Rate My Professor Phuong Dao

Dao's research specializations include remote sensing, geospatial science, machine learning applications in agriculture, plant ecophysiology, precision agriculture, and plant-disturbance interactions. Directing the Remote Sensing and Environmental Intelligence Lab (ReSEIL) at CSU, he integrated multi-source remote sensing, high-throughput plant phenotyping, genetic methods, biological modeling, and AI to explore how plant chemical responses at the species level affect health, growth, and functioning amid disturbances like drought and invasives. His scholarly impact is evidenced by over 2,279 citations on Google Scholar. Key publications encompass 'Recent advances of hyperspectral imaging technology and applications in agriculture' (Remote Sensing, 2020; 1,372 citations), 'Object-based flood mapping and affected rice field estimation with Landsat 8 OLI and MODIS data' (Remote Sensing, 2015; 133 citations), 'Plant drought impact detection using ultra-high spatial resolution hyperspectral images and machine learning' (International Journal of Applied Earth Observation and Geoinformation, 2021; 94 citations), 'From spectra to plant functional traits: Transferable multi-trait models from heterogeneous and sparse data' (Remote Sensing of Environment, 2023; 76 citations), and 'Imaging spectroscopy reveals topographic variability effects on grassland functional traits and drought responses' (Ecology, 2025). Major awards include a USDA-NIFA grant of $500,000 in 2024 for an advanced high-throughput plant phenotyping system. He contributed editorially as Associate Editor for Agrosystems, Geosciences & Environment (appointed October 2024) and Austral Ecology (2022-2024).