Hello, I’m Anatoly Gitelson, physicist, remote sensing specialist and professor in the School of Natural Resources.
Most of my research is on the development of models and remote sensing techniques for monitoring terrestrial and aquatic environments. Consequently, I also teach quantitative remote sensing classes that cover both aquatic and terrestrial ecosystems. Remote sensing models and techniques are extremely useful in monitoring water quality and vegetation status. In fact, in a recent research projects that the U.S. Environmental Protection Agency and NASA funded, we developed techniques to monitor phytoplankton density and suspended matter in lakes, reservoirs and coastal waters and we used remote sensing to classify lakes across Nebraska.
Analyses that use remote sensing are equally valuable for land-based projects and often have several important applications. We have used remote sensing techniques in the past in the study of land cover change in different part of the world and we use it now in the assessment of vegetation “health” including carbon dioxide exchange.
Remote sensing tools are dynamic, permitting me to expand the scope of my projects. Hence, I have employed remote sensing techniques and models to track global carbon dioxide exchange and monitor global vegetation dynamics.
I started working at UNL in 2000. I have a Master’s and a Ph.D. from the Institute of Radio Technology in Taganrog in the former Soviet Union.
Key Publications
Gitelson, A.A., Viña, A., Masek J.G., Verma, S. B., and A. E. Suyker. 2008. Synoptic Monitoring of Gross Primary Productivity of Maize Using Landsat Data, IEEE Geoscience and Remote Sensing Letters, Vol. 5, No. 2, April 2008, 10.1109/LGRS.2008.915598.
Gitelson, A.A. G. Dall’Olmo, W. Moses, D.C. Rundquist, T. Barrow, T.R. Fisher, D. Gurlin, and J. Holz. 2008. A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: Validation. Remote Sensing of Environment, 112: 3582–3593, doi:10.1016/j.rse.2008.04.015
Gitelson, A. A., A. Viña, S. B. Verma, D. C. Rundquist, T. J. Arkebauer, G. Keydan, B. Leavitt, V. Ciganda, G. G. Burba, and A. E. Suyker (2006), Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity, J. Geophys. Res., 111, D08S11, doi:10.1029/2005JD006017.
Gitelson, A. A., G. P. Keydan, and M. N. Merzlyak (2006), Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves, Geophys. Res. Lett., 33, L11402, doi:10.1029/2006GL026457.
Gitelson, A. A. Wide Dynamic Range Vegetation Index for Remote Quantification of Crop Biophysical Characteristics. Journal of Plant Physiology, Vol. 161, 165-173, 2004.
Gitelson, A. A., S. B. Verma, A. Vina, D. C. Rundquist, G. Keydan, B. Leavitt, T. J. Arkebauer, G. G. Burba, and A. E. Suyker, Novel technique for remote estimation of CO2 flux in maize, Geophys. Res. Lett., 30(9), 1486, doi:10.1029/2002GL016543, 2003.
Dall'Olmo, G., A. A. Gitelson, and D. C. Rundquist, Towards a unified approach for remote estimation of chlorophyll-a in both terrestrial vegetation and turbid productive waters, Geophys. Res. Lett., 30(18), 1938, doi:10.1029/2003GL018065, 2003.
Gitelson, A.A., Gritz, U. and Merzlyak M.N. 2003. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. J Plant Physiol, Vol. 160, No 3, 271-282.
