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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 闕蓓德(Pei-Te Chiueh) | |
dc.contributor.author | Andrea H Chu | en |
dc.contributor.author | 朱驊 | zh_TW |
dc.date.accessioned | 2021-05-13T08:37:56Z | - |
dc.date.available | 2018-07-30 | |
dc.date.available | 2021-05-13T08:37:56Z | - |
dc.date.copyright | 2016-07-26 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016-07-20 | |
dc.identifier.citation | References
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/3879 | - |
dc.description.abstract | 氣候變遷調適能力的評估可用以推估當地政府與人民在未來面對氣候變遷影響時,是否能採行足夠且適當的調適措施。但目前相關指標的發展並未考量都市化對調適措施的影響,因此可能會高估調適能力。本研究目的為建立氣候變遷調適能力指標系統,該系統中納入與都市化相關指標 如:建設面積和教育程度,並設定三種社會經濟發展情境,包括:基線 (情境BAU,Business As Usual)、重視經濟發展(情境 A) 及重視環境與社會 (情境 B);以期能提高氣候變遷調適能力評估的準確性,並可供地方發展與規劃之參考。以美國佛羅里達洲的West Palm Beach和臺灣新北市的淡水區為研究案例,使用土地利用模擬軟體What if,分別模擬三種社會經濟發展情境,於2030年及2050年之土地利用狀況;並將結果輸入本研究所建立之指標系統計,以推估兩地的氣候變遷調適能力。在West Palm Beach,情境A在2030年的調適能力為三者最高,然而在2050年的則降低為各情境中最低;情境BAU與情境A類似,但起伏的程度較小;情境B在2030年和2050年的分數都呈逐步上升,並於2050年具有最佳的氣候變遷調適能力。淡水區的趨勢測不同於West Palm Beach,從基準年起三個情境的調適能力都會下降,但以情境B降低的幅度較小。綜合而言,情境A是短期最佳的發展方向,不過以長期來看會有調適能力的限制,而情境B雖然發展較慢,但到2050年會有較高的氣候變遷調適能力。本研究可做為當地政府規劃未來發展的參考。 | zh_TW |
dc.description.abstract | Measuring the ability of a community to face climatic changes, or its adaptive capacity, is necessary in order to plan and guide development as the global climate continues to warm. One factor that has not been thoroughly addressed by previous attempts at measuring adaptive capacity is urbanization. This study looks to measure adaptive capacity in relation to urbanization, as many areas of the world are undergoing this rapid transition. An indicator system was created with land-use sensitive measures and applied to three different land use projection scenarios (high, medium, and low growth) to 2030 and 2050 for two case study areas, Tamsui, Taiwan and West Palm Beach, USA. In Tamsui, the adaptive capacity decreased in all scenarios, but most dramatically for the high growth scenario. The low growth scenario decreased more slowly through each time slice. For West Palm Beach, the high growth scenario had the highest score in 2030, but declined in 2050. The medium growth Scenario BAU, also had a higher adaptive capacity score in 2030 than in 2050. The low growth Scenario B had a score that improved less dramatically but continued to rise through 2050. Scenario A would be ideal for short term gains, but its benefits would plateau in the long term. Scenario B, with conservation measures and more restricted growth would be the most ideal alternative. This study shows that urbanization has short term socioeconomic gains, but long term environmental consequences, and it successfully incorporates the effect of land use change into an adaptive capacity indicator system and can be used in other localities expecting significant increases in urbanization. | en |
dc.description.provenance | Made available in DSpace on 2021-05-13T08:37:56Z (GMT). No. of bitstreams: 1 ntu-105-R03541219-1.pdf: 3256713 bytes, checksum: 72fde68ef3b080ad4352430f3818259e (MD5) Previous issue date: 2016 | en |
dc.description.tableofcontents | Table of Contents
Acknowledgements i Chinese Abstract ii English Abstract ii Table of Contents v List of Tables viii List of Figures ix 1 Introduction 1 2 Literature Review 3 2.1 Introduction 3 2.2 Conceptual Overview 4 2.2.1 Failure of Mitigation and the Ascent of Adaptation 4 2.2.2 Relating Adaptation, Adaptive Capacity, Vulnerability, Resilience and Risk 10 2.2.3 Indicators 21 2.2.4 Land Use and Urbanization Dynamics 25 2.3 Study-Specific Review 30 2.3.1 Case Study Sites 30 2.3.1.1 Tamsui, New Taipei City, Taiwan 30 2.3.1.2 West Palm Beach, Florida, USA 32 2.3.2 Indicator Systems – Previous Studies & Indicator Selection 34 2.3.2.1 Biophysical Indicators 34 2.3.2.2 Socioeconomic Indicators 36 2.3.3 Scenario Building 40 2.4 Conclusion 42 3 Methods 44 3.1 Case Study Sites 45 3.1.1 Introduction 45 3.1.2 Tamsui, Taiwan 46 3.1.3 West Palm Beach, Florida 48 3.2 Indicator System and Scoring 51 3.3 Land Use Scenarios and What If? 54 3.3.1 Data 54 3.3.2 Scenarios 55 3.3.3 What If? 55 4 Results and Discussion 61 4.1 What If? Allocation Maps 61 4.2 UACI Scores 66 4.2.1 Tamsui Scores 66 4.2.1.1 Baseline 66 4.2.1.2 Predicted 69 4.2.2 West Palm Beach Scores 70 4.2.2.1 Baseline 70 4.2.2.2 Predicted 72 4.2.3 Discussion 76 5 Conclusion 80 References 85 Appendices 95 What If? Projections Calculations and Assumptions 95 What If? Allocation Output Reports 103 | |
dc.language.iso | en | |
dc.title | 建立具都市化特徵的氣候變遷調適能力指標 | zh_TW |
dc.title | Incorporating the Effect of Urbanization in Measuring Climate Adaptive Capacity | en |
dc.type | Thesis | |
dc.date.schoolyear | 104-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 馬鴻文(Hwong-Wen Ma),童慶斌(Ching-Pin Tung) | |
dc.subject.keyword | 都市化,土地利用變遷,氣候變遷,調適能力,調適, | zh_TW |
dc.subject.keyword | urbanization,land use change,climate change,adaptive capacity,adaptation, | en |
dc.relation.page | 117 | |
dc.identifier.doi | 10.6342/NTU201600887 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2016-07-20 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 環境工程學研究所 | zh_TW |
顯示於系所單位: | 環境工程學研究所 |
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