Welcome to the Canizaro Livingston Gulf States Center for Environmental Informatics (GulfSCEI, pronounced “Gulf Sea”). We foster inter-disciplinary collaboration within the University of New Orleans and between investigators across the Gulf of Mexico, and empower scientists and engineers with modern informatics tools to solve environmental problems of the coastal margin of the US Gulf States. We assist state and federal agencies, non-governmental organizations and industrial partners to advance their educational, and research and development capabilities in environmental informatics. Questions and Inquiries about GulfSCEI should be directed to: firstname.lastname@example.org
A Framework to Annotate the Uncertainty for Geospatial Data
Environmental Geospatial Information Systems Development for the Louisiana Department of Wildlife and Fisheries (LDWF)
Freshwater Diversions into Estuaries
Frey, D.J., A. Mishra, M.D. Houque, M. Abdelguerfi and T.M. Soniat. 2018. A Machine Learning Approach to Determine Oyster Vessel Behavior. Mach. Learn. Knowl. Extr. 1, 4; doi:10.3390/MAKE 101000
Soniat, T.M. (Ed.) Synopsis of the Fifth Annual Louisiana Oyster Stock Assessment Workshop. University of New Orleans, New Orleans, LA. 28 pp.
Ioup, E., Z. Yang, B. Barre, J. Sample, K. Shaw & M. Abdelguerfi. 2015. Annotated uncertainty of geospatial and environmental data. IEEE Internet Computing 19(1):18-27.
Soniat, T., "Coupling U.S. Gulf State Stock Assessments to Shell-Budget Modeling to Determine Sustainable Harvest of Oysters Across the Gulf of Mexico," National Oceanic and Atmospheric Administration (NOAA), Start date: 9/21/2018, Duration: 2 years.
Soniat, T., (PI), Abdelguerfi, M., (Co-PI) “Maintaining Sustainable Oyster Production for the Louisiana Oyster Industry,” Louisiana Department of Wildlife and Fisheries. $770,111, Start date: 05/01/16, Duration: 3 years.
Abdelguerfi, M., “Large Scale Geospatial Data Mining using Hadoop and R System,” Naval Research laboratory, Stennis Space center – M.S., $999,994, Start Date: 1/1/2016, Duration: 5 years (funded).