Sathyachandran, Sanath Kumar

Postdoctoral Fellow
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Ph.D. Title: Fire Type Classification in the Brazilian Tropical Moist Forest Biome (Advisor: David Roy) Sanath has bachelor's (1994) and master's (1997) degrees in physics from the University of Delhi and over six years of teaching experience as an astronomer and a science educator at the Nehru Planetarium New Delhi, India.  He earned a master's degree in Space Studies (2007) at the University of North Dakota, working on model inversion of visible near infra red spectra to deduce the surface mineralogy, albedo, and size of near Earth asteroids 2005 AB and 1999 HF1. Sanath graduated with his PhD in 2014 under the supervision of Prof. David P. Roy. He is currently employed as a  Post-Doctoral Fellow in the Geospatial Sciences Center of Excellence.  He continues to work with Dr. Roy on advancing remote sensing methods  for improved characterization of active fires.      

His PhD research was funded by a NASA Earth and Space Science 2010 Fellowship (NNX10AN72H) for his proposal titled "Fire Type Classification in the Brazilian Legal Amazon" and previously was funded by a NASA biodiversity grant (PI Prof. Mark Cochrane).  His research responded to the NASA Carbon Cycle and Ecosystems science focus area by developing methods to classify MODIS active fire detections as deforestation fires, forest fires, disturbed forest fires, or maintenance fires. The spatio-temporal distribution of fire types over a eight year period (2003-2010) was documented and hypotheses concerning the impact of drought and disturbed forest on annual fire type proportions across the Brazilian Legal Amazon addressed.

Submitted Publications

Kumar S. S and Roy D.P., Global Operational Land Imager (GOLI) Landsat-8 reflectance based active fire detection algorithm, Remote Sensing of Environment.


Huang, H., Roy, D.P., Boschetti, B., Zhang, H.K., Yan, L., Kumar, S.S., Gomez-Dans, J., Li, J., 2016, Separability analysis of Sentinel-2A multi-spectral instrument (MSI) data for burned area discrimination, Remote Sensing. 8(10), 873.

Roy, D.P.  and  Kumar, S.S., 2017, Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome, International Journal of Digital Earth. 10(1), 54-84.

Roy, D.P., Kovalskyy, V., Zhang, H.K., Vermote, E.F., Yan, L., Kumar, S.S, Egorov, A., 2016, Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity, Remote Sensing of Environment.  doi:10.1016/j.rse.2015.12.024

Kumar, S.S., Roy, D.P., Cochrane, M.A., Souza JR, C.M., Barber, C., Boschetti, L., 2014, A quantitative study of the proximity of satellite detected active fires to roads and rivers in the Brazilian tropical moist forest biome, International Journal of Wildland Fire.

Smith, A.M.S., Tinkham, W.T., Roy, D.P., Boschetti, L., Kremens, R.L., Kumar, S.S., Sparks, A., Falkowski, M.J., 2013, Quantification of fuel moisture effects on biomass consumed derived from fire radiative energy retrievals, Geophysical Research Letters, 40, 6298-6302. doi:10.1002/2013GL058232

Kumar, S.S., Roy, D.P., Boschetti, L., Kremens, R., 2011, Exploiting the power law distribution properties of satellite fire radiative power retrievals - a method to estimate fire radiative energy and biomass burned from sparse satellite observations, Journal of Geophysical Research, 116, D19303. doi:10.1029/2011JD015676

Last modified: 
May 08, 2017