The Naval Research Labratory (NRL) invites proposals for research on using advanced algorithms and techniques, including artificial intelligence, machine learning, and statistical methods, for retrieving biophysical information from high-resolution remote sensing data.
We are particularly interested in research dealing with the coastal zone, focusing more on coastal waters but also including land. Coastal areas are dynamic. Monitoring them is crucial to understanding land-sea processes and various ecological and environmental functions that are of importance and relevance to the Navy.
Proposals are expected to involve the use of innovative approaches to exploit rich spectral and spatial information contained in hyperspectral and multispectral data cubes and retrieve coastal biophysical information, including but not limited to concentrations and types of physical and biologial constituents in water, bottom depth, bottom type, terrestrial soil type and characteristics, coastal vegetation distribution, physical and biological coastal processes, and detection and identification of underwater targets.
Research may address one or several aspects of remote sensing in the coastal domain, including (but not limited to) observing system simulation experiments, compensation for atmospheric effects on remote sensing data, theoretical modeling, image processing, feature extraction, feature classification, and target identification.
NRL provides access to a number of sensing and imaging systems (hyperspectral, multispectral, thermal, and polarimetric systems), calibration facilities, and computer resources to perform the work.
high-resolution; hyperspectral; image processing; machine learning; remote sensing; satellites; coastal; oceans; radiative transfer; bio-optics; multispectral