Sense, Predict, Act

Steven A. Klooster

Senior Research Scientist
California State University - Monterey Bay at the NASA-Ames Research Center

Steven A. Klooster is a Senior Research Scientist with California State University - Monterey Bay (CSUMB) at the NASA-Ames Research Center (ARC) in the Earth Systems Science Division. He holds a Master of Science in Engineering and Environmental Studies from the University of Wisconsin - Madison, WI.

He designs, develops and implements global modeling software for studies of greenhouse trace gas fluxes to study climatic change. This is accomplished by coupling a raster/GIS based simulation modeling system that is compatible with remote sensing satellite data bases, scientific visualization tools and geographic information system analysis techniques (GIS). He has ported this model to several parallel computer systems.

He is currently co-developing with the University of Minnesota a set of scalable geo-spatial data mining techniques by the innovative use of Knowledge Discovery and Datamining (KDD) techniques uniquely applied to large geo-spatial scientific datasets. This uses methods to reveal or detect anomalies, relationships or interactions of multiple data inputs derived from advanced satellite data products, climate variables and our NASA-CASA global biospheric model outputs.

As a past member of the Nimbus Science Team he implemented and validated the "Gordon method" atmospheric correction algorithms developed for the Nimbus Ocean Color Research Program (CZCS). This also included scan angle and sun angle dependence for each pixel. This and bio-optical algorithms were tested and validated over Monterey Bay in Case-II waters.

The Gordon CZCS atmospheric and bio-optical algorithms were also extended using a longer infrared reference channel included in the AOCI (Airborne Ocean Color Instrument, a SeaWiFS/SeaStar prototype). This was for studies in Case-II studies and a near real time fisheries research project in the Gulf of Mexico. This required systems design for data flow and real time processing. Chlorophyll concentration and correlated phyto-pigments were determined for this in near coastal waters. Inertial navigation data and the multispectral (AOCI) scanner imagery were merged into a geo-referenced database and transmitted to the user.

While he worked as a hydrologist for the U.S. Geological Survey he devised a method to input classified Landsat data into a regional ground water withdrawal model.

He has authored or co-authored over 40 papers on global modeling of trace gas fluxes or research and applications related to ocean color, bio-optical oceanography and remote sensing related science.

Current interests also include using remote sensing science, ecology and multi-media to present an integrated approach to teaching science to children.