脆弱性是氣候變遷研究與政策的核心概念，在環境變遷研究中自然災害的發 生不必然會導致受災的結果，只有當地區（或人）對災害具有暴露或敏感的條件 並缺乏調適能力，才會具有脆弱性的特質。脆弱性具有明確的「地理空間」與「社 會空間」的特性，將脆弱的空間特性納人地區災害管理，並進行地區間脆弱程度 與影響因素的比較有其必要性。「整合性的指標評估」能將脆弱性的多元概念與 現實事件加以鏈結，惟過去研究奠基於「地區間影響因素及指標重要性一致」的 假設，分析結果往往忽略了地區間可能具有空間關聯性及災害承載能力本質上的 差異，使得分析結果是具有疑義的。 本文以雲林縣易淹水13個郷鎮為驗證地區，並利用「主成份分析法」整合 指標，擷取出「地區發展強度」與「災害敏感地區」兩個潛在衝撃綜合指標及「都 市化與醫療資源」、「短期緊急應變能力」與「長期照護能力」三個調適能力綜合 指標。進而藉由空間分析方法，得到「高潛在衝撃地區」與「低調適能力地區」， 有利於提供地區決策者判斷對於洪災潛在的危險程度與資源分配；最後利用4也 理加權的主成份分析法」，同時考量「屬性」與「區位」下，得到熱區與冷區的 重要影響指標，作為地區提升應災能力政策研擬的參考。

Vulnerability is a key component of research and policy of global climate change. An area is vulnerable only when it has been exposed to disasters. Therefore, vulnerability is measured in terms of two major factors, namely geographic and social. Many recent studies apply “aggregated indices” to connect multiple factors to real events, and further compare the differences and intensity across regions. Nevertheless, not only does the integration and weighted rationality challenge current research, but the disregard of spatial correlation and disaster capacity might result in inaccurate explanations for local vulnerabilities. Hence, this study applies Principle Component Analysis to flood-prone areas of Yunlin. The factors identified according to previous studies are then classified into potential integrated indicators (local development intensity and disaster sensitive areas) and adaptive integrated indicators (urbanization and medical resources, short-term emergency response capabilities and long-term care capacity). The Spatial Statistical Analysis is then adopted to investigate the hot-spots and cold-spots of local vulnerability. Finally, the Geographically Weighted Principal Components Analysis is used to determine the specific key impact indices of each area. The ultimate outcome of the analysis can be referred to local disaster prevention and management.