IEEE Green Energy and Smart Systems Conference
Long Beach, CA, October 29-30, 2018

Lunch Speaker

Multi-sensor Satellite Image Fusion, Data Merging, and Machine Learning  for Monitoring the Changing Urban Environment


The Earth’s total surface area is made up of various flow regimes of reservoirs, bays and lakes as well as soil environment, which are considered important natural resources for the maintenance of ecosystem integrity and human consumption. As the condition of environment deteriorates throughout the world, it necessitates the scientific work of monitoring environmental quality in response to its dynamic changes of quality status or flow conditions and feedbacks to our society. For this purpose, satellite remote sensing techniques with multiple in-situ ground-based sensors may be applied to collectively capture a much larger spatial coverage within relatively short time periods through various traditional or non-traditional algorithms. To improve the overall efficiency there is a tradeoff in spectral, spatial and temporal resolution of different sensors when monitoring the changing environment at the ground level from space. The goal of this presentation is to introduce the latest forefronts in the field and demonstrate green, smart, and sustainable management of our changing Earth environment by integrating multi-sensor satellite image fusion, data merging, and machine learning – an emerging area of importance in systems science and engineering. It demonstrates how the optical and microwave remote sensing can work together to detect the minute changes at the ground level of the Earth. The following scientific questions are explored in this study: (1) Are fused image reflectance bands and machine-learning techniques able to accurately carry out the estimation of target environmental quality parameters under different challenges? (2) Is it feasible to have an integrative and innovative process for updating the urban environmental condition for early warning?

Bio: Prof. Ni-Bin Chang received his B.S. degree in Civil Engineering from National Chiao-Tung University, Taiwan in 1983, and his M.S. and Ph.D. degree in Environmental Systems Engineering from Cornell University, USA in 1989 and 1991, respectively.  He joined the University of Central Florida (UCF) in 2005. At UCF he has been conducting highly interdisciplinary research in Sustainable Systems Engineering. His research interests are related to environmental sensing, monitoring, and modeling with the aid of sensor networks, cyberinfrastructure, and informatics for environmental sustainability and ecosystem conservation. He has over 250 journal publications, 9 books, 11 special issues of academic journals, and 9 United States patents. He served as a plenary speaker for several conferences. He is the Editor-in-Chief of the Journal of Applied Remote Sensing, and an associate editor of the IEEE Systems Journal. He served the general chair of 2014 IEEE International Conference on Sensing, Networking and Control and 2014~2018 SPIE Conference of Remote Sensing and Modeling of Ecosystems for Sustainability. He is the vice chair of the Executive Committee of the IEEE Environmental Engineering Committee. He was the recipient of nearly 40 awards/honor, including the Distinguished Visiting Fellowship from the Royal Academy of Engineering, United Kingdom, Fulbright Scholar Award in the USA/Germany, Bridging the Gaps Award from Engineering and Physical Sciences Research Council (EPSRC) in United Kingdom, Outstanding Achievement Award (ASCE) in the USA, and the Blaise Pascal Award from the European Academy of Science. He is Fellow of the American Association for the Advancement of Science (FAAAS), the American Society of Civil Engineers (FASCE), the Institute of Electrical and Electronics Engineers (FIEEE), the International Society of Optics and Photonics (FSPIE), the Royal Society of Chemistry (FRSC) in the United Kingdom, and the European Academy of Sciences (FEASc). From Aug. 2012 to Aug. 2014, he worked as a program director of the Cyber-enabled Sustainability Science and Engineering (CyberSEES) program and the Hydrologic Science Program at the National Science Foundation in the USA



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