Tian, Z., Y. Niu, D. Fan, L. Sun, G. Ficsher, H. Zhong, J. Deng, F. N. Tubiello. 2018. “Maintaining Rice Production while Mitigating Methane and Nitrous Oxide Emissions from Paddy Fields in China: Evaluating Tradeoffs by Using Coupled Agricultural
Kussul N., Lavreniuk M., Skakun S., Shelestov A. (May, 2017) Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data. IEEE Geoscience and Remote Sensing Letters, 14(5), 778–782.
An online application for decision support in siting woody-biomass to electricity facilities
The goal of this proposal is to develop a robust facility siting application that allows potential users to quickly evaluate economic feasibility and environmental performance potential of particular locations for development as a wood-based biomass power plant, or combined heat and power (CHP) cogeneration plant. Dr. Bandaru is institutional PI and he involves in the development of decision support system to identify biomass locations.
System for Advanced Biofuels Production from Woody Biomass in the Pacific Northwest
Shuman, J.K., A.C. Foster, H.H. Shugart, A. Hoffman-Hall, T. Loboda, Dmitry Ershov, and Elena Sochilova. 2017. Fire Disturbance and Climate Change: Implications for Russian Forests. Environmental Research Letters, 12, 3.
Song, X.P., Potapov, P.V., Krylov, A., King, L., Di Bella, C.M., Hudson, A., Khan, A., Adusei, B., Stehman, S.V. and Hansen, M.C., 2017. National-scale soybean mapping and area estimation in the United States using medium resolution satellite imagery and
Total Carbon Estimation in African Mangroves and Coastal Wetlands in Preparation for REDD and Blue Carbon Credits
We are using a suite of commercial off-the-shelf datasets to estimate forest biomass, extend and cover change over time, including airborne LiDAR, Synthetic Aperture Radar (SAR) and Very High Resolution optical (VHR). Our methodology takes into account that most MRV systems require repeated measurements of carbon stocks and acquiring airborne lidar data on a regular timeframe is costly and impractical.
Linking carbon and water dynamics in the pursuit of predicting peat collapse in coastal blue carbon wetlands
Mangroves and coastal wetlands are some of the most carbon dense ecosystems around the world. The locations of these ecosystems along coastlines make them susceptible to areas of population growth and projected sea level rise. At the current rate of sea level rise, ~3 mm per year, and the reported acceleration in sea level rise, coastal wetlands are and will be exposed to longer inundation periods that cover larger areas.