Lu, Xiaoman

Oliveira, Pedro

Pedro Oliveira is a PhD student at GSCE started in spring 2017. Dr. David Roy is his advisor. He is using Landsat 8, Sentinel 2, and LiDAR data to study forest disturbances in the Brazilian Amazon.

Hess, Andrea

Wang, Jianmin

Jianmin Wang is a PhD student at GSCE started in Fall 2015. He is working with Dr. Xiaoyang Zhang. He currently focuses on the wildfire impacts on satellite derived land surface phenology. His research interests are exploring the mechanisms of environmental conditions regulating the vegetation composition and growth with the biophysical parameters of vegetation retrieved by remote sensing. Commonly used methodologies include land surface phenology (LSP) detection, data fusion, spectral mixture analysis (SMA), radiative transfer modelling, etc.

Tomaszewska, Monika

Vetrita, Yenni

Yenni started her Ph.D. program at the GSCE in Fall 2015, working with Dr. Mark Cochrane and Dr. Xiaoyang Zhang as her advisors. Prior to joining the Center, she worked for the Indonesian National Institute of Aeronautics and Space (LAPAN) as a researcher. She earned her bachelor's degree in forest management from Bogor Agricultural University, Indonesia, and her M.Sc. in space technology and applications from Beijing University of Aeronautics and Space (Beihang), China.

Samasse, Kaboro

Kaboro’s dissertation research focuses on the use and improvement of remote sensing and geospatial technologies in support of famine early warning and food security institutions in West Africa, with a focus on Mali. The first stage of the research has used satellite remote sensing data on vegetation greenness and leaf area to calibrate crop growth models to estimate crop yields. Interannual variation in predicted yields will be compared to agricultural statistics available in Mali.

Stephens, Jeff

Nguyen, Lan

Velpuri, Naga Manohar

Dr. Velpuri graduated with his PhD in May 2012 under the supervision of Dr. Senay.  His PhD research was focused on developing methods to monitor lakes and reservoirs using multi-resolution remotely sensed data.


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