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I seek to improve our understanding of crop carbon and water exchange from field to global scales. I answer my research questions with models that capture the spatio-temporal dynamics of agricultural production (area × yield) and evapotranspiration. The models are: (i) implemented in a Geographic Information System; (ii) based on principles of light-use efficiency and machine-learning; and (iii) driven by Earth observation, climate reanalysis, and other geospatial information. The work flow reduces uncertainties in crop models and improves agricultural monitoring systems, as well as motivates my teaching and training activities. Ultimately, my work increases agricultural production, enhances resilience of crops to drought and other climate shocks, and reduces CO2 emissions caused by agricultural expansion into natural ecosystems. Such outcomes help achieve Sustainable Development Goal SDG-2 (“Zero Hunger”), SDG-6 (“Clean Water and Sanitation”), SDG-13 (“Climate Action”), and SDG-15 (“Life on Land”).

Editor of Agricultural and Forest Meteorology

Expertise

  • Earth and Planetary Sciences

    • Model
    • Cartography
    • Investigation
    • Farmland
    • Vegetation Index
    • Evapotranspiration
    • Remote Sensing
    • Datum

Organisations

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