Publications
Showing 34 results for Author: Benjamin T. Swan
Jun, 2024
Journal
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…
Dec, 2023
Journal
Iterative self-organizing SCEne-LEvel sampling (ISOSCELES) for large-scale building extraction
Convolutional neural networks (CNN) provide state-of-the-art performance in many computer vision tasks, including those related to remote-sensing image analysis. Successfully training a CNN to generalize well to unseen data, however, requires training on samples that represent the full distribution of variation of both the target classes and their surrounding contexts. Wit…
Nov, 2023
Book Chapter
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…
Nov, 2023
Journal
A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams
This article outlines a semi‐autonomous approach for using a fusion of light detection and ranging (LiDAR) and optical remote sensing data to identify and measure small impoundments (SIs) and their dams. Quantifying such water bodies as hydrologic network features is critical for ecosystem and species conservation, emergency management, and water resource planning; however…