Information retrieval from Earth Observation (EO) imagery | 6961
Journal of Aeronautics & Aerospace Engineering

Journal of Aeronautics & Aerospace Engineering
Open Access

ISSN: 2168-9792

Information retrieval from Earth Observation (EO) imagery

2nd International Conference and Exhibition on Satellite & Space Missions

July 21-23, 2016 Berlin, Germany

Nicolas H Younan

Mississippi State University, USA

Scientific Tracks Abstracts: J Aeronaut Aerospace Eng

Abstract :

Earth Observations (EO) data are obtained from a multitude of sources and requires tremendous efforts and coordination among researchers and user groups to come to a shared understanding on a set of concepts involved in a domain. The ultimate goal of any EO system is to provide understanding, which will often require expertise and/or data sources from globally distributed resources, thus presenting unique challenges. To address these challenges, it is incumbent upon the global community to evolve and sustain a global observation network. These observations serve as the foundation for the models that are used to describe Earth processes. As this observational data accumulates in global archives, new opportunities become available for knowledge discovery about the Earth system. However, access to these observational data is optimized for the science teams for whom the instruments were launched and access by operational users may be problematic. This presentation will lay out some of the challenges for those engineers and scientists involved in pattern recognition in the Earth remote sensing arena. It describes the problem space for making decisions and introduces the concept of contextual remote sensing.

Biography :

Nicolas H Younan is currently the Department Head and James worth Bagley Chair of Electrical and Computer Engineering at Mississippi State University (MSU). He received the BS and MS degrees from MSU in 1982 and 1984, respectively, and the PhD degree from Ohio University in 1988. His research interests include signal processing and pattern recognition. He has been involved in the development of advanced image processing and pattern recognition techniques for remote sensing applications, image/data fusion, feature extraction and classification, automatic target recognition/identification, and image information/data mining.