学术报告第201940期

报告题目：Oil Spill Detection, Identification and Tracking via Hyperspectral Imaging

报 告 人：Mohammad S. Alam教授（德州农工大学）

报告时间：2019年7月8日9:30-11:00

报告地点：南一楼中311室

Abstract: On April 20, 2010 the BP Deepwater Horizon drilling rig in the Gulf of Mexico exploded releasing 206 million gallons of crude oil contaminating the Gulf and 665 miles of coastlines. The oil and gas volumes released from this accident are the largest in US history and have resulted in catastrophic impacts on environment, ecological balance, marine life, regional industry and economy. Characterizing the distribution, composition and ecosystem interactions of the oil is essential to understanding the long term consequences of this and future oil spills. This incident cost billions of dollars in economic losses while billions were used for clean-up efforts as well as environmental and economic recovery.

Many techniques exist to identify and track the oil slick, to aid in the clean-up and mitigation efforts. However, most of these methods are limited in scope and cover very small areas. Hyperspectral imaging (HSI) is a fast and effective way to capture oil spill information over a vast region of interest encompassing several hundred square miles. HSI provides spatial and time-resolved measurements of the composition and distribution of emissive, reflective or transmissive sources for ground, water, atmospheric or space applications. Hyperspectral sensors can record over 300 selected wavelengths of reflected and emitted energy. Because both spectral and spatial information are obtained, HSI sensors provide a three-dimensional data cube. By extracting all pixels in a single ground resolution cell as a function of wavelength, one can obtain the spectral signature for that cell. However, by extracting all the pixels in the same spectral band, one can obtain a 2D intensity image showing the spatial distribution of reflectance values of the scene for that particular wavelength. By analyzing the spectral signature of oil or oil-derived substances one can detect minute concentrations of hydrocarbon on the surface, subsurface and other areas of interest. Consequently, we propose to use HSI imaging, to provide a qualitative and/or quantitative understanding of the detection, identification, and distribution of oil and oil-derived substances on the surface and subsurface level over a vast region of interest.

Detailed analytical modelling and robust algorithms were developed to identify potential regions-of-interest and classify the oil and/or oil derived substances at the surface and sub-surface levels. Test results using real life hyperspectral imagery available from various agencies (e.g. NASA Jet Propulsion Lab) will be presented to verify the effectiveness of the proposed techniques.

Brief Biography: Prof. Mohammad S. Alam received his BS and MS degrees in electrical and electronic engineering from the Bangladesh University of Engineering and Technology (BUET) in 1983 and 1985, his MS degree in computer engineering from the Wayne State University in 1989, and his Ph.D. degree in electrical engineering from the University of Dayton in 1992. Currently, he serves as a Professor of Electrical Engineering and Computer Science and as the Dean of College of Engineering at Texas A&M University - Kingsville (TAMUK). He served as the Chair of the Department of Electrical and Computer Engineering at the University of South Alabama (USA) during 2001-2015, and as the first Warren H. Nicholson Endowed Chair Professor of Electrical and Computer Engineering in 2016. He served on the faculty of BUET, Purdue University - Fort Wayne, and the University of Alabama. He also served as a Graduate Faculty member of Purdue University and Indiana University.

His research interests include renewable energy, smart energy management and control, image processing, pattern recognition and ultrafast computing. He authored or co-authored over 525 publications, including 198 articles in refereed journals, 330+ conference publications, and 17 book chapters. He has edited a reference book of selected papers on JTC (SPIE Press) and numerous conference proceedings. Nearly 7000 citations of his work have been reported in the Google Scholar (h-index: 38, i10-index: 138). He received numerous excellence in research/teaching/service awards including the 1998 Outstanding Engineer Award from Region 4 of IEEE, 2013 Outstanding Engineer Award from Region 3 of IEEE, and 2016 Joseph M. Biedenbach Outstanding Engineering Educator Award from Region 3 of IEEE. He was also recognized as one of the 50 faculty who made outstanding and lasting research and scholarship contributions in the 50-year history of USA.

Prof. Alam served as the PI or Co-PI of many research projects totaling nearly $15M, funded by NSF, NASA, FAA, DoE, ARO, AFOSR, AFRL, SMDC, Wright-Patt AFB, Alabama Department of Commerce, British Petroleum, nfina Technologies, and ITT industry. He presented over 125 keynote addresses, invited papers, seminars and tutorials at international conferences and research institutions in the US and abroad. He has organized and chaired many international conferences and served as a Guest Editor for several professional journals. He supervised the research work of 55+ Masters/Ph.D. students, 15 post-doctoral students, and 7 visiting scholars. Prof. Alam serves as an ABET evaluator for domestic and international institutions.

Prof. Alam is an elected Fellow of nine professional societies including the Institute of Electrical and Electronics Engineers (IEEE), Institution of Engineering and Technology (IET), Optical Society of America (OSA), SPIE - the International Society for Optical Engineering, Institute of Physics (IoP), Society for Imaging Science & Technology (IS&T), and International Association for Pattern Recognition (IAPR). He serves as an OSA Fellows Travelling Lecturer. He was the Chairman of the Fort Wayne Section of IEEE during 1995-1996 and as the President of the Mobile Section of IEEE during 2012-2016. He also served as the President of the Southeastern ECE Department Heads Association during 2005-2006.