Field-scale Crop Yield Prediction

Field-scale satellite observations, physical models, and machine learning combined can enable crop yield prediction at high spatial resolution at data-scarse regions. Learn more about it [here](research/crop_yields_zambia).

Cognitive Biases about Climate Variability in Smallholder Farming Systems in Zambia

Given the varying manifestations of climate change over time and the influence of climate perceptions on adaptation, it is important to understand whether farmer perceptions match patterns of environmental change from observational data. We use a …

Comparing empirical and survey-based yield forecasts in a dryland agro-ecosystem

Accurate crop yield forecasts before harvest are crucial for providing early warning of agricultural losses, so that policy-makers can take steps to minimize hunger risk. Within-season surveys of farmers’ end-of-season harvest expectations are one …