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.
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. http://dx.doi.org/10.1080/17538947.2016.1208686
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. http://dx.doi.org/10.1071/WF13106
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