Research conducted in the EcodynLab incorporates field work and modeling geared towards understanding the impacts of land management and environmental change on the provisioning of ecosystems goods and services – more specifically carbon sequestration, crop production, water quality, wildlife habitat provision, and urban climate regulation. ​ We develop of novel instrumentation and quantitative techniques to leverage measurements from leaf-level, canopy-level and landscape-scale satellite, airborne, and unmanned aerial system (UAS)-borne spectroscopic imagery and LiDAR to assess forest and crop canopy structure, biochemistry, and function. We use these measurements to assess crop and forest health, to detect stress in pest and pathogen-affected plants, and to detect effects of water and thermal stress on photosynthetic potential of tree species and agricultural crops. The focus of our research is to use this information to drive mechanistic ecophysiology models to predict spatio­temporal differences in plant productivity. We also develop novel instrumentation and a broad spectrum of analytical methods spanning statistical, machine learning, and deep learning-based approaches.​ We are broadly supported by NASA, USDA, NSF, and DOE funds in addition to funding from the state of Florida and internal grants from the university. These projects span topics such as plant phenotyping, mapping of forest canopy biochemistry, structure, and function using hyperspectral imagery, invasive species control, the use of energy crops in improving ecosystem service delivery, and international research in food insecurity and causes and consequences of land degradation. ​