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Remote Sensing of Water Resources: Successes and Challenges

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Monday, September 21, 2015, 4 pm– 5 pm

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Water resources, the major driving force on our planet, support numerous ecosystems and cultural services from maintaining biodiversity, nutrient cycling, and enhancing primary productivity; to recreation, ecotourism, transport, and other cultural uses. The pressure on water resources has been on the rise and will continue to increase in the coming years because of increased frequency of drought, urbanization, urban population growth, deforestation, increased use of fertilizers and pesticides, and spread of invasive species. Therefore, accurate, inexpensive, and fast monitoring tools using remote sensing technology are needed for timely implementation of conservation and restoration measures in problematic areas. My research is focused on combining field spectroscopy with the traditional satellite remote sensing to model and map various water quality properties of the inland and coastal waters. My lab at UGA, Remote Sensing and Spectroscopy Lab (RSSL), is mainly focused on quantifying phytoplankton, suspended sediment and toxic cyanobacteria content in waters, particularly, developing remote sensing tools to detect the initiation, growth, and senescence of both green algae and blue-green algae (CyanoHABs). CyanoHABs is a major water quality and public health issue in the inland waters and estuarine environments as it can hamper recreational activities, degrade aquatic habitats (fish kills), and potentially affect human health (toxin impact). RSSL’s long-term goal is to understand the environmental factors controlling the bloom initiation and develop an automated early warning system using satellite data which can be used by various state and federal agencies to warn people of the impending risks and also take measures to reduce or eliminate the frequency and severity of these blooms in the future. This presentation highlights a comparative study between a modified quasi-analytical algorithm (QAA) and a novel three-band algorithm (PC3) to retrieve phycocyanin (PC) pigment concentration in cyanobacteria laden inland waters.


Seminar by:

Deepak R. Mishra, PhD

Associate Professor

University of Georgia

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  • Simone Puel

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