Syllabus

The four-week summer component of aims to guide students through the processing of designing experiments and analyzing commonly used for data for disaster response. Daily course material, case studies, guest lectures, and small-group projects will expose students to challenges across technical domains. This syallabus is subject to change over the duration of the course.

Schedule

Week 1: Foundation

  1. Introduction to Remote Sensing for Humanitarian Assistance and Disaster Relief
  2. Review of online Python course
  3. GIS and networks in Python
  4. Field trip to MIT Lincoln Laboratory

Week 2: Data Science and Analysis

  1. Introduction to engineering design and data science principles
  2. Images, metadata, and image processing
  3. Field trip to Massachusetts Task Force One (MA-TF1)

Week 3: Aerial Imagery and Sensing

  1. Civil Air Patrol and Aerial Imagery
  2. Internet of things and analyzing aerial images
  3. Building a hardware multispectral sensor
  4. Kite photography
  5. Field trip to Draper Laboratory

Week 4: Optimization Decision Making

  1. Network optimization and class optimization formulations
  2. Guest lectures from Swissnex and Red Cross Red Crescent Climate Centre
  3. Final exercise of disaster tabletop simulation