released each year and becomes a source of greenhouse gases. Mangroves have the highest density above ground in blue carbon, and provide supply, support, regulation, and cultural ecosystem services. Continuous promotion of environmental monitoring, resource surveys, and environmental education in mangroves contributes to human well-being and ecosystems.
    There are two important wetlands Danshuei River Mangrove Nature Reserve (DRMNR) and Guandu Nature Reserve (GNR) in Danshuei Rive. There are a large range of mangroves, but the main protection objects of their natural reserves are different. The main protection of Kandelia candel(L.) Druce in DRMNR and the primary protection of waterfowl in GNR. This study uses four different satellites vehicle by Landsat-5, Formosat-2, Landsat-8 and Sentinel-2 during from 1984 to 2021. Using telemetry technology to use the spectral characteristics of different ground objects as a judgment, this study uses a supervised classification support vector machine (SVM) explore the distribution of mangroves. Over the past 30 years, the changes of mangrove forests in the two natural reserves were discussed through image subtraction. The area covered by mangroves was calculated according to the classified images, and the biological data of the field survey was used to estimate the storage of blue carbon in living of mangrove trees.
    The results of this research, the DRMNR and GNR mangroves are showing significant changes during from 1972 to 2021, and recorded a growing trend in area. The DRMNR has changed from 40.9 hectares to 49.81 hectares; and the GNR has expanded from the original marshland to 39.21 hectares, while the mangrove plants in the DRMNR store 49,216 tons of carbon, while the GNR store 45,109 tons of carbon, show that a large amount of carbon stored in mangrove trees.

    第一章 緒論 1 第一節 研究動機 1 第二節 研究目的 3 第三節 研究範圍 4 第四節 研究限制 5 第二章 文獻回顧 6 第一節 紅樹林理論與相關研究 6 第二節 遙測衛星理論與相關研究 16 第三章 研究方法與材料 28 第一節 研究資料取得及處理 28 第二節 研究流程 37 第四章 研究結果與討論 38 第一節 衛星遙測技術探討紅樹林分布 38 第二節 影像分類紅樹林變遷情形 42 第三節 紅樹林面積及藍碳儲存量 45 第五章 結論與建議 49 第一節 結論 49 第二節 建議 49 參考文獻 50

    Alongi D M, 2002. Present state and future of the world’s mangrove forests[J]. Environmental conservation, 29:331-349.
    Agoramoorthy, G., Chen, F.-A., & Hsu, M. J. (2008). Threat of heavy metal pollution in halophytic and mangrove plants of Tamil Nadu, India. Environmental Pollution, 155(2), 320-326.
    Alongi, D. M. (2012). Carbon sequestration in mangrove forests. Carbon management, 3(3), 313-322.
    Arcos, J. M., Bécares, J., Villero, D., Brotons, L., Rodríguez, B., & Ruiz, A. (2012). Assessing the location and stability of foraging hotSPOTs for pelagic seabirds: an approach to identify marine Important Bird Areas (IBAs) in Spain. Biological Conservation, 156, 30-42.
    Barbier, B., Acreman, M., Barbier, E. B., & Knowler, D. (1997). Ramsar Convention Bureau.
    Blasco, F., Aizpuru, M., & Gers, C. (2001). Depletion of the mangroves of Continental Asia. Wetlands Ecology and Management, 9(3), 255-266.
    Boyd, J., & Banzhaf, S. (2007). What are ecosystem services? The need for standardized environmental accounting units. Ecological economics, 63(2-3), 616-626.
    Cao, R., Chen, Y., Shen, M., Chen, J., Zhou, J., Wang, C., & Yang, W. (2018). A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay filter. Remote sensing of Environment, 217, 244-257.
    Carugati, L., Gatto, B., Rastelli, E., Martire, M. L., Coral, C., Greco, S., & Danovaro, R. (2018). Impact of mangrove forests degradation on biodiversity and ecosystem functioning. Scientific reports, 8(1), 1-11.
    Chen, P.-C., Chang, P.-H., Shih, C.-H., Chu, T.-J., Lu, Y.-M., Kao, W.-C., & Shih, Y.-J. (2020). Effects of Phytoremediation Technology on Purification of Eutrophic Water by Micro-wetland System in Nanzaigou Stream, Taiwan. Education and Awareness of Sustainability: Proceedings of the 3rd Eurasian Conference on Educational Innovation 2020 (ECEI 2020),
    Chipman, J. W., Lillesand, T. M., Schmaltz, J. E., Leale, J. E., & Nordheim, M. J. (2004). Mapping lake water clarity with Landsat images in Wisconsin, USA. Canadian journal of remote sensing, 30(1), 1-7.
    Chowdhury, M. S. N., Hossain, M. S., Mitra, A., & Barua, P. (2011). Environmental functions of the Teknaf Peninsula mangroves of Bangladesh to communicate the values of goods and services. Mesopot J Mar Sci, 26(1), 79-97.
    Croxall, J. P., Butchart, S. H., Lascelles, B., Stattersfield, A. J., Sullivan, B., Symes, A., & Taylor, P. (2012). Seabird conservation status, threats and priority actions: a global assessment. Bird Conservation International, 22(1), 1-34.
    DeFries, R., Achard, F., Brown, S., Herold, M., Murdiyarso, D., Schlamadinger, B., & de Souza Jr, C. (2007). Earth observations for estimating greenhouse gas emissions from deforestation in developing countries. Environmental science & policy, 10(4), 385-394.
    Diniz, C., Cortinhas, L., Nerino, G., Rodrigues, J., Sadeck, L., Adami, M., & Souza-Filho, P. W. M. (2019). Brazilian mangrove status: Three decades of satellite data analysis. Remote Sensing, 11(7), 808.
    Donato, D. C., Kauffman, J. B., Murdiyarso, D., Kurnianto, S., Stidham, M., & Kanninen, M. (2011). Mangroves among the most carbon-rich forests in the tropics. Nature geoscience, 4(5), 293-297.
    Dudley, N. (2008). Guidelines for applying protected area management categories. Iucn.
    Friess, D. A., Rogers, K., Lovelock, C. E., Krauss, K. W., Hamilton, S. E., Lee, S. Y., Lucas, R., Primavera, J., Rajkaran, A., & Shi, S. (2019). The state of the world's mangrove forests: past, present, and future. Annual Review of Environment and Resources, 44, 89-115.
    Friess, D. A., & Webb, E. L. (2014). Variability in mangrove change estimates and implications for the assessment of ecosystem service provision. Global Ecology and Biogeography, 23(7), 715-725.
    Gedan K B,Silliman B,Bertness M,2009. Centuries of human-driven change in salt marsh ecosystems[J]. Marine Science, 1:117-141.
    Garcia, K. B., Malabrigo, P. L., & Gevaña, D. T. (2014). Philippines’ mangrove ecosystem: status, threats and conservation. In Mangrove Ecosystems of Asia (pp. 81-94). Springer.
    Geldmann, J., Coad, L., Barnes, M., Craigie, I. D., Hockings, M., Knights, K., Leverington, F., Cuadros, I. C., Zamora, C., & Woodley, S. (2015). Changes in protected area management effectiveness over time: A global analysis. Biological Conservation, 191, 692-699.
    Giacinto, G., Roli, F., & Bruzzone, L. (2000). Combination of neural and statistical algorithms for supervised classification of remote-sensing images. Pattern Recognition Letters, 21(5), 385-397.
    Gilman, E. L., Ellison, J., Duke, N. C., & Field, C. (2008). Threats to mangroves from climate change and adaptation options: a review. Aquatic botany, 89(2), 237-250.
    Gilman, E. L., Ellison, J., Jungblut, V., Van Lavieren, H., Wilson, L., Areki, F., Brighouse, G., Bungitak, J., Dus, E., & Henry, M. (2006). Adapting to Pacific Island mangrove responses to sea level rise and climate change. Climate Research, 32(3), 161-176.
    Giri, C., Ochieng, E., Tieszen, L. L., Zhu, Z., Singh, A., Loveland, T., Masek, J., & Duke, N. (2011). Status and distribution of mangrove forests of the world using earth observation satellite data. Global Ecology and Biogeography, 20(1), 154-159.
    Hall, P., Sheather, S. J., Jones, M., & Marron, J. S. (1991). On optimal data-based bandwidth selection in kernel density estimation. Biometrika, 78(2), 263-269.
    Hauser, L. T., Vu, G. N., Nguyen, B. A., Dade, E., Nguyen, H. M., Nguyen, T. T. Q., Le, T. Q., Vu, L. H., Tong, A. T. H., & Pham, H. V. (2017). Uncovering the spatio-temporal dynamics of land cover change and fragmentation of mangroves in the Ca Mau peninsula, Vietnam using multi-temporal SPOT satellite imagery (2004–2013). Applied geography, 86, 197-207.
    Hockings, M. (2006). Evaluating Effectiveness: A framework for assessing management effectiveness of protected areas. IUCN.
    Hockings, M., James, R., Stolton, S., Dudley, N., Mathur, V., Makombo, J., Courrau, J., & Parrish, J. (2008). Enhancing our Heritage Toolkit: Assessing management effectiveness of natural World Heritage sites.
    Hopkins, C. R., Burns, N. M., Brooker, E., Dolman, S., Devenport, E., Duncan, C., & Bailey, D. M. (2020). Evaluating whether MPA management measures meet ecological principles for effective biodiversity protection. Acta Oecologica, 108, 103625.
    Howard, J., Hoyt, S., Isensee, K., Telszewski, M., & Pidgeon, E. (2014). Coastal blue carbon: methods for assessing carbon stocks and emissions factors in mangroves, tidal salt marshes, and seagrasses.
    Iiames, J., Congalton, R., Pilant, A., & Lewis, T. (2008). Leaf area index (LAI) change detection analysis on Loblolly pine (Pinus taeda) following complete understory removal. Photogrammetric Engineering & Remote Sensing, 74(11), 1389-1400.
    Kathiresan, K., & Bingham, B. L. (2001). Biology of mangroves and mangrove ecosystems.
    Kathiresan, K., & Rajendran, N. (2005). Coastal mangrove forests mitigated tsunami. Estuarine, Coastal and Shelf Science, 65(3), 601-606.
    Kauffman, J. B., Heider, C., Norfolk, J., & Payton, F. (2014). Carbon stocks of intact mangroves and carbon emissions arising from their conversion in the Dominican Republic. Ecological Applications, 24(3), 518-527.
    Khan, M. N. I., Suwa, R., & Hagihara, A. (2009). Biomass and aboveground net primary production in a subtropical mangrove stand of Kandelia obovata (S., L.) Yong at Manko Wetland, Okinawa, Japan. Wetlands Ecology and Management, 17(6), 585-599.
    King S E, Lester J N,1995. The value of salt marsh as a sea defence[J]. Marine Pollution Bulletin, 30:180-189.
    Klemas, V. (2013). Remote sensing of emergent and submerged wetlands: an overview. International journal of remote sensing, 34(18), 6286-6320.
    Landis, J. R., & Koch, G. G. (1977). An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers. Biometrics, 363-374.
    Leverington, F., Costa, K. L., Pavese, H., Lisle, A., & Hockings, M. (2010). A global analysis of protected area management effectiveness. Environmental Management, 46(5), 685-698.
    Lyon, J. G., Yuan, D., Lunetta, R. S., & Elvidge, C. D. (1998). A change detection experiment using vegetation indices. Photogrammetric engineering and remote sensing, 64(2), 143-150.
    Matthews, G. V. T. (1993). The Ramsar Convention on Wetlands: its history and development.
    Mcleod, E., Chmura, G. L., Bouillon, S., Salm, R., Björk, M., Duarte, C. M., Lovelock, C. E., Schlesinger, W. H., & Silliman, B. R. (2011). A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Frontiers in Ecology and the Environment, 9(10), 552-560.
    Mejía-Rentería, J. C., Castellanos-Galindo, G. A., Cantera-Kintz, J. R., & Hamilton, S. E. (2018). A comparison of Colombian Pacific mangrove extent estimations: Implications for the conservation of a unique Neotropical tidal forest. Estuarine, Coastal and Shelf Science, 212, 233-240.
    Murdiyarso, D., Purbopuspito, J., Kauffman, J. B., Warren, M. W., Sasmito, S. D., Donato, D. C., Manuri, S., Krisnawati, H., Taberima, S., & Kurnianto, S. (2015). The potential of Indonesian mangrove forests for global climate change mitigation. Nature Climate Change, 5(12), 1089-1092.
    Murray, B. C., Pendleton, L., Jenkins, W. A., & Sifleet, S. (2011). Green payments for blue carbon: economic incentives for protecting threatened coastal habitats. Green payments for blue carbon: economic incentives for protecting threatened coastal habitats.
    Nagelkerken, I., Blaber, S., Bouillon, S., Green, P., Haywood, M., Kirton, L., Meynecke, J.-O., Pawlik, J., Penrose, H., & Sasekumar, A. (2008). The habitat function of mangroves for terrestrial and marine fauna: a review. Aquatic botany, 89(2), 155-185.
    Nellemann, C., & Corcoran, E. (2009). Blue carbon: the role of healthy oceans in binding carbon: a rapid response assessment. UNEP/Earthprint.
    Perumal, K., & Bhaskaran, R. (2010). Supervised classification performance of multispectral images. arXiv preprint arXiv:1002.4046.
    Pham, L. T., & Brabyn, L. (2017). Monitoring mangrove biomass change in Vietnam using SPOT images and an object-based approach combined with machine learning algorithms. ISPRS Journal of Photogrammetry and Remote Sensing, 128, 86-97.
    Phillips, A., & Union, W. C. (2002). Management guidelines for IUCN category V protected areas: Protected landscapes/seascapes (Vol. 9). IUCN--the World Conservation Union.
    Rajkaran, A., Adams, J. B., & du Preez, D. R. (2004). A method for monitoring mangrove harvesting at the Mngazana estuary, South Africa. African Journal of Aquatic Science, 29(1), 57-65.
    Rajpar, M. N., & Zakaria, M. (2014). Mangrove fauna of Asia. In Mangrove Ecosystems of Asia (pp. 153-197). Springer.
    Rouse, B. T., & Babiuk, L. A. (1974). Host responses to infectious bovine rhinotracheitis virus: III. Isolation and immunologic activities of bovine T lymphocytes. The Journal of Immunology, 113(5), 1391-1398.
    Sandilyan, S., & Kathiresan, K. (2015). Mangroves as bioshield: an undisputable fact. Ocean & coastal management, 103, 94-96.
    Sasmito, S. D., Taillardat, P., Clendenning, J. N., Cameron, C., Friess, D. A., Murdiyarso, D., & Hutley, L. B. (2019). Effect of land‐use and land‐cover change on mangrove blue carbon: A systematic review. Global change biology, 25(12), 4291-4302.
    Schowengerdt, R. (1997). Remote sensing: methods and models for image processing. In: Academic Press, New York, New York, USA.
    Shih, C. H., Kuo, Y. Y. Chu, T. J. Chou, W. C. Chang, W. T., and Lee, Y. C., 2011. Eco-environmental impact assessment of artificial beach nourishment on benthic invertebrate community at Anping Coast, Taiwan. China Ocean Engineering. 25(2): 1~11.
    Shih, C. H, 2011. Artificial habitat restoration model in pre-leisure coastal areas. Institute of Fisheries Science, College of Life Science, National Taiwan University. PhD. Thesis. P141.
    Slobodian, L., & Badoz, L. (2019). Tangled roots and changing tides: mangrove governance for conservation and sustainable use. In: WWF Germany, Berlin, Germany and IUCN, Gland, Switzerland, Berlin, Germany.
    Tucker, D. M., Watson, R. T., & Heilman, K. M. (1977). Discrimination and evocation of affectively intoned speech in patients with right parietal disease. Neurology, 27(10), 947-947.
    Tuia, D., Volpi, M., Copa, L., Kanevski, M., & Munoz-Mari, J. (2011). A survey of active learning algorithms for supervised remote sensing image classification. IEEE Journal of Selected Topics in Signal Processing, 5(3), 606-617.
    Veenvliet, J. K., & Sovinc, A. (2009). Protected area management effectiveness in Slovenia Final report of the RAPPAM analysis.
    Veettil, B. K., Ward, R. D., Quang, N. X., Trang, N. T. T., & Giang, T. H. (2019). Mangroves of Vietnam: Historical development, current state of research and future threats. Estuarine, Coastal and Shelf Science, 218, 212-236.
    Virgulino-Júnior, P. C. C., Carneiro, D. N., Nascimento Jr, W. R., Cougo, M. F., & Fernandes, M. E. B. (2020). Biomass and carbon estimation for scrub mangrove forests and examination of their allometric associated uncertainties. PloS one, 15(3), e0230008.
    Walsh, G. E. (1974). Mangroves: a review. Ecology of halophytes, 51-174.
    Wang, L., Jia, M., Yin, D., & Tian, J. (2019). A review of remote sensing for mangrove forests: 1956–2018. Remote sensing of Environment, 231, 111223.
    Yang, Z., Dan, T., & Yang, Y. (2018). Multi-temporal remote sensing image registration using deep convolutional features. IEEE Access, 6, 38544-38555.
    邵廣昭(1998)。海洋生態學。臺北市。文海環境科學出版。
    陸彥伊(2017)。水筆仔衍生菌化學成分研究. 高雄醫學大學天然藥物研究所碩士班學位論文, 1-200.
    陳怡旴(1997)。水筆仔族群內的基因流傳研究. (碩士), 國立臺灣師範大學, 臺北市
    薛怡珍(2005)。地景動態變遷預測模式之研究-以台大實驗林和社地區為例. (博士), 國立臺灣大學, 臺北市.
    吳欣恂(2021)。水筆仔與海茄苳碳收支模式. (碩士), 國立中興大學, 台中市.
    盧道杰、施上栗、黃國文、趙芝良、薛美莉、羅暐菱(2012)。淡水河紅樹林, 挖子尾與關渡三個自然保留區經營管理效能 的系統評量. 國家公園學報.
    許偉斌(2020)。淡水河水筆仔胎生苗移流及延散特性研究. 臺灣大學土木工程學研究所學位論文, 1-131.
    王勝民(2003)。新竹海岸消波塊群之週遭底棲生物空間分佈之研究. (碩士), 中華大學, 新竹市.
    謝蕙蓮、黃守忠、李坤瑄、陳章波(1993)。潮間帶底棲生態調查法。生物科學(36),頁 71-80。
    陳莉、魏曉萍、王泰盛(2004)。監督式分類方法於遙測影像判釋之研究. 農業工程學報, 50(3), 59-70.
    莊明軒(2020)。台中地區土地利用與都市熱島效應之時空變遷分析. (碩士), 國立臺灣師範大學, 臺北市.
    陳俊愷(2011)。影像特徵點萃取與匹配應用於福衛二號影像幾何糾正. (博士), 國立臺灣師範大學, 臺北市.
    張桂祥(1999)。臺灣西南海域海桶類之時空分佈. (碩士), 國立中山大學, 高雄市.
    劉正千(2009)。福爾摩沙衛星二號在全球災害緊急應變與地球環境監測應用之回顧. 國研科技(23), 61-71.
    陳建同(2009)。應用影像分段技術與多時段衛星影像於崩塌地植生復育成效分析研究. (碩士), 國立成功大學, 台南市.
    周天穎(2001)。地理資訊系統理論與實務, 儒林圖書有限公司.
    潘國樑、張國楨(2014)。遙測影像判釋原理, 五南圖書出版有限公司.
    陳信安(2007)。衛星影像幾何校正控制點自動萃取與匹配之研究. (碩士), 國立臺灣大學, 臺北市.
    施學延(2010)。衛星雷達影像反投影定位與有理函數模式. (碩士), 國立中央大學, 桃園縣.
    王素芬、余佳樺、劉雅婷(2014)。衛星影像前處理對植生變遷偵測影響之探討. 地理學報(75), 81-99.
    陳姜琦(2002)。應用衛星遙測於區域蒸發散量之估算. (碩士), 國立成功大學, 台南市.
    張國楨、田應平、施孝謙(2012)。以多時期與 PCA+ NDVI 法改善地物分類之正確性與完整性. 地理研究(57), 49-60.
    謝漢欽(1996)。應用 SPOT 衛星影像與地理資訊於林地土地利用型綠度分析. 臺灣林業科學, 11(1), 77-86.
    賴奕璇(2017)。以遙測影像探討香山溼地紅樹林清除變遷之研究. (碩士), 中華大學, 新竹市.
    張國楨、曾露儀(2009)。應用福衛二號衛星影像於 淡水河紅樹林生態變遷監測. 國研科技, (23), 38-44.
    陳俊愷、張國楨(2010)。福衛二號立體像對產製數值地表模型精度分析. 環境與世界(21), 55-72.
    許立志(2009)。關渡自然保留區紅樹林變遷之研究. (碩士), 國立臺灣大學, 臺北市.
    曾文政(2009)。以遙感探測暨地理資訊系統應用於屏東地區紅樹林碳吸存之可行性研究. (碩士), 國立屏東科技大學, 屏東縣.
    陳彥穎(2012)。多尺度遙測影像應用於紅樹林調查-以台江國家公園為例. (碩士), 國立成功大學, 台南市.
    楊樹森、張登凱、李沛沂(2014)。新竹香山濕地紅樹林擴張歷程及其可能因素探討. 濕地學刊, 3(1), 17-26.
    沈淑敏、陳映璇(2010)。經建版地形圖和像片基本圖在濱線繪製上的應用與限制. 地理研究, 53, 71-89.
    方偉達(2012)。築夢生態淡水河, 荒野保護協會.
    郭一羽、朱達仁、施君翰(2012)。紅樹林底棲生物棲地模式之建立. 濕地學刊, 1(1), 1-10.
    謝蕙蓮、施上粟(2006)。淡水河系紅樹林溼地疏伐可行性評估研究(1/2)。經濟部水利署水利規劃試驗所委託研究報告。260 頁。
    謝蕙蓮、施上粟(2007)。淡水河系紅樹林溼地疏伐可行性評估研究(2/2)。經濟部水利署水利規劃試驗所委託。330 頁。
    薛美莉、林幸助(2015)。臺灣濕地生態補償之執行與推動. 濕地學刊, 4(1), 22-30.
    劉棠瑞、陳建鑄(1960)。臺灣木本植物圖誌. 國立臺灣大學農學院.
    薛美莉(1995)。消失的溼地森林-記臺灣的紅樹林。南投縣:農委會特有生物研究中心。
    李建堂(2003)。淡水河口水筆仔紅樹林分布變遷之研究。華岡地理學報(16),頁 59-69。
    林俊全、張菀文(1999)。紅樹林的特性與淡水河紅樹林保育研究. 地景保育通訊(11), 27-29.
    周憲德、林柏青、何良勝、李璟芳、陳沛蓉、鄭年佑(2014)。淡水河河口段之河床水理特性及沙嘴變遷研究. 港灣季刊, (99), 28-41.
    周憲德、林柏青、何良勝、鄭年佑、黃郅軒(2015)。淡水河河口沙嘴風吹砂及水下河床沙丘特性研究. 港灣季刊, (101), 16-23.
    盧道杰、陳維立、趙芝良、賴欣欣、徐霈馨、裴家騏、何立德(2012)。保護(留)區經營管理效能評估計畫初期成果。臺灣林業.
    陳柏宏(2014)。淡水河紅樹林及草澤植物的碳儲存量與碳收支. 中興大學生命科學系所學位論文, 1-141.
    施君翰(2018)。應用遙測影像技術評估國土計畫法對南臺灣海岸濕地與漁村產業生態系統服務衝擊之影響探討。科技部補助專題研究計畫成果報告.
    施君翰(2021)。應用遙測影像技術於臺南市七股區國土計畫土地變遷評估及海岸產業發展分區管理策略之研究。科技部補助專題研究計畫成果報告.

    下載圖示
    QR CODE