NGA Names Winners of NURI Grant Competition

July 11, 2008

The National Geospatial-Intelligence Agency's Office of Basic and Applied Research has announced its grant awards for the fiscal year 2008 NGA University Research Initiative (NURI) program. The objective of the NURI program is to enhance U.S. universities' ability to perform research in geospatial science, mathematics and engineering topics integral to geospatial intelligence and, in conjunction with that research, provide education in related science and engineering areas critical to U.S. national security.

This year's program requested research in the following four special topic areas, listed below with their corresponding awards. Initial awards are for two years, with a value of about $300,000. All awards include up to three one-year options valued at about $150,000 per year.

Topic 1. Research in Geophysics to investigate, measure, and develop approaches and algorithms to model and interpret the geopotential of both gravity and the magnetic field. Investigations focus on both global and local applications using satellite and in-situ observations to develop scientifically valid theoretical and practical frameworks for models applicable over a very wide range of spatial scales.

University of California-Berkeley, "Spaceborne Magnetic Gradiometry after Swarm: Novel Approaches to Mapping the Earth's Magnetic Field Employing Nonlinear Magneto-Optical Rotation sensors," Principal Investigator: Dr. Dmitry Budker.
Wichita State University, Kansas, "Innovative Mathematical Methods for Gravimetric and Magnetometric Prospecting," Principal Investigator: Dr. Victor Isakov.

Topic 2. Research in Advanced Geospatial Intelligence to investigate and develop efficient target detection and tracking techniques using image data from multiple sources and advanced methods that reduce the amount of hyperspectral data required for processing and characterization.

California Institute of Technology, Pasadena, "A Framework for Regularizing Hyperspectral Images-Image Processing, Spectral Domain Dimension Reduction, Visualization and Quality Assessment," Principal Investigator: Dr. Meyer Pesenson.
University of Maryland, College Park, "Frame Theoretic Methodology for Spectral Domain Dimension Reduction," Principal Investigator: Dr. John Benedetto.
Mississippi State University, "Random Projections for Dimensionality Reduction of Hyperspectral Data," Principal Investigator: Dr. James E. Fowler.
University of California-Berkeley, "Probabilistic Discriminative Latent Spaces for High-Dimensional Image Data," Principal Investigator: Dr. Trevor Darrell.
Arizona State University, Tempe, "Integrated Spectral Dimensionality Reduction," Principal Investigator: Dr. Jieping Ye.

Topic 3. Research in Computer Vision that advances, develops, and improves techniques for automatically extracting features from remotely sensed imagery using contextual cues, implementing algorithms based upon biological models, and providing estimates of the causes of visual scenes. Effective use of contextual cues can be used to improve the quality for information extracted by automated feature extraction. In addition, research is needed to understand and implement algorithms derived from models of biological function. Biologically inspired computer vision using multi-band data offers innovative methods to detect, categorize, and track complex spectral and geospatial features. Research also is needed to develop innovative approaches to interpret and decompose scene causes.

Brown University, Providence, R.I., "A Probabilistic Framework for Relation-Based Registration," Principal Investigator: Dr. Joseph Mundy.
University of California-Berkeley, "Unsupervised Learning of Hierarchical Structure in Multi-Band Imagery," Principal Investigator: Dr. Bruno A. Olshausen.
University of Central Florida, Orlando, "Data and Algorithms for Estimating Scene Causes from Real World Images," Principal Investigator: Dr. Marshall Tappen

Topic 4. Research in Geospatial Representation to capture unconstrained linguistic data, either text or speech, to develop methods that discover, describe, and capture high-order complex and dynamic spatio-temporal structures, to develop analytic tools and techniques that track, monitor, and predict natural or anthropogenic activities, and to provide estimates of the causes of visual scenes. Current products on the market are inherently constrained around structured data and are limited in their ability to accommodate spatial and unstructured information. Research is needed to capture textual information, understand complex features, and develop effective tools and improved techniques to visualize, monitor, and predict change.

Brandeis University, Waltham, Massachusetts, "Spatio-Temporal Tracking of Entities: Determining Object Location from Image and Text Data," Principal Investigator: Dr. James Pustejovsky.
University of Missouri, Columbia, "Linguistic Spatial Reasoning," Principal Investigator: Dr. James Keller.
University of Wyoming, Laramie, "Biologically Inspired Approaches for Reasoning on Complex Functional Networks," Principal Investigator: Dr. Steven Dean Prager.
University of Minnesota, Minneapolis, "Purpose-Aware Dynamic Graph Models for Representing and Reasoning about Networks," Principal Investigator: Dr. Shashi Shekhar.
State University of New York at Buffalo, "A Multiresolution Approach for Modeling and Forecasting of Geospatial Activities," Principal Investigator: Dr. Puneet Singla.
University of Iowa, Iowa City, "Simulating Spatiotemporal Interactions of Mobile Entities," Principal Investigator: Dr. David Bennett.

The NURI program is a component of the NGA Academic Research Program.

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