Member of the Graduate Faculty | Research Professor, Electrical and Computer Engineering | Professor, Remote Sensing / Spatial Analysis - GIDP | Professor, Biosystems Engineering
The focus of my teaching and research is global remote sensing of the land surface vegetation and the development of remote sensing measurements, data, algorithms, and models for calibrated time series analysis aimed at assessing 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 data and techniques to address engineering and societal challenges from agricultural production to ecosystem management, and from watershed to regional to global levels. My research grouhas also developed an engineering and application-oriented program for the use of drones as fast and cost-effective platforms for land surface characterization, precision mapping, precision agriculture, and the low-cost validation of global remote sensing data. I have been particularly promoting a program that actively engages undergraduate and graduate students to pursue their research and academic interests through internships, MS and Ph.D. research support, and creative and immersive research through collaboration and teamwork.
The Department of the Interior has awarded a grant to Professor Kamel Didan from Biosystems Engineering for the project titled "Natural Vegetation Water Use and Efficiency at the US-Mexico Transboundary Region." Dr. Didan, a remote sensing expert, along with his VIP Lab (vip.arizona.edu) students and personnel, are leading the research aimed at studying water use and efficiency in natural vegetation along the US-Mexico border. Key components of the project include:
- Harmonizing regional land cover maps using a machine learning classification model to support transboundary natural resources and ecohydrology research.
- Utilizing remote sensing techniques to analyze the impact of climate and land use changes on vegetation water use.
- Offering insights to guide decision-making, restoration efforts, habitat quality assessments, and enhance regional resilience at the US-Mexico border.
- Expanding our understanding of transboundary water challenegs and its broader impact on regional vegetation.
Development of Algorithms and time series data from Remote sensing platforms, Time series analysis in support of Ecosystem and natural resources management, Climate-related and land use change influences on vegetation and phenology, Multidisciplinary use of remote sensing data, Development of a UAV/drone based program for the precision observation of the environment, including precision Agriculture, land mapping, and space-borne data validation. Prerequisite Courses: Data Science, Programming (Python), Image processing Majors: Computer Science, ECE, Natural Resources
Development of Algorithms and time series data from Remote sensing platforms, Time series analysis in support of Ecosystem and natural resources management, Climate-related and land use change influences on vegetation and phenology, Multidisciplinary use of remote sensing data, Development of a UAV/drone based program for the precision observation of the environment, including precision Agriculture, land mapping, and space-borne data validation. Prerequisite Courses: Data Science, Programming (Python), Image processing Majors: Computer Science, ECE, Natural Resources