Global Leader in Remote Sensing
Global Leader in Remote Sensing
Increasingly myriad spaceborne, airborne, and land-based remote sensors collect information used to characterize human populations, built environments, and natural resources. Data from remote-sensing technology is critical to national security, emergency management, natural resource studies, and hazardous waste analysis. Now, with significant advancements in emerging technologies, remotely sensed data is available at higher spatial, temporal, and spectral resolutions than ever before.
As a global leader in high-performance computing and geographic information science, Oak Ridge National Laboratory is at the forefront of research and development in data modeling, analysis, and visualization. As part of the integrated National Security Emerging Technologies Division, our team provides the expertise to develop algorithms that work across multimodal sensors and platforms to achieve new capabilities that advance the field of remote sensing. Relevance of our groups work can be seen in:
- Emergency response: We help first responders prioritize where to send assistance as soon as possible. We develop technology and procedures that determine debris pile size and locations as well as edge computing on unmanned aerial systems.
- Maritime surveillance: Using temporal series of visible and radar satellite imagery, our Group works to track and surveil “dark vessels” under adverse conditions which are targets for therefore targeted for smuggling.
- Topography and Water security: Water levels and locations can change due to flooding or drought. We model elevation to understand storm surges, where floods may be a risk, where mosquito-bearing water can pool, and the health of our glaciers and polar ice. We also monitor geologic events (e.g., subsidence, earthquakes, and landslides) and human actions (e.g., agriculture, development, and conflict/war). Our Group researches and deploys solutions to map water and measure its depth, and constituents on a country-level scale using high-performance computing.
