Nur Hussain

Postdoctoral Fellow

Ensminger Lab

Mailing Address:

3359 Mississauga Road
Mississauga ON L5L1C6
Canada

Dr. Nur Hussain is a postdoctoral fellow in remote sensing and forest ecosystems. His research focuses on evaluating how forest management treatments, such as variations in tree species and age classes, influence forest growth, carbon sequestration, and resilience to future climatic stresses and extreme events. He uses Solar-Induced Fluorescence (SIF) and Gross Primary Productivity (GPP) data to assess forest carbon dynamics under different management regimes.

Nur completed his Ph.D. at McMaster University (2024), where his thesis explored climate change impacts on land surface-atmosphere interaction processes in both managed forests and agricultural ecosystems. He has extensive experience using remote sensing, GIS, and eddy covariance techniques to monitor carbon, water, and energy fluxes, particularly in the Great Lakes Region.

His work also includes evaluating the effectiveness of variable retention harvesting (VRH) treatments in enhancing forest carbon uptake and studying spongy moth infestations' impacts on forest ecosystems. His research provides insights into optimizing forest management for carbon sequestration and climate resilience.

Education

Doctor of Philosophy (Ph.D.), School of Earth, Environment, & Society Sciences, McMaster University, Hamilton, Ontario, Canada (2019 to 2024)

Master of Engineering (M.Eng.), School of Instrumentation Science and Opto-Electronics Engineering, Beijing University of Aeronautics and Astronautics (BUAA), China (2017 to 2019)

Master of Science (M.S.), Geography and Environment, Jahangirnagar University, Bangladesh (2016-17)

Bachelor of Science (B.Sc.), Geography and Environment, Jahangirnagar University, Bangladesh (2011-2015)

Publications

Hussain, N., Gonsamo, A., Wang, S., & Arain, M. A. (2024). Assessment of spongy moth infestation impacts on forest productivity and carbon loss using the Sentinel-2 satellite remote sensing and eddy covariance flux data. Ecological Processes, 13(1), 37.

Hussain, N., Arain, M. A., Wang, S., Parker, W. C., & Elliott, K. A. (2024). Evaluating the effectiveness of different variable retention harvesting treatments on forest carbon uptake using remote sensing. Remote Sensing Applications: Society and Enviro

Hussain, N., Ahmed, S. S., & Shumi, A. M. (2023). Remote sensing‐based geostatistical hot spot analysis of Urban Heat Islands in Dhaka, Bangladesh. Singapore Journal of Tropical Geography, 44(3), 438-458.

Hussain, N., & Islam, M. N. (2020). Hot spot (G i∗) model for forest vulnerability assessment: a remote sensing-based geo-statistical investigation of the Sundarbans mangrove forest, Bangladesh. Modeling Earth Systems and Environment, 6(4), 2141-2151.