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+ SG Home > Earth Science Division > Biospheric Science Branch Staff > Jennifer L. Dungan
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Jennifer Dungan
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Jennifer L. Dungan

MS: 245-4
650-604-3618
Jennifer.L.Dungan@nasa.gov

Education:

B.A. Environmental Science, Wesleyan University,
Middletown, CT 1981

M.S., Environmental Monitoring, University of Wisconsin, Madison, WI 1986

Ph.D., Geography, University of Southampton, United Kingdom, 2000


Professional Experience:  
2000-Present

Research Scientist
NASA Ames Research Center, Moffett Field, CA 94035-1000

1998-2000 Senior Research Scientist
California State University, Monterey Bay at NASA Ames Research Center
1987-1997 Research Scientist
Johnson Controls World Services at NASA Ames Research Center
1981-1984 Research Assistant
The Ecosystems Center, Marine Biology Lab, Woods Hole, MA 02543


Contributions:

First application of a stochastic method for spatial description of remotely sensed vegetation amount.

Application of analysis of variance to hyperspectral data to show leaf versus canopy scale measurement differences in response to fertilization treatments.



Scientific Societies/Committees: Associate Editor, Remote Sensing of Environment
  Associate Editor, International J. of Applied Earth Observation and Geoinformation (2002-2011)
  Executive Council (1994-1998), North American Council on Geostatistics
  American Geophysical Union


Selected Publications:  
Anderson, K.A., J.L. Dungan and A. MacArthur. 2011. On the reproducibility of field-measured reflectance factors in the context of vegetation studies. /Remote Sensing of Environment/, 15: 1893-1905.
Wang, W., J.L. Dungan, H. Hashimoto, A. Michaelis, C. Milesi, K. Ichii and R. Nemani. 2010. Diagnosing and assessing uncertainties of terrestrial ecosystem models in a multi-model ensemble experiment: 1. Primary production. Global Change Biology, 17: 1350-1366.
Hashimoto, H., J.L. Dungan, M.A. White, F. Yang, A.B. Michaelis, S.W. Running, and R.R. Nemani. 2008. Satellite-based estimation of surface vapor pressure deficits using MODIS land surface temperature data. Remote Sensing of Environment, 112: 142–155.
Dungan, J. L. 2008. Geostatistics, in Encyclopedia of Geographic Information Science , Karen K. Kemp, ed. Thousand Oaks, CA: Sage Publications.
Hashimoto, H., J. L. Dungan, M. A. White, F. Yang, A. R. Michaelis, S. W. Running, R. Nemani. 2008. Satellite-based estimation of surface vapor pressure deficits using MODIS land surface temperature data. Remote Sensing of Environment , 112(1): 142-155.
Warren-Rhodes, K. A., J. L. Dungan, J. Piatek, K. Stubbs, B. Gómez-Silva, Y. Chen, and C. P. McKay. 2007. Ecology and spatial pattern of cyanobacterial community island patches in the Atacama Desert, Chile. J. Geophys. Res ., 112, G04S15, doi:10.1029/2006JG000305
Dungan, J. 2006. Focusing on feature-wise differences in map comparison. J. Geographical Systems , 8(2): 131-143, doi: 10.1007/s10109-006-0019-8.
Gamon, J. A., A. F. Rahman, J. L. Dungan, M. Schildhauer, K. F. Huemmrich 2006. Spectral Network (SpecNet)—What is it and why do we need it? Remote Sensing of Environment . 103: 227-235
Berterretche, M., A. T. Hudak , W. B. Cohen, T. K. Maiersperger, S. T. Gower, and J. L. Dungan. 2005. Comparison of regression and geostatistical methods for mapping Leaf Area Index (LAI) with Landsat ETM + data over a boreal forest. Remote Sensing of Environment , 96: 49-61.
Dungan, J. L., J. Frank, A. Jonsson, R. Morris and D. E. Smith. 2003. Advances in planning and scheduling of remote sensing instruments for fleets of Earth observing satellites. In Real-time Information Technology for Future Intelligent Earth Observing Satellites , eds. G. Zhou, O. Baysal, M. Kafatos, and R. Yang, 115-122. Pottstown, PA: Hierophantes. 115-122.
Dungan, J. L. 2002. Toward a comprehensive view of uncertainty in remote sensing analysis. In Uncertainty in Remote Sensing and GIS , ed. G. Foody and P. M. Atkinson, 25-33. New York: John Wiley & Sons.
Moghaddam, M. and J. L. Dungan. 2002. Forest variable estimation from fusion of SAR and multispectral optical data. IEEE Transactions on Geoscience and Remote Sensing 40: 2176-2187.
Dungan, J. L., J. N. Perry, M. R. T. Dale, P. Legendre, S. Citron- Pousty, M.-J. Fortin, A. Jakomulska, M. Miriti, and M. S. Rosenberg. 2002. A balanced view of scale in spatial statistical analysis. Ecography. 25: 626-640.
Hlavka, C. A. and J. L. Dungan. 2002. Areal estimates of fragmented land cover - effects of pixel size and model-based corrections. International Journal of Remote Sensing . 23: 711-721.
Kyriakidis, P. C. and J. L. Dungan. 2001. Stochastic simulation for assessing thematic classification accuracy and the impact of inaccurate spatial data on ecological model predictions. Environmental and Ecological Statistics . 17: 1083-1098
Dungan, J. L. 2001. Scaling up and scaling down: relevance of the support effect on remote sensing of vegetation. In Modelling Scale in Geographical Information Science , eds. N. J. Tate and P. M. Atkinson, 221-236. Hoboken, NJ: John Wiley and Sons.
Csillag, F., M.-J. Fortin, and J. L. Dungan. 2000. On the limits and extensions of the definition of scale. Ecological Society of America Bulletin. 81: 230-232.
Dungan, J. L. 1999. Conditional simulation: An alternative to estimation for achieving mapping objectives. In Spatial Statistics for Remote Sensing , eds. Stein, van der Meer and Gorte, 135-152. Norwell, MA: Kluwer Academic Publishers.
Keller, R. L., and Dungan, J. L. 1999. Meta-modelling: A knowledge-based approach to facilitating model construction and reuse. Ecological Modelling. 119: 89-116.
Norwell, MA: Kluwer Academic Publishers. Keller, R. L., and Dungan, J.L. 1999. Meta-modelling: A knowledge-based approach to facilitating model construction and reuse. Ecological Modelling, 119: 89-116.
Moghaddam, M., J. Dungan, and J. Coughlan. 1999. Fusion of AIRSAR and TM Data for Parameter Classification and Estimation in Dense and Hilly Forests. IEEE , 305-307.
Dungan, J. L. 1998. Spatial prediction of vegetation quantities using ground and image data, International Journal of Remote Sensing, 19: 267-285.
Coughlan, J. C., and J. L. Dungan. 1997. Combining remote sensing and forest ecosystem modeling: An example using the Regional HydroEcological Simulation System (RHESSys). In The Use of Remote Sensing in the Modeling of Forest Productivity , eds. Gholz, Nakane and Shinoda, 135-158. Norwell, MA: Kluwer Academic Publishers.
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