Phone: 603-862-1070
Email:
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Janet Campbell
University of New Hampshire
Biography:
Janet W. Campbell received her B.A. degree in 1966, her M.A. degree in 1968, both in mathematics, and her Ph.D. degree in statistics in 1973, all from the Virginia Polytechnic Institute, Blacksburg. She was with NASA Langley Research Center, Hampton, VA, as an Aerospace Technologist between 1967 and 1982. Between 1982 and 1993, she was a Research Scientist at the Bigelow Laboratory for Ocean Sciences and has been involved in ocean color remote-sensing research since 1976. She is a Research Associate Professor at the Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham. She is a Member of the SeaWiFS and MODIS science teams.
Research Area:
As a member of the MODIS Instrument Team, my goal is to develop the scientific and statistical basis for monitoring algal pigments and primary productivity in coastal, estuarine and inland ecosystems using satellite data and complementary surface measurements. Specific objectives are:
* Establish a protocol for developing and validating regional or site-specific algorithms for estimating surface chlorophyll-a concentration and primary productivity while accounting for the optical variability of other water constituents. (Definition Phase: February 1996 - January 1997)
* Demonstrate the above protocol by developing chlorophyll and productivity algorithms for near-shore coastal ocean areas and for major estuaries and inland bodies of water found in the northeast region of the United States. (Execution Phase: February 1997 - January 1999)
* Define a strategy for long-term monitoring using surface and satellite measurements to detect change in surface chlorophyll concentration and primary productivity. (Completion Phase: February 1999 - January 2000)
To demonstrate the monitoring strategy, I will produce a time series of spatial maps (images) of surface chlorophyll and primary productivity for the northeast region averaged over monthly periods beginning with the launch of MODIS, together with a series of anomaly maps of the same properties. The anomaly maps will be created by subtracting the long-term mean for each month from each monthly map.
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