Course overview, syllabus, schedule, etc. for the Beaver Works Summer Insitute (BWSI) summer remote sensing course
The Beaver Works Summer Institute course on Remote Sensing for Disaster Response offers students the opportunity to explore the exciting intersection of data science and disaster response. During the course, the students will learn the basics of Python, Git, geospatial information systems (GIS), and image processing. Students will explore real world datasets including aerial imagery from drones and Civil Air Patrol, as well as various satellite sources. Students will develop experience in an area of data science that is poised to play a critical role in understanding our world.
Imagine coordinating a response after the chaos of a hurricane or the challenges of a famine lasting years; these big problems require big data to solve. With airplanes and satellites, we collect mountains of data of affected regions, but who looks at this data? How do we turn this data into a physical response? The program’s goal is for participants to explore, leverage, and transform open source information and imagery collected from drones, airplanes, helicopters, and satellites to generate actionable intelligence to support a disaster or humanitarian response. Students will be exposed to three main components: 1) processing and extracting features from raw data, 2) data classification and analysis, and 3) developing data products to support decision making. The program will explore tools and techniques using real world operational data collected from across the globe.
The BWSI Remote Sensing program offers high school students the opportunity to explore the exciting intersection of data science and crisis response. The program consists of two components: (1) online course from January to May, open to all interested and committed students; and (2) a four-week summer program in July/August held virtually with real-time instruction or on MIT campus in Cambridge, MA when possible. During the course, the students will learn to understand the basics of Python, Git, machine learning, and image processing. Students will explore real world datasets of aerial and satellite imagery. By participating in the online and/or virtual/onsite portion of the program, students will develop experience in an area of data science that is poised to play a critical role in understanding our world.
The virtual/in-person session of the program features guest lecturers from academia, nonprofits, industry, and various levels of government discussing their work on Remote Sensing and Emergency Management. Previous offerings of the course have featured guest lecturers from organizations such as: the Federal Emergency Management Agency, the Red Cross Red Crescent Climate Centre, the World Health Organization, MIT Lincoln Laboratory, the Defense Innovation Unit, the California Office of Emergency Services, Massachusetts Task Force 1, the US Census Bureau, and the Civil Air Patrol, among many others.
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.
- Introduction to Remote Sensing for Disaster Response
- Intro to Python and Pandas
- GIS in Python
- Field trip to MIT Lincoln Laboratory
Repositories:
- https://github.com/bwsi-hadr/01-Intro-to-python
- https://github.com/bwsi-hadr/02-visualization-and-shapes
- https://github.com/bwsi-hadr/03-Intro-to-GIS
- Geospatial analysis
- Satellite imagery and remote sensing
- Network analysis and Open Street Maps
- Field trip to Massachusetts Task Force One (MA-TF1)
Repositories:
- https://github.com/bwsi-hadr/04-Intro-to-networks
- https://github.com/bwsi-hadr/05-Rasters-and-satellite-imagery
- https://github.com/bwsi-hadr/06-Intro-to-Image-processing
- Image processing, spectral analysis
- Classifying images with Convolutional Neural Networks
- Structure from Motion/Photogrammetry
Repositories:
- https://github.com/bwsi-hadr/07-3D_Reconstruction_and_SfM
- https://github.com/bwsi-hadr/08-Intro_to_deep_learning
- Final Exercise Preparation: Simulated hurricane response
- Communication and presentation skills
- Collective decision making and collaboration
Repositories:
- Beaver Works Summer Institute (BWSI)
- MIT Lincoln Laboratory (MIT LL)
- Python Like You Mean It (PLYMI)
- Geospatial Information Systems (GIS)
- Public Lab
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