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Bandana Kar, Ph.D.
Assistant Professor

E-mail: bandana.kar@usm.edu
Office: Walker Science, Room 222
Phone : (601) 266-5786
Fax : (601) 266-6219
Personal Webpage

Education

B.Arch. 1997 College of Engineering & Technology, O.U.A.T., Orissa, India
M.C.P. 2001, Indian Institute of Technology, Kharagpur, India
M.S. 2003, State University of New York, Albany
Ph.D. 2008 University of South Carolina, Columbia


Teaching Interests

GHY 417/517Geographic Information System
GHY 418/518Spatial Analysis
GHY 612/712Seminar in Geographic Information Science


Research Interests
Geographic Information Science, Remote Sensing, Hazards

I specialize in GIScience approaches and algorithms. Developing algorithms to model social and environmental factors contributing to potential hazard impact and disseminating model outcomes to public and policy makers are my main two objectives. To fulfill my objectives, I am interested in pursuing research in three areas: scale analysis, web-based mapping, and remote sensing.

My current research goal is to develop a scale model that would empirically model how assessed loss from surge impact varies with scales of analysis. The two research goals explored in my dissertation are (1) establishment of a statistical relationship between estimated loss and geographic scale of analysis; (2) the spatial distribution of potential residential dollar loss from surge impacts.

Another of my research interests is to develop interactive, user-friendly and intuitive web-based spatial decision support systems. An example of such system that I was part of during the summer of 2005 and 2005 – 2006 academic year was the Remote Sensing Hazard Guidance System (RSHGS), a NASA funded research project. The goal of this system is to help emergency managers and support staff to identify suitable satellite imagery for a disaster site immediately after the event occurs (i.e. the response/recovery phases of the hazard cycle).

The research areas dealing with remote sensing data I am interested in are (1) extracting information from images to integrate with GIS based analytical models and (2) accuracy assessment of studies conducted at varying spatial and temporal resolution.