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McKee, Jacob

Publications and source records attributed to McKee, Jacob.

A baseline structure inventory with critical attribution for the US and its territories

Leveraging high performance computing, remote sensing, geographic data science, machine learning, and computer vision, Oak Ridge National Laboratory has partnered with Federal Emergency Management Agency (FEMA) to build a baseline structure inventory covering the US and its territories to support disaster preparedness, response, and recovery. The dataset contains more than 125 million structures with critical attribution, and is ready to be used by federal agencies, local government and first responders to accelerate on-the-ground response to disasters, further identify vulnerable areas, and develop strategies to enhance the resilience of critical structures and communities. Data can be freely and openly accessed through Figshare data repository, ESRI’s Living Atlas or FEMA’s Geodata platform.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Providing Geospatial Intelligence through a Scalable Imagery Pipeline

This chapter describes ORNL’s (Oak Ridge National Laboratory’s) contributions to imagery preprocessing for geospatial intelligence research and development (R&D) in four sections. First, we discuss challenges involved in building an effective imagery preprocessing workflow and the world-class high-performance computing (HPC) resources at ORNL available to process petabytes of imagery data. Second, we highlight how we developed imagery preprocessing tools over three decades while paving the way for our current cutting-edge machine learning and computer vision algorithms that are impacting humanitarian and disaster response efforts. Third, we discuss how PIPE modules work together to turn raw images into analysis-ready datasets. Fourth, we look toward the future and discuss planned advancements to PIPE and computing trends that will affect geospatial intelligence R&D.

Reith, Andrew↗