Lesson Proposal: Infrastructure Damage Analysis Post-Earthquake

[cvilla4]

The data science lifecycle emphasizes the crucial aspects of data collection, management, and visualization. Participants will be guided on gathering earthquake data from sources like the USGS and efficiently managing and cleaning infrastructure datasets using various tools. Additionally, they will learn to create interactive maps to visualize damage severity and prioritize restoration efforts. The thematic focus is on the 2010 Haiti Earthquake, providing a practical context for understanding how earthquakes impact roads, bridges, and buildings. By studying this real-life event, users will gain insights into the damage caused by earthquakes and strategies for effective recovery planning.

Key Takeaways:

• Access earthquake data from sources like the USGS Earthquake API and infrastructure data from OpenStreetMap.
• Utilize data to plan disaster response and recovery, focusing on resource allocation and prioritization.
• Learn techniques to identify and assess damage to roads, bridges, and buildings using geospatial data and satellite imagery.
• Gain practical experience in cleaning and integrating datasets from multiple sources, including geospatial data formats and filtering data pertinent to earthquake analysis.

[jfmartinez4]

The second bullet may need more context on how the earthquake data would relate to resources and what methods there are to allocate to areas affected.
Look for sources of data and check what the data represents to make sure that (1) you don't overwhelm yourself with too many datasets and (2) you're not misrepresenting the data when comparing with other data.

[cdeodati]

I think this is a great project focus. Will you be focusing on a certain region of Haiti or are you planning to do a country-level analysis? OpenStreetMap will have great data, but if you are struggling to find what you are looking for, it may be worthwhile to look for building footprints and infrastructure data in specific regions for more in-depth analysis, especially if you are looking at multiple points in time. I really like the aspect of disaster response and recovery and your final bullet point about practical experience cleaning and integrating datasets.