Kamel Didan

The focus of Dr. Didan teaching and research is global remote sensing of the land surface vegetation.  This includes the development of remote sensing algorithms, data, and models for calibrated time series analysis aimed at supporting research on climate-related and land-use change influences on vegetation, phenology, water, carbon and nutrient cycles, ecosystem composition, and function over a wide range of biomes. This work connects natural resources management and the multidisciplinary use of remote sensing to address societal challenges from food production to ecosystem management, and from watershed to regional to global levels.

My research group is also developing engineering and application-oriented programs and tools for the use of Unmanned Aerial Systems as fast and cost-effective platforms for land surface proximal observation, characterization, mapping, precision agriculture, and as tools for validating global remote sensing data.