| 研究生: |
簡為朋 Chien, Wei-Peng |
|---|---|
| 論文名稱: |
探討災害韌性時空動態變化之評估研究-高雄市為例 A Study on the Spatiotemporal Dynamics of Disaster Resilience Assessment: The Case of Kaohsiung |
| 指導教授: |
顧嘉安
Ku, Chia-An |
| 學位類別: |
碩士 Master |
| 系所名稱: |
規劃與設計學院 - 都市計劃學系 Department of Urban Planning |
| 論文出版年: | 2025 |
| 畢業學年度: | 113 |
| 語文別: | 中文 |
| 論文頁數: | 103 |
| 中文關鍵詞: | 災害韌性 、時空動態 、韌性評估 |
| 外文關鍵詞: | Disaster Resilience, Spatiotemporal Dynamics, Resilience Assessment |
| 相關次數: | 點閱:47 下載:16 |
| 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 |
台灣因其特殊地理區位處於颱風盛行之亞熱帶氣候與太平洋板塊及菲律賓海板塊交界地震事件頻繁,故針對自然災害的災害減少策略格外重要,因此台灣共同響應聯合國及國際組織所制訂之目標,國內積極推動相關減災策略,其中韌性在空間規劃方面如國土計畫內將因應氣候變遷極端氣候,營造永續韌性城鄉視為發展目標,同時台灣防災體系除都市防災計畫外另一具有直接相關性計畫為地區防救災計畫,目前地區韌性評估的相關研究尚不成熟,現有的評估流程不足以全面反映地方韌性水準,導致政策推動缺乏具體依據。
而目前相關韌性研究多聚焦於單一時間點之評估,針對韌性之動態屬性研究仍佔少數,故本研究透過2013年至2023年資料於環境、社會、經濟、基礎設施、災害影響等五大面向,初步建置地區災害韌性評估指標,結合過程與結果導向研究方法,於過程導向運用主成分分析將指標資料進行降維,並找出最能夠解釋資料的方向,而後透過熵值權重法利用熵值在資訊理論代表的不確定性,計算各評估指標能傳遞決策資訊能力,求算評估指標間之相對權重,並使用整合 GIS 與空間統計之空間自相關分析,於結果導向運用社區韌性測量模型,以理想中系統功能與實際功能之間差距進而量化適應性韌性,探討各地區不同年度之災害韌性空間及時間差異,檢視其空間分布型態與空間自相關特性,分析結果亦可了解研究地區內各空間單元之韌性分布差異及各地區內韌性時間變化差異,針對空間單元不同特性給予後續韌性調適策略,依此建議後續相關韌性政策推動之依據,根據本研究成果,西南方向市中心周邊邊陲地區在地區條件上有逐漸下降的趨勢,經適應性韌性評估後也發現以長期趨勢來看韌性為下降之趨勢,表明該地區在面對災害的適應能力是不足以恢復到較好的狀態,表明儘管在地區條件上相對較好但在經災害影響後將使該地區逐漸喪失韌性,本研究嘗試以更完整角度將韌性兩者特性結合整體評估高雄地區災害韌性,並作為相關單位作為政策上之依據,此評估架構亦可作為相關防救災計畫評估韌性之流程參考。
Taiwan's geographic location makes it highly vulnerable to natural disasters such as typhoons and earthquakes. In response, Taiwan promotes disaster risk reduction strategies aligned with international goals, emphasizing resilience in national spatial planning. However, current regional resilience assessments remain underdeveloped, often focusing on single time points and lacking dynamic perspectives.
This study establishes a regional disaster resilience assessment framework for Kaohsiung from 2013 to 2023 across five dimensions: environment, society, economy, infrastructure, and disaster impact. It integrates a process-oriented approach using Principal Component Analysis and the Entropy Weight Method to identify key indicators and their relative importance, and an outcome-oriented approach applying GIS-based spatial autocorrelation and a community resilience measurement model to quantify adaptive resilience.
Results show significant spatial and temporal variations in resilience, with southwestern peripheral areas exhibiting a long-term decline. This indicates insufficient adaptive capacity despite favorable conditions. The proposed framework offers a more comprehensive evaluation method and provides a policy reference for future resilience planning.
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