請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/83674完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳惠美(Hui-Mei Chen) | |
| dc.contributor.author | Yi-Ting Jiang | en |
| dc.contributor.author | 蔣伊婷 | zh_TW |
| dc.date.accessioned | 2023-03-19T21:13:49Z | - |
| dc.date.copyright | 2022-08-18 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-08-15 | |
| dc.identifier.citation | 1.王永珍(2008)。河川景觀暨生態環境規劃。台北:明文書局。 2.王志弘、林純秀(2013)。都市自然的治理與轉化 新北市二重疏洪道。台灣社會研究季刊,(92),35-71。 3.王志弘、黃若慈、李涵茹(2014)。臺北都會區水岸意義與功能的轉變。地理學報,(74),63-86。 4.王啟東(2012)。淡水河水系之永續發展及綠色旅遊之探討。休閒觀光與運動健康學報,2(2),1-17。 5.中山休閒農業區,(2021)。中山風光。上網日期:2021年07月28日。網址:http://www.jhongshan.org.tw/WebMaster/?section=3。 6.平雅朋、許益彰、陳寬裕(2020)。活動熱情、遊憩專門化與心流體驗關係之研究:以山溪釣者為例。人文社會科學研究,14(2),1-23。 7.內政部營建署(2017)。淡水河域重要濕地(國家級)保育利用計畫。上網日期:2022年07月28日。網址:https://reurl.cc/MNdYZX。 8.內政部營建署(2017)。淡水河域重要濕地(國家級)保育利用計畫圖。上網日期:2022年07月28日。網址:https://reurl.cc/NR65rn。 9.朱達仁、鄭裕仁、施君翰(2010)。自然旅遊地遊憩潛力空間分析。地理資訊系統季刊,4(2),21-25。 10.行政院農業委員會(2022)。主管法規查詢系統。上網日期:2022年06月24日。網址:https://law.coa.gov.tw/glrsnewsout/LawContent.aspx?id=FL052262。 11.行政院環境保護署(2017)。全國環境水質監測資訊網。上網日期:2020年12月01日。網址:https://wq.epa.gov.tw/EWQP/zh/Default.aspx。 12.行政院交通部觀光局(2022)。國人旅遊調查。上網日期:2020年12月01日。網址:https://admin.taiwan.net.tw/FileUploadCategoryListC003340.aspx?CategoryID=7b8dffa9-3b9c-4b18-bf05-0ab402789d59。 13.全國法規資料庫(2021)。水利法施行細則。上網日期:2021年02月20日,網址:https://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=J0110002。 14.?宗鴻、游顯宗(2008)。溯溪??模式之研究-以溯溪俱?部??。運動與遊憩研究,3(2),124-142。 15.李孫榮、甘其銓、萬孟瑋、黃俊穎、蔡明穎、蔣志政(2008)。現場電解消毒技術控制遊憩用水水質之研究-以溫泉及SPA用水?例,嘉南學報(科技類),(34),98-110。 16.李素馨、侯錦雄、林宗賢、黃章展、葉源鎰(2014)。休閒遊憩行為。台北:華都文化事業有限公司。 17.林孟龍、劉瓊嬬(2020)。以社群平台自發性地理資訊探討觀光遊憩資源的空間特性:淡水老街的個案研究。真理觀光學報,17,45-57。 18.林朝欽、Driver, B. L.、Brown, P. T.、Stankey, G. H.、Gregoire, T. G.(1989)。遊憩機會序列規劃系統:演進、基本觀念及研究需要。戶外遊憩研究,2(3),37-44。 19.林敬妤、廖學誠(2006)。宜蘭河溪廊道的整治與管理-環境識覺分析。中華水土保持學報,37(3),291-304。 20.侯錦雄、郭彰仁(2003)。關渡、高美、七股濕地生態遊憩動機與旅遊特性之比較。觀光研究學報,9(1),1-18。 21.洪詩涵、張俊彥(2020)。建構感知親生命性設計於環境體驗之概念架構。造園景觀學報,24(4),41-71。 22.郭彰仁、蘇麗思、韓耀期(2015)。公共藝術支應性知覺與觀賞者互動行為傾向關係之研究-以台中市綠園道周邊為例。建築學報,(92),61-80。 23.陳本源、黃耀祿、蘇細煌、陳亮元(2010)。朴子溪圍潭溼地復育工程對景觀生態之影響。造園景觀學報,16(3),1-31。 24.陳秋政(2016)。臺中市筏子溪流域治理網絡發展之研究。組織與管理,9(2),73-116。 25.陳晉琪、姜正國(2016)。初探流量變化對河流景觀之視覺偏好度之影響。華梵藝術與設計學報,(11),53-62。 26.陳培源(2008)。台灣地質。台北:臺灣省應用地質技師公會出版。 27.陳樹群、安軒霈(2012)。河川型態五層分類法架構與應用。中華水土保持學報,43(1),21-40。 28.黃有傑、羅紹麟(2005)。生態旅遊機會序列指標之研究。農林學報,54(4),283-296。 29.黃偉婷、吳東霖、施君翰、朱達仁(2018)。休閒農場與觀光資源之遊憩機會序列之研究。休憩管理研究,5(1),41-60。 30.普若瑄(2020)。應用自發性地理資訊於國家公園之遊憩行為分析與遊客管理—以陽明山國家公園為例(未出版之碩士論文)。國立臺灣大學,台北市。 31.楊偉甫(2015)。流域綜合治理計畫之績效管理機制。國土及公共治理季刊,3(3),96-105。 32.楊薇玉、姜善鑫(2007)。台灣季節?雨之週期現象。華岡地理學報,(20),77-88。 33.溫重翰、張智安、史天元(2021)。犯罪熱點分析方法及其應用:以 2015-2018 年桃園市機車竊盜犯罪為例。國土測繪與空間資訊,9(1),1-20。 34.經濟部水利署水利規劃試驗所,(2020)。水質保告。上網日期:2020年12月01日。網址:https://wq.epa.gov.tw/EWQP/zh/Default.aspx。 35.經濟部水利署第十河川局,(2019)。淡水河水系河川環境管理計畫。上網日期:2022年03月01日。網址:https://reurl.cc/q5Ry5q 36.臺北市政府工務局大地工程處,(2021)。永春坡濕地公園 韌性城市與自然共好。營建知訊,(459),4-11。 37.蔡博文(2011)。NGIS 的下一步:公眾參與。國土資訊系統通訊,(80),2-9。 38.蔡博文、吳怡潔、鍾明光(2016)。自發性地理資訊品質評估探討-蝴蝶VGI案例分析。中國地理學會會刊,(56),1-13。 39.鄭裕仁(2010)。以GIS空間分析克利金法研析苗栗中港溪遊憩潛力與環境景觀之關聯(未出版之碩士論文)。中華大學,新竹縣。 40.歐聖榮、鄭佳美、黃郁琇、林建堯(2010)。以支應性理論探討環境屬性與使用者行?之關係-以國家美術館前開放空間?例。戶外遊憩研究,23(4),79-109。 41.劉小蘭、沈育生、蔡杰廷(2016)。都會區綠地變遷趨勢及其驅動因素之探討-以臺北都會區為例。都市與計劃,43(2),189-227。 42.戴光全、陳欣(2009)。旅遊者攝影心理初探——基於旅遊照片的內容分析。旅遊學刊,7,71-77。 43.蘭陽博物館,(2021)。學習與活動 環教課程。上網日期:2021年07月28日。網址:https://www.lym.gov.tw/ch/education/course/introduction/。 44.Anwar Sadat, M., Guan, Y., Zhang, D., Shao, G., Cheng, X., & Yang, Y. (2020). The associations between river health and water resources management lead to the assessment of river state. Ecological Indicators, 109, 105814. doi:https://doi.org/10.1016/j.ecolind.2019.105814 45.Andrea Ghermandi, Michael Sinclair. (2019). Passive crowdsourcing of social media in environmental research: A systematic map. Global Environmental Change, 55, 36-47. 46.B?rger, T., Campbell, D., White, M. P., Elliott, L. R., Fleming, L. E., Garrett, J. K.,Taylor, T. (2021). The value of blue-space recreation and perceived water quality across Europe: A contingent behaviour study. Science of The Total Environment, 771, 145597. doi:https://doi.org/10.1016/j.scitotenv.2021.145597 47.Basak, S. M., Hossain, M. S., Tusznio, J., & Grodzi?ska-Jurczak, M. (2021). Social benefits of river restoration from ecosystem services perspective: A systematic review. Environmental Science & Policy, 124, 90-100. doi:https://doi.org/10.1016/j.envsci.2021.06.005 48.Bonasia, R., & Lucatello, S. (2019). Linking Flood Susceptibility Mapping and Governance in Mexico for Flood Mitigation: A Participatory Approach Model. Atmosphere, 10(8). doi:10.3390/atmos10080424 49.Casiano Flores, C., Vikolainen, V., & Crompvoets, J. (2021). Governance assessment of a blue-green infrastructure project in a small size city in Belgium. The potential of Herentals for a leapfrog to water sensitive. Cities, 117, 103331. doi:https://doi.org/10.1016/j.cities.2021.103331 50.Chen, Y., Caesemaecker, C., Rahman, H. M. T., & Sherren, K. (2020). Comparing cultural ecosystem service delivery in dykelands and marshes using Instagram: A case of the Cornwallis (Jijuktu'kwejk) River, Nova Scotia, Canada. Ocean & Coastal Management, 193, 105254. doi:https://doi.org/10.1016/j.ocecoaman.2020.105254 51.Chen, Y., & Yuan, Y. (2020). The neighborhood effect of exposure to blue space on elderly individuals’ mental health: A case study in Guangzhou, China. Health & Place, 63, 102348. doi:https://doi.org/10.1016/j.healthplace.2020.102348 52.Craig W. McDougall, Nick Hanley, Richard S. Quilliam, David M. Oliver. (2022). Blue space exposure, health and well-being: Does freshwater type matter? Landscape and Urban Planning, 224, 104446. 53.David Serrano Gin?, Mar?a Yolanda P?rez Albert, Aitor ?vila Callau, Joan Jurado Rota. (2020). Dataset on georeferenced and tagged photographs for ecosystem services assessment, Ebro Delta, N-E Spain. Data in Brief, 29. 54.Do, Y., & Kim, J. Y. (2020). An assessment of the aesthetic value of protected wetlands based on a photo content and its metadata. Ecological Engineering, 150, 105816. https://doi.org/https://doi.org/10.1016/j.ecoleng.2020.105816 55.Dur?n Vian, F., Pons Izquierdo, J. J., & Serrano Mart?nez, M. (2021). River-city recreational interaction: A classification of urban riverfront parks and walks. Urban Forestry & Urban Greening, 59, 127042. doi:https://doi.org/10.1016/j.ufug.2021.127042 56.Elwood, S., Goodchild, M. F., & Sui, D. Z. (2012). Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice. Annals of the Association of American Geographers, 102(3), 571-590. doi:10.1080/00045608.2011.595657 57.Fox, N., August, T., Mancini, F., Parks, K. E., Eigenbrod, F., Bullock, J. M., Graham, L. J. (2020). “photosearcher” package in R: An accessible and reproducible method for harvesting large datasets from Flickr. SoftwareX, 12, 100624. doi:https://doi.org/10.1016/j.softx.2020.100624 58.Federal Interagency Stream Restoration Working Group (US). (1998). Stream corridor restoration: Principles, processes, and practices. National Technical Info Svc. 59.Frumkin. (2003). Healthy places: exploring the evidence. Am J Public Health, 93, 1451-1456. 60.Gargiulo, I., Garcia, X., Benages-Albert, M., Martinez, J., Pfeffer, K., & Vall-Casas, P. (2020). Women’s safety perception assessment in an urban stream corridor: Developing a safety map based on qualitative GIS. Landscape and Urban Planning, 198, 103779. doi:https://doi.org/10.1016/j.landurbplan.2020.103779 61.Gascon, M., S?nchez-Benavides, G., Dadvand, P., Mart?nez, D., Gramunt, N., Gotsens, X., Nieuwenhuijsen, M. (2018). Long-term exposure to residential green and blue spaces and anxiety and depression in adults: A cross-sectional study. Environmental research, 162, 231-239. doi:10.1016/j.envres.2018.01.012 62.Gascon, M., Zijlema, W., Vert, C., White, M. P., & Nieuwenhuijsen, M. J. (2017). Outdoor blue spaces, human health and well-being: A systematic review of quantitative studies. International Journal of Hygiene and Environmental Health, 220(8), 1207-1221. doi:https://doi.org/10.1016/j.ijheh.2017.08.004 63.Ghermandi, A., & Sinclair, M. (2019). Passive crowdsourcing of social media in environmental research: A systematic map. Global Environmental Change, 55, 36-47. doi:https://doi.org/10.1016/j.gloenvcha.2019.02.003 64.Gibson, J. J. (1979). The Theory of Affordances. The Ecological Approach to Visual Perception. USA, 1(8), 127-131. 65.Giglio, S., Bertacchini, F., Bilotta, E., & Pantano, P. (2019). Using social media to identify tourism attractiveness in six Italian cities. Tourism Management, 72, 306-312. doi:https://doi.org/10.1016/j.tourman.2018.12.007 66.S. Giletycz, N. Loget, C.-P. Chang, F. Mouthereau. (2015). Transient fluvial landscape and preservation of low-relief terrains in an emerging orogen: Example from Hengchun Peninsula, Taiwan.Geomorphology, 231, 169-181. 67.Goodchild, M. F. (2007). Citizens as sensors: the world of volunteered geography. GeoJournal, 69(4), 211-221. doi:10.1007/s10708-007-9111-y 68.Guidotti, V., Ferraz, S. F. D. B., Pinto, L. F. G., Sparovek, G., Taniwaki, R. H., Garcia, L. G., & Brancalion, P. H. S. (2020). Changes in Brazil’s Forest Code can erode the potential of riparian buffers to supply watershed services. Land Use Policy, 94, 104511. doi:10.1016/j.landusepol.2020.104511 69.Guti?rrez-C?novas, C., Arribas, P., Naselli-Flores, L., Bennas, N., Finocchiaro, M., Mill?n, A., & Velasco, J. (2019). Evaluating anthropogenic impacts on naturally stressed ecosystems: Revisiting river classifications and biomonitoring metrics along salinity gradients. Science of The Total Environment, 658, 912-921. doi:https://doi.org/10.1016/j.scitotenv.2018.12.253 70.Haase, D. (2015). Reflections about blue ecosystem services in cities. Sustainability of Water Quality and Ecology, 5, 77-83. doi:10.1016/j.swaqe.2015.02.003 71.Hale, R. L., Cook, E. M., & Beltr?n, B. J. (2019). Cultural ecosystem services provided by rivers across diverse social-ecological landscapes: A social media analysis. Ecological Indicators, 107, 105580. doi:https://doi.org/10.1016/j.ecolind.2019.105580 72.Huang, Y. M., Chen, M. Y., & Mo, S. S. (2015). How do we inspire people to contact aboriginal culture with Web2.0 technology? Computers & Education, 86, 71-83. doi:https://doi.org/10.1016/j.compedu.2015.03.001 73.Huang, Y., Li, J., Wu, G., & Fei, T. (2020). Quantifying the bias in place emotion extracted from photos on social networking sites: A case study on a university campus. Cities, 102, 102719. https://doi.org/https://doi.org/10.1016/j.cities.2020.102719 74.Hermida, M. A., Cabrera-Jara, N., Osorio, P., & Cabrera, S. (2019). Methodology for the assessment of connectivity and comfort of urban rivers. Cities, 95, 102376. doi:https://doi.org/10.1016/j.cities.2019.06.007 75.Holsti, O. R. (1969). Content analysis for the social sciences and humanities. MA: Addison-Wesley Publishing Company 76.Jansen, F. M., Ettema, D. F., Kamphuis, C. B. M., Pierik, F. H., & Dijst, M. J. (2017). How do type and size of natural environments relate to physical activity behavior? Health Place, 46, 73-81. doi:10.1016/j.healthplace.2017.05.005 77.Kassarjian, H. (1977). Content analysis in consumer research. Journal of Consumer Research, 4(1), 8-18. 78.Kejriwal, M., Wang, Q., Li, H., & Wang, L. (2021). An empirical study of emoji usage on Twitter in linguistic and national contexts. Online Social Networks and Media, 24, 100149. https://doi.org/https://doi.org/10.1016/j.osnem.2021.100149 79.Korpilo, S., Virtanen, T., Saukkonen, T., & Lehv?virta, S. (2018). More than A to B: Understanding and managing visitor spatial behaviour in urban forests using public participation GIS. Journal of Environmental Management, 207,124-133. 80.Le Corre, N., Saint-Pierre, A., Hughes, M., Peuziat, I., Cosquer, A., Michot, T., & Bernard, N. (2021). Outdoor recreation in French Coastal and Marine Protected Areas. Exploring recreation experience preference as a way for building conservation support. Journal of Outdoor Recreation and Tourism, 33, 100332. doi:https://doi.org/10.1016/j.jort.2020.100332 81.Liao, K.-H., Le, T. A., & Nguyen, K. V. (2016). Urban design principles for flood resilience: Learning from the ecological wisdom of living with floods in the Vietnamese Mekong Delta. Landscape and Urban Planning, 155, 69-78. doi:https://doi.org/10.1016/j.landurbplan.2016.01.014 82.Li, D., Zhou, X., & Wang, M. (2018). Analyzing and visualizing the spatial interactions between tourists and locals: A Flickr study in ten US cities. Cities, 74, 249-258. https://doi.org/https://doi.org/10.1016/j.cities.2017.12.012 83.Litton, R. B. (1968). Forest landscape description and inventories: a basis for land planning and design. CA: Forest Service, US Department of Agriculture, Pacific Forest and Range Experiment Station. 84.Matthews, Y., Scarpa, R., & Marsh, D. (2018). Cumulative attraction and spatial dependence in a destination choice model for beach recreation. Tourism Management, 66, 318-328. doi:https://doi.org/10.1016/j.tourman.2017.12.009 85.Mavoa, S., Lucassen, M., Denny, S., Utter, J., Clark, T., & Smith, M. (2019). Natural neighbourhood environments and the emotional health of urban New Zealand adolescents. Landscape and Urban Planning, 191, 103638. doi:https://doi.org/10.1016/j.landurbplan.2019.103638 86.McDougall, C., Quilliam, R., Hanley, N., & Oliver, D. (2020). Freshwater blue space and population health: An emerging research agenda. Science of The Total Environment, 737, 140196. doi:10.1016/j.scitotenv.2020.140196 87.Namyun Kil, Taylor V. Stein, Stephen M. Holland. (2014). Influences of wildland–urban interface and wildland hiking areas on experiential recreation outcomes and environmental setting preferences.Landscape and Urban Planning, 127, 1-12. 88.Norman, P., & Pickering, C. M. (2019). Factors influencing park popularity for mountain bikers, walkers and runners as indicated by social media route data. Journal of Environmental Management, 249, 109413. doi:https://doi.org/10.1016/j.jenvman.2019.109413 89.Olive, R., & Wheaton, B. (2021). Understanding blue spaces: Sport, bodies, wellbeing, and the sea. Journal of Sport and Social Issues, 45(1), 3-19. doi:10.1177/0193723520950549 90.?nder, I. (2017). Classifying multi-destination trips in Austria with big data. Tourism Management Perspectives, 21, 54-58. https://doi.org/https://doi.org/10.1016/j.tmp.2016.11.002 91.Pasanen, T. P., White, M. P., Wheeler, B. W., Garrett, J. K., & Elliott, L. R. (2019). Neighbourhood blue space, health and wellbeing: The mediating role of different types of physical activity. Environment International, 131, 105016. doi:https://doi.org/10.1016/j.envint.2019.105016 92.Perchoux, C., Kestens, Y., Brondeel, R., & Chaix, B. (2015). Accounting for the daily locations visited in the study of the built environment correlates of recreational walking (the RECORD Cohort Study). Prev Med, 81, 142-149. doi:10.1016/j.ypmed.2015.08.010 93.Peter J. Fix, Joshua Carroll, Andrew M. Harrington (2013) .Visitor experiences across recreation settings: A management or measurement issue?.Journal of Outdoor Recreation and Tourism, 3-4, 28-35. 94.Pitt, H. (2019). What prevents people accessing urban bluespaces? A qualitative study. Urban Forestry & Urban Greening, 39, 89-97. doi:https://doi.org/10.1016/j.ufug.2019.02.013 95.Raymond, C. M., Gottwald, S., Kuoppa, J., & Kytt?, M. (2016). Integrating multiple elements of environmental justice into urban blue space planning using public participation geographic information systems. Landscape and Urban Planning, 153, 198-208. doi:https://doi.org/10.1016/j.landurbplan.2016.05.005 96.Rabe, S. E., Gantenbein, R., Richter, K. F., & Gr?t-Regamey, A. (2018). Increasing the credibility of expert-based models with preference surveys – Mapping recreation in the riverine zone. Ecosystem Services, 31, 308-317. doi:https://doi.org/10.1016/j.ecoser.2017.12.011 97.Richards, D. R., & Tun?er, B. (2018). Using image recognition to automate assessment of cultural ecosystem services from social media photographs. Ecosystem Services, 31, 318-325. doi:https://doi.org/10.1016/j.ecoser.2017.09.004 98.Robert E. Manning、Charles P. Liali、李明宗(1988)。遊憩與河流型態-社會與環境間的相關性。戶外遊憩研究,1(1),22-38。doi:10.6130/JORS.1988.1(1)3 99.Clark, R. N., & Stankey, G. H. (1979). The recreation opportunity spectrum: A framework for planning, management, and research (Vol. 98). Department of Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station. 100.Rosgen, D. L. (1994). A classification of natural rivers. CATENA, 22(3), 169-199. doi:https://doi.org/10.1016/0341-8162(94)90001-9 101.Ryan, R. L. (1998). Local perceptions and values for a midwestern river corridor. Landscape and Urban Planning, 42(2), 225-237. doi:https://doi.org/10.1016/S0169-2046(98)00089-9 102.Santos, T., Mendes, R. N., & Vasco, A. (2016). Recreational activities in urban parks: Spatial interactions among users. Journal of Outdoor Recreation and Tourism, 15, 1-9. 103.Shafer, C. S., Lee, B. K., & Turner, S. (2000). A tale of three greenway trails: user perceptions related to quality of life. Landscape and Urban Planning, 49(3), 163-178. doi:https://doi.org/10.1016/S0169-2046(00)00057-8 104.Giglio, S., Bertacchini, F., Bilotta, E., & Pantano, P. (2019). Using social media to identify tourism attractiveness in six Italian cities. Tourism management, 72, 306-312. 105.Sliva, L., & Williams, D. (2001). Buffer Zone Versus Whole Catchment Approaches to Studying Land Use Impact on River Water Quality. Water research, 35, 3462-3472. doi:10.1016/S0043-1354(01)00062-8 106.Spyrou, E., & Mylonas, P. (2016). A survey on Flickr multimedia research challenges. Engineering Applications of Artificial Intelligence, 51, 71-91. doi:https://doi.org/10.1016/j.engappai.2016.01.006 107.Teles da Mota, V., & Pickering, C. (2020). Using social media to assess nature-based tourism: Current research and future trends. Journal of Outdoor Recreation and Tourism, 30, 100295. doi:https://doi.org/10.1016/j.jort.2020.100295 108.Tieskens, K. F., Van Zanten, B. T., Schulp, C. J. E., & Verburg, P. H. (2018). Aesthetic appreciation of the cultural landscape through social media: An analysis of revealed preference in the Dutch river landscape. Landscape and Urban Planning, 177, 128-137. doi:https://doi.org/10.1016/j.landurbplan.2018.05.002 109.V?lker, S., Heiler, A., Pollmann, T., Cla?en, T., Hornberg, C., & Kistemann, T. (2018). Do perceived walking distance to and use of urban blue spaces affect self-reported physical and mental health? Urban Forestry & Urban Greening, 29, 1-9. doi:https://doi.org/10.1016/j.ufug.2017.10.014 110.Vert, C., Carrasco-Turigas, G., Zijlema, W., Espinosa, A., Cano-Riu, L., Elliott, L. R., . . . Gascon, M. (2019). Impact of a riverside accessibility intervention on use, physical activity, and wellbeing: A mixed methods pre-post evaluation. Landscape and Urban Planning, 190, 103611. doi:https://doi.org/10.1016/j.landurbplan.2019.103611 111.Vert, C., Gascon, M., Ranzani, O., M?rquez, S., Triguero-Mas, M., Carrasco-Turigas, G., . . . Nieuwenhuijsen, M. (2020). Physical and mental health effects of repeated short walks in a blue space environment: A randomised crossover study. Environ Res, 188, 109812. doi:10.1016/j.envres.2020.109812 112.Vitale, C., Meijerink, S., Moccia, F. D., & Ache, P. (2020). Urban flood resilience, a discursive-institutional analysis of planning practices in the Metropolitan City of Milan. Land Use Policy, 95, 104575. doi:https://doi.org/10.1016/j.landusepol.2020.104575 113.Wan, C., Shen, G. Q., & Choi, S. (2021). Eliciting users’ preferences and values in urban parks: Evidence from analyzing social media data from Hong Kong. Urban Forestry & Urban Greening, 62, 127172. https://doi.org/https://doi.org/10.1016/j.ufug.2021.127172 114.Wan, J., Zhou, Y., Li, Y., Su, Y., Cao, Y., Zhang, L., . . . Deng, W. (2020). Research on Color Space Perceptions and Restorative Effects of Blue Space Based on Color Psychology: Examination of the Yijie District of Dujiangyan City as an Example. International journal of environmental research and public health, 17(9), 3137. doi:10.3390/ijerph17093137 115.Well, F., & Ludwig, F. (2020). Blue–green architecture: A case study analysis considering the synergetic effects of water and vegetation. Frontiers of Architectural Research, 9(1), 191-202. doi:https://doi.org/10.1016/j.foar.2019.11.001 116.White, M., Smith, A., Humphryes, K., Pahl, S., Snelling, D., & Depledge, M. (2010). Blue space: The importance of water for preference, affect, and restorativeness ratings of natural and built scenes. Journal of Environmental Psychology, 30(4), 482-493. doi:https://doi.org/10.1016/j.jenvp.2010.04.004 117.Xin Xiao, Chaoyang Fang, Hui Lin, Jingfu Chen(2022). A framework for quantitative analysis and differentiated marketing of tourism destination image based on visual content of photos,Tourism Management, (93). 118.Yvonne, P. Allan, R. & Scott, L. (2010). The aesthetic value of river flows: An assessment of flow preferences forlarge and small rivers. Landscape and Urban Planning, (95), 68~78. 119.Zha, Z. J., Tian, Q., Cai, J., & Wang, Z. (2013). Interactive social group recommendation for Flickr photos. Neurocomputing, 105, 30-37. doi:https://doi.org/10.1016/j.neucom.2012.06.039 120.BlueHealth. (2020). Blue Health Linking environment climate & Health. Download URL:https://bluehealth2020.eu/ | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/83674 | - |
| dc.description.abstract | 近年來,歐盟委員會BlueHealth計畫,將藍色空間視為一種促進活動使用的環境。相關研究更顯示,在溪流環境作為民眾多元化活動使用的空間,且成為當今國民重要的休閒遊憩場所。從宏觀層面,根據遊憩機會序列(Recreation Opportunity Spectrum, ROS)顯示環境由開發程度高到低,使用者活動類型會隨著環境需求的不同,而產生不一樣的遊憩體驗。以微觀層面,根據支應性理論(affordance theory)說明隨環境屬性的變化,使用者也會跟著改變使用行為,而促成不同的遊憩使用強度。臺灣隸屬島嶼型的國家,島內受到地勢影響,密佈眾多河川、溪流,甚比國外擁有多元型態的環境。然而,過去研究多數僅針對單一個河流河段進行調查,鮮少有研究探討整條溪流環境對遊憩使用之影響;於方法上,過去主要透過問卷、訪談與觀察法等方式進行資料蒐集,除人力與時間成本高外,並無法精準掌握每位使用者所處的環境,更無法瞭解使用者所分佈之環境類型與其活動類型。自發性地理資訊(Volunteered Geographic Information, VGI)為即時能獲取到使用者的空間數據。因此,本研究將應用自發性地理資訊獲取臺灣溪流環境中所有的使用者空間資訊,研究共分為兩階段來執行。第一階段,從宏觀角度探討不同溪流提供之遊憩機會序列。第二階段,以微觀角度探討溪流環境屬性所支應之遊憩使用。 研究資料透過開放API數據集收集Flickr社群媒體網站2012年01月至2021年12月間,位在經濟部水利署水利規劃試驗所(2020)提供之河川範圍內具有精確地理標籤。研究第一階段,首先獲取臺灣最熱門的河流,分別為基隆河、淡水河、新店溪與大漢溪。接續,將熱門河流內之使用者空間資訊進行空間密度聚集分析(DBSCAN),共獲得112個群集,最終以此作為本研究的熱門遊憩點,同時亦為研究樣本。另外,依據經濟部河川局之分類,將河段分為資源保育河段、自然利用河段與人工經營河段這三種環境,再對應使用者照片內容分析而獲取溪流環境的遊憩機會序列。第二階段,應變項為遊憩熱點內的打卡數量;自變項則為河流縱斷面(坡度、海拔)、河流橫斷面(喬灌木、草坪、人工設施、水域、河岸裸露地)及水物理特性(水溫、汙染水質),並進一步透過多元迴歸分析(Multiple regression analysis)評估變項間的關係。 第一階段研究結果顯示,溪流環境之自然利用河段形成的遊憩熱點最多。三種河段性質內的活動類型,在水上活動以靜態休閒為主,如乘船、走吊橋、戲水等;陸域活動則以休閒為主,如跑步、散步、參觀活動等,其中於自然河段又有體能型活動出現,如踢足球、打棒球、溜直排輪。然而,在觀賞活動當中,主要是拍攝人物、設施物與河流為主,而於自然河段與人工經營河段會觀賞夕陽與夜景。第二階段研究結果顯示,喬木與灌木、河岸裸露地以及人工設施此三個變項對遊憩使用數量有正相關的影響(R2=0.71)。整體而言,溪流環境遊憩使用上最關鍵的因素為河流周旁的土地面積,而且根據遊憩機會序列表亦說明使用者活動類型仍以陸域活動為主,且三種河段上均出現不同性質活動的變化。因此,顯示當今溪流廊道空間確實已轉變成休憩空間與觀光的景點,然而在未來溪流環境規劃時,則需特別重視溪流周的土地規劃利用。 | zh_TW |
| dc.description.abstract | In recent years,the European Commission's BlueHealth program has seen blue space as an environment that promotes the use of activities. Related research have shown that the stream environment is used as a space for the various acivities of the people, and has become an important leisure and recreation place for the people.From a macro point of view, according to the sequence of recreation opportunities, the environment is displayed from high to low, and the type of user activity will supply different recreation experiences depending on the needs of the environment. From a microcosmic point of view, according to the theory of affordance, with the change of environmental attributes, users will also change their behavior, which will promote different recreational use intensities.Taiwan belongs to the island type of country, the island is affected by the terrain, densely coverd with many rivers, streams, and even more than a foreign country has a multiple environment. However, most of the previous studies have been conducted on a single river, and few studies have explored the impact of the entire stream environment on recreational use. In the past of research methods, data collection was mainly carried out through questionnaires, interviews and observation methods that has caused high cost of manpower and time, it was impossible to accurately grasp the environment of each user, let alone understand the type of environment distributed by users and the type of activity. Volunteered Geographic Information (VGI) provides real-time access to the user's spatial data.Therefore, this study will apply volunteered geographic information to obtain all user spatial information in the stream environment in Taiwan, and the study will be carried out in two phases. In the first phase, the sequence of recreation opportunities provided by different streams is explored from a macro perspective. In the second stage, the recreational use of streams supported by the environmental properties of streams is explored from a microscopic perspective. Research data collected through an open API dataset on flickr social media between January 2012 and December 2021, with precise geotagging within the river provided by the Water Resources Planning Institute,WRA (2020). In the first phase of the study, the most popular rivers in Taiwan were first obtained, namely the Keelung River, the Tamsui River, the Xindian Creek and the Great Han Creek. Subsequently, the spatial density aggregation analysis of user spatial information in popular rivers was carried out, and a total of 112 clusters were obtained, which were finally used as popular recreation points for this study, and also as a research sample. In addition, according to the classification of the Water Resources Agency of the Ministry of Economy, the river section is divided into three environments: resource conservation section, natural utilization section and artificial operation section, and then the recreation opportunity sequence of the stream environment is obtained according to the analysis of the user photo content. In the second stage, the strain item is the number of punch cards in the recreation hotspot; The autovariths are the river profile, such as slope, elevation. River cross-section, such as trees, lawns, artificial facilities, waters, bare ground.Water physics, such as water temperature, polluted water quality. And the relationship between the variants is further evaluated by multiple regression analysis. The results of the first phase of the study show that the natural use of the stream environment forms the most recreational hotspots. Three types of activities within the nature of the river section, in the water activities are mainly static leisure, such as boat rides, suspension bridges, water play, etc.; Land activities are mainly leisure, such as running, walking, visiting activities, etc., of which there are physical activities in the natural river section, such as playing football, playing baseball, and skating in a row. However, in the viewing activities, the main photography is people, facilities and rivers, but in the natural river section and the artificial river section, the sunset and night scenery will be enjoyed. The results of the second phase of the study showed that the three variants of trees and shrubs, bare ground and artificial facilities had a positive correlation on the number of recreational use (R2=0.71). Overall, the most critical factor in the recreational use of the stream environment is the land area around the river, and according to the sequence of recreation opportunities, it is also indicated that the type of user activity is still dominated by land activities, and there are changes in activities of different natures on the three river sections. Therefore, it shows that today's stream corridor space has indeed been transformed into a recreational space and sightseeing attraction, but in the future stream environmental planning, special attention needs to be paid to the land planning and utilization of the stream week. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T21:13:49Z (GMT). No. of bitstreams: 1 U0001-1508202211345100.pdf: 12871794 bytes, checksum: 910f289a490df0b538f71288f9228470 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 第一章、緒論P.1 第一節、研究動機P.1 第二節、研究目的P.3 第二章、文獻回顧P.5 第一節、藍色空間與休閒遊憩P.5 一、藍色空間類型與遊憩活動P.5 二、溪流遊憩研究之價值P.5 三、溪流環境之特性P.6 第二節 溪流河段之遊憩機會P.7 一、遊憩機會序列P.7 二、溪流河段開發尺度P.8 三、溪流河段開發尺度之遊憩機會序列P.9 第三節 溪流環境屬性對遊憩活動之支應P.10 一、支應性理論P.10 二、溪流縱斷面環境屬性對遊憩活動影響P.11 三、溪流橫斷面環境屬性對遊憩活動影響P.12 四、溪流水體物理屬性對遊憩活動影響P.13 第四節 自發性地理資訊P.15 一、自發性地理資訊之意涵P.15 二、自發性地理資訊平台應用P.16 三、自發性地理資訊之應用P.18 第三章、溪流環境開發程度與遊憩機會之研究P.21 第一節、研究架構圖P.21 第二節、研究方法P.22 一、研究範圍P.22 二、研究工具與研究材料P.22 三、研究資料擷取與處理P.23 四、資料分析P.23 第三節、研究結果P.27 一、全臺熱門溪流P.27 二、熱門溪流之遊憩熱點P.29 三、熱門河流之遊憩機會序列P.32 第四章、溪流環境屬性與遊憩強度支應研究P.60 第一節、研究架構圖P.60 第二節、研究方法P.61 一、研究樣本P.61 二、研究材料與資料分析P.61 第三節、研究結果P.66 一、描述性統計P.66 二、相關性分析結果P.67 三、多元迴歸分析結果P.69 第五章、結論與建議P.71 第一節、主要結論與應用建議P.71 一、主要結論P.71 二、應用建議P.77 第二節、研究限制與後續研究P.78 參考文獻P.80 | |
| dc.language.iso | zh-TW | |
| dc.subject | 遊憩使用 | zh_TW |
| dc.subject | 環境屬性 | zh_TW |
| dc.subject | 遊憩機會序列 | zh_TW |
| dc.subject | 藍色空間 | zh_TW |
| dc.subject | 支應性 | zh_TW |
| dc.subject | Blue space | en |
| dc.subject | Recreational use | en |
| dc.subject | Environmental attributes | en |
| dc.subject | Recreation opportunity spectrum | en |
| dc.subject | Affordance | en |
| dc.title | 應用自發性地理資訊探勘河流環境對遊憩使用之影響 | zh_TW |
| dc.title | Applying Volunteered Geographic Information (VGI)to explore the influence of river environment on recreational use. | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 110-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 趙芝良(Chih-Liang Chao),蔡博文(Bor-Wen Tsai),王正平(Cheng-Ping Wang),李美芬(Mei-Fen Lee) | |
| dc.subject.keyword | 藍色空間,支應性,遊憩機會序列,環境屬性,遊憩使用, | zh_TW |
| dc.subject.keyword | Blue space,Affordance,Recreation opportunity spectrum,Environmental attributes,Recreational use, | en |
| dc.relation.page | 107 | |
| dc.identifier.doi | 10.6342/NTU202202394 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2022-08-16 | |
| dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
| dc.contributor.author-dept | 園藝暨景觀學系 | zh_TW |
| 顯示於系所單位: | 園藝暨景觀學系 | |
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| U0001-1508202211345100.pdf 未授權公開取用 | 12.57 MB | Adobe PDF |
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