Module 1: Emerging Technologies in Disaster Risk Reduction

  • Content:

    • Introduction to Artificial Intelligence (AI) and its role in disaster prediction.

    • Drone usage for hazard mapping and real-time disaster response.

    • Remote sensing and satellite technology for disaster preparedness.

    • Integration of big data and machine learning in early warning systems.

  • Real-World Application:

    • Case studies on the use of AI and drones in recent disasters (e.g. floods).

    • Video walkthroughs of AI-based disaster prediction systems.

  • Assessment:

    • Students develop a drone-based hazard map project for a chosen region using GIS tools.

Module 2: Policy and Financing Innovations in DRR

  • Content:

    • Overview of Innovative financing mechanisms such as catastrophe bonds and insurance for disaster recovery.

    • Public-private partnerships and the role of local governments in DRR funding.

  • Case Studies:

    • Real-world examples from countries.

    • Students draft a policy brief proposing an innovative financing solution for a disaster-prone region.

Module 3: Real-World Case Studies in Disaster Risk Management

  • Content:

    • Case studies on successful DRR strategies implemented in vulnerable areas.

    • Lessons learned from past disaster management responses.

  • Case Study Examples:

    • Flood control systems.

  • Assessment:

    • Comparative analysis of two regions with contrasting disaster risks. Students identify key lessons and propose improvements to existing systems.

Module 4: Field Visit Preparation: On-Ground Applications of DRR Technologies

  • Content:

    • Introduction to the Field Site: Detailed analysis of the flood control system (or other DRR-related infrastructure) they will be visiting, technologies and strategies already implemented at the site, such as early warning systems, structural interventions, and non-structural measures (e.g., community-based preparedness).

    •  Practical training on the tools and technologies students will use during the field visit, including : Drone, GIS and AI

    • Practical instruction on conducting on-site risk assessments, including hazard identification, vulnerability assessments, and exposure evaluation.

    • Workshop on data collection: How to use drones, sensors, and AI tools for real-time data gathering.

  • Materials:

    • Detailed GIS maps showing the flood-prone areas and the current hazard mitigation infrastructure at the site (e.g., flood barriers, drainage systems).

    • Pre-analysis of hazard zones, including historical flood data, rainfall patterns, and land-use changes.

  • Assessment:

    • Students submit a pre-trip reflection detailing their expectations and a brief on the methodologies they plan to use during the field trip.

Module 5: Post-Field Visit Analysis and Capstone Project

  • Content:

    • Reflection on the field visit experience, comparing pre-trip expectations to real-world applications.

    • Analysis of the data collected during the trip using GIS and AI tools.

    • Capstone Project: Develop a comprehensive DRR proposal for a region of the student's choice, integrating technologies like AI, drone mapping, and risk financing strategies.

  • Assessment:

    • Students submit their final project, which will include hazard maps, policy recommendations, and proposed technological innovations.

Course Delivery

  • Duration: 10 weeks total (including the 3-day field trip).

  • Online Modules: Combination of video lectures, hands-on exercises, and quizzes.

  • Field Visit: The real-world experience.