In the last couple decades, satellite remote sensing has played an increasingly important role to researchers by providing them with valuable information about the Earths landscape

Remote Sensing

Over the last two decades, satellite remote sensing has played an increasingly important role for researchers by providing valuable information about the Earth’s landscape. Some areas of study have not been able to fully benefit from satellite data because of the relatively high spatial resolution of most multispectral satellites (i.e., 1000 m AVHRR, 500 or 250 m MODIS, 30 m Landsat TM, 20 m SPOT). To help bridge these data gaps, research scientists at the Kansas Applied Remote Sensing (KARS) Program within the Kansas Biological Survey (KBS) at the University of Kansas have assembled a multispectral airborne imaging system. This system is able to collect high spatial resolution imagery over specific regions at varying altitudes to produce the desired spatial and temporal resolution. Researchers can now obtain multispectral data when and where they choose instead of being limited by a satellite’s relatively rigid spatial resolution and imaging schedule.

A customized DuncanTech MS3100 digital multispectral camera is used for this imaging system. The MS3100 captures high-resolution imagery (1392 x 1040 pixels) in three co-registered bands using a color-separating prism with three CCD imaging sensors covering the blue (450-520nm), red (630-690nm), and near-infrared (NIR) (760-900) regions of the spectrum. It uses a progressive scan to acquire clear images of moving targets at frame rates of up to 7.5 fps. Image data are captured from the digital camera using Nation Instrument’s PCI-1424 Frame Grabber with each frame having the time of acquisition and GPS coordinates embedded into the header information. To bring all of these components together, a 600Mhz Pentium III computer running Windows 98 with 128Mb RAM is used to control camera configuration and the image acquisition software. The system is installed in a Cessna 182 airplane, which when flown at different altitudes above ground level (AGL) can produce different spatial resolutions to meet specific user needs. When flown at 10,000 ft AGL the imagery has a spatial resolution of one meter, and when flown at 5,000 ft AGL the imagery has a spatial resolution of 0.5 meters.

The three spectral bands used by the camera were selected to provide researchers with valuable information about both terrestrial and aquatic systems. On land, the NIR band provides data on chlorophyll concentrations (plant conditions), while the red and blue bands provide information about vegetation structure and the amount of bare soil present. Similarly, in aquatic regimes, the NIR band senses plant conditions, however, the blue and red bands provide data for water turbidity, shoreline sediment accumulation, and channel or basin structure. Using these data, a researcher examining images of two ponds can compare a variety of features of ponds, including the type and condition of surrounding vegetation, shoreline conditions, amount and type of aquatic vegetation, and turbidity levels with all of these parameters related to watershed conditions.

For terrestrial vegetation and the aquatic vegetation above and just beneath the water surface, it is the finely distinguished differences in “greenness” that allow conditions and then relationships to be determined (several references…can’t get until Tuesday). The amount of vegetation, condition of active growth verses senescence, and major type of plant (eg., grass, shrub, tree, aquatic algae, aquatic rooted or floating flowering plants, species in some cases) are all features of the plant communities that can be determined. These plant conditions are strongly influenced by watershed conditions and considerable information is available concerning these relationships including many studies for ponds and reservoirs in Kansas completed by members of this research team (eg., deNoyelles and O’Brien 1978, deNoyelles and Likens 1985, Randtke and deNoyelles 1985, Johnson et al. 1991, 1994, deNoyelles et al. 1989, 1999, Graham et al. 1999, Wang et al. 1999). (Bob, I assume this is about all of the text detail that you will have room to use. If you need more specifics concerning methods and procedures for the RS you will find some where I have described the budget in some detail below.)

REFERENCES (others for RS to be added Tuesday)

deNoyelles, F., Jr. and W.J. O’Brien. 1978. Phytoplankton succession in nutrient enriched experimental ponds as related to changing carbon, nitrogen and phosphorus conditions. Arch. Hydrobiol., 84:137-165.

deNoyelles, F., Jr., W.D. Kettle and D.E. Sinn. 1982. The resopnses of plankton communities in experimental ponds to atrazine, the most heavily used pesticide in the United States. Ecology 53:1285-1293.

deNoyelles, F.,Jr. and G.E. Likens. 1985. Species composition, distribution, poputation, biomass and behavior. 2. Phytoplankton, p. 161-175. In G.E. Likens (ed.) An ecosystem approach to aquatic ecology – Mirror Lake and its environment, Springer-Verlag, New York.

deNoyelles, F., Jr., W.D. Kettle, C.H. Fromm, M.F. Moffett, and S.L. Dewey. 1989 Use of experimental ponds to assess the effects of a pesticide on the aquatic environment. Ent. Soc. Am. Misc. Publ. No. 75:41-56.

deNoyelles, F., S.L. Dewey, D.G. Huggins, and W.D. Kettle. 1994. Aquatic mesocosms in ecological effects testing: detecting direct and indirect effects of pesticides, p. 577-603. In: R.L. Graney et al. (eds.), Aquatic mesocosm studies in ecological risk assessment. Lewis Publishers, Inc., Boca Raton, FL.

deNoyelles, F., S.H. Wang, J.O. Meyer, D.G. Huggins, J.T. Lennon, W.S. Kolln, and S.J. Randtke. 1999. Water quality issues in reservoirs: some considerations from a study of a large reservoir in Kansas. In: Environmental Engineering Conference Proceedings. 49^th Annual Engineering Conf. , Lawrence, KS, pp. 83-119.

Graham, D.W., D. Miles, F. deNoyelles, and V.H. Smith. 1999. Development of small outdoor microcosms for studying contaminant transformation rates and mechanisms under various water column conditions. Environ. Tox. Chem. 18:1124-1132.

Johnson, M.L., D.G. Huggins and F. deNoyelles, Jr. 1991. Ecosystem modeling with LISREL: a new approach for measuring direct and indirect effects in ecosystem level ecotoxicological testing. Ecological Applications 1:383-398.

Johnson, M.L., D.G. Huggins and F. deNoyelles, Jr. 1994. Structural equation mnodeling and ecosystem analysis, p. 627-652. In: R.L. Graney et al. (eds), Aquatic mesocosm studies in ecological risk assessment. Lewis Publishers, Inc., Boca Raton, FL..

Randtke, S.J., and F. deNoyelles. 1985. A critical assissment of the influence of management practices on water quality, water treatment, and sport fishing in multipurpose reservoirs in Kansas. Final report to the Office of Water Research and Technology, Dept. of the Interior, September 1985, no. 252, Washington, DC. 171 pp.

Wang, S.H., D.G. Huggins, F. deNoyelles, and W.S. Kolin. 1999. An analysis of the trophic state of Clinton Lake. Lake and Reserv. Manage. 15:239-250.