Carnegie Mellon University, the U.S. Department of Defense, and U.S. startup CrowdAI have released a dataset of 22,000 satellite images to advance the development of systems that can automatically assess building damage. The dataset includes and pre and post-natural disaster images and includes 850,000 building annotations. The researchers used a zero to three annotation scale to categorize the level of a building’s level of damage.
Using Satellite Imagery to Automatically Assess Building Damage
Michael McLaughlin is a research analyst at the Center for Data Innovation. He researches and writes about a variety of issues related to information technology and Internet policy, including digital platforms, e-government, and artificial intelligence. Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He received his Master’s in Communication at Stanford University, specializing in Data Journalism.
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