防減災與氣候變遷調適
臺北科技大學 115-1 學期課程，課號 364192。
課程大綱
自第七週起，本課程將介紹人工智慧於氣候變遷調適與災害管理之應用，內容涵蓋氣候AI與災害AI的國際發展趨勢、責任AI治理、天氣預報、災害預警、氣候資料判讀、淹水與都市熱島分析、機器學習、水風險，以及企業氣候風險管理。課程結合理論講授、案例討論、數位工具操作與線上自主學習，培養學生運用AI及空間分析工具理解氣候風險、判讀災害資訊，並提出調適策略之基礎能力。 From Week 7 onwards, this course introduces the applications of artificial intelligence in climate change adaptation and disaster management. Topics include global trends in Climate AI and Disaster AI, responsible AI governance, weather forecasting, disaster early warning, climate-data interpretation, flood and urban heat island analysis, machine learning, water risk, and corporate climate-risk management. Through lectures, case discussions, digital-tool exercises, and online self-directed learning, students will develop fundamental skills in applying AI and spatial-analysis tools to understand climate risks, interpret disaster information, and propose adaptation strategies.
課程進度
Week 1~6：Dr. Tseng Week 7：國際氣候AI、災害AI與責任AI治理趨勢 Global Trends in Climate AI, Disaster AI and Responsible AI Governance Week 8：AI天氣預報、災害預警與災害監測工具 AI Weather Forecasting, Disaster Early Warning and Monitoring Tools Week 9：期中考試 (Dr. Tseng) Midterm Examination (Dr. Tseng) Week 10：氣候資料、升溫情境與調適需求判讀 Climate Data, Warming Scenarios and Adaptation Needs Week 11：Google Earth Engine與UN-SPIDER淹水範圍判釋 Google Earth Engine and UN-SPIDER Flood Mapping Week 12：QGIS、都市熱島、NDVI與綠覆率調適分析 QGIS, Urban Heat Island, NDVI and Green Coverage Analysis Week 13：AI機器學習入門：災害脆弱度分群與影像辨識 Introductory AI: Vulnerability Clustering and Disaster Image Classification Week 14：水風險、企業氣候風險與AI排放追蹤 Water Risk, Corporate Climate Risk and AI-based Emissions Tracking Week 15：期末考試 Final Examination Week 16：聖誕節／國定假日 Christmas / National Holiday Week 17：彈性學習週／Flexible Learning (元旦／國定假日 New Year’s Day / National Holiday) Week 18：彈性學習週／Flexible Learning
評量方式
出席狀況：10% 個人作業：30% 期末考試：30% 學習報告：30%
教材
【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：是 教師自編教材 Birkmann, J. (Ed.). (2013). Measuring Vulnerability to Natural Hazards: Towards Disaster Resilient Societies (2nd ed.). United Nations University Press. Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2015). Geographic Information Science and Systems (4th ed.). Wiley. Dignum, V. (2019). Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way. Springer. Dale, L. (2022). Climate Change Adaptation: An Earth Institute Sustainability Primer. Columbia University Press. Cardille, J. A., Crowley, M. A., Saah, D., & Clinton, N. E. (Eds.). (2024). Cloud-Based Remote Sensing with Google Earth Engine: Fundamentals and Applications. Springer.