NASA ARSET: Transforming Earth Observation (EO) Data into Building Infrastructure Data Sets for Disaster Risk Modeling

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ARSET - sarah.cutshall
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NASA ARSET: Transforming Earth Observation (EO) Data into Building Infrastructure Data Sets for Disaster Risk Modeling

by ARSET - sarah.cutshall » Wed Sep 13, 2023 2:48 pm America/New_York

NASA’s Applied Remote Sensing Training Program (ARSET) has opened a new open, online, intermediate webinar series: Transforming Earth Observation (EO) Data into Building Infrastructure Data Sets for Disaster Risk Modeling. This three-part training, presented in English and Spanish, is open to the public and will cover the basics of natural hazard risk modeling and exposure development with a focus on fusing data from multiple datasets expressly for the purposes of risk assessment. We will also present examples applying the techniques to applications related to flood risk assessment, climate adaptation, and earthquake modeling.

Transforming Earth Observation (EO) Data into Building Infrastructure Data Sets for Disaster Risk Modeling

Climate change is not only changing the location, frequency, and severity of environmental extremes and hazards, but also the baseline spatial and temporal patterns that have served as the basis for land use planning, the design of infrastructure, and the development of construction standards and practices. To anticipate the emerging impacts on communities, we must improve understanding of exposed assets, including the built infrastructure and its characteristics such as structure type, use, occupance, compliance with engineering standards, and replacement cost. GIS databases track exposure on a wide variety of scales, formats, and levels of detail, yet aggregating these data for risk assessment typically results in skewed datasets that present a view of risk that is limited to known assets. In this short course, we will cover the basics of natural hazard risk modeling and exposure development with a focus on fusing data from multiple datasets expressly for the purposes of risk assessment. We will also present examples applying the techniques to applications related to flood risk assessment, climate adaptation, and earthquake modeling. A portion of this training was funded by the NASA Applied Sciences Disasters Program.

Relevant UN Sustainable Development Goals:
  • SDG 11: Make cities and human settlements inclusive, safe, resilient and sustainable
  • Goal 9: Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Course Dates: October 3, 5, 10, 2023

Times and Registration Information:
English Session: 10:00-12:00 EDT (UTC-4): https://go.nasa.gov/3QEyyZu
Spanish Session: 14:00-16:00 EDT (UTC-4): https://go.nasa.gov/3KK9ywq

Learning Objectives
By the end of this training attendees will be able to:
  • Recognize what building vulnerability is and why it is important for risk modeling
  • Identify the core elements of natural hazard risk modeling and asset loss estimation
  • Identify fundamental approaches for developing building-exposure models using Earth Observation data and tools
  • Apply a basic procedure to model built infrastructure exposure and vulnerability characteristics from Earth Observation data
  • Evaluate building-specific exposure data sets to identify key components for fit, validity, consistency and rectify bias
  • Evaluate the appropriate use of modeled building exposure data to a given community
  • Apply strategies to identify and address equity and bias considerations
  • Apply approaches to validate building data with imagery for regional datasets
  • Document your exposure development process through metadata so that others can understand the process used, the limitations, and how to update if necessary.
Audience: Advanced-level students interested in risk assessment and climate change adaptation, emergency managers, risk modelers, GIS analysts, EO researchers and analysts, Structural Engineers, climate adaptation researchers and planners

Course Format: Three, 2 hour parts

X (formerly Twitter) announcement (English): https://x.com/NASAARSET/status/1698335285682000314?s=20

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