Name:James V. Aanstoos (Jim)
Associated Centers:Geosystems Research Institute
Email: aanstoos@gri.msstate.edu
Office:High Performance Computing Building,
Office Phone:(662) 325-8278
Address:Mailstop 9627
2 Research Blvd
Mississippi State, MS 39762

Biography:Dr. Aanstoos is an Associate Research Professor of the Geosystems Research Institute (GRI) at Mississippi State University and an adjunct in the Electrical and Computer Engineering department. His current responsibilities include conducting and managing research on remotely sensed image and radar analysis, and teaching in the area of Remote Sensing. Other recent research activities have focused on satellite rainfall estimation, small satellite engineering, multispectral land cover classification and accuracy assessment, and terrain database visualization. His past work has also included: development of a multispectral sensor simulator; visualization of wind shear models; development of software for data quality assurance.
B.S., Electrical and Computer Engineering, Rice University, 1977
M.E.E, Rice University, 1979
Ph.D., Atmospheric Science, Purdue University, 1996
Mississippi State University, Geosystems Research Institute
Associate Research Professor, 2006-present
Cary Academy, Cary, NC
Director of Information Services, 2001-2006
Research Triangle Institute, Research Triangle Park, NC
Senior Research Engineer, 1997-2001
Research Electrical Engineer, 1979-1997
North Carolina State University
Adjunct instructor, Electrical and Computer Engineering, 1980-1985

IEEE (senior member); American Geophysical Union
Applied Imagery Pattern Recognition (AIPR) Executive Committee, Treasurer 1995-99, General Chair 2001-2002, AIPR 2000 Program Chair
Technical Advisory Committee to North Carolina statewide land cover mapping project, 1995

Research Interest: Image Processing, Remote Sensing, Scientific Visualization

Publications: Marapareddy, R., Aanstoos, J.V., & Younan, N. H. (2015). Unsupervised Classification of SAR Imagery Using Polarimetric Decomposition to Preserve Scattering Characteristics. Applied Imagery Pattern Recognition (AIPR) -2015. Washington DC. [Document]

Dabbiru, L., Aanstoos, J.V., & Younan, N. H. (2015). Earthen Levee Slide Detection via Automated Analysis of Synthetic Aperture Radar Imagery. Journal of Landslides. Springer. 1612-5118, 10. DOI:10.1007/s10346-015-0599-9. [Abstract]

Mahrooghy, M., Aanstoos, J.V., Prasad, S., Hasan, K., Nobrega, R. A. A., & Younan, N. H. (2015). A Machine Learning Framework for Detecting Land Slides on Earthen Levees Using Spaceborne SAR Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. IEEE. 8(8), 3791 - 3801. [Abstract] [Document]

Marapareddy, R., Aanstoos, J.V., & Younan, N. H. (2015). Classification Of Polarimetric SAR Imagery Using Unsupervised H/Alpha And Extended H/Alpha Schemes To Detect Anomalies On Earthen Levees. International Conference on Image Processing (ICIP 2015). Quebec City, CANADA.: IEEE. [Abstract] [Document]

Marapareddy, R., Aanstoos, J.V., & Younan, N. H. (2015). An Innovative Approach to Detect Anomalies on Earthen Levees Using Unsupervised Classification of Polarimetric Sar Imagery. IGARSS 2015. Milan, Italy: IEEE. [Document]

Total Publications by this Author: 48