Uniting remote sensing, crop modelling and economics for agricultural risk management

The increasing availability of satellite data at higher spatial, temporal and spectral resolutions is enabling new applications in agriculture economic development, including agricultural insurance. Yet, effectively using this context requires blending technical knowledge about their capabilities limitations with an understanding influence on the value risk-reduction programmes. In Review, we discuss how approaches to estimate losses for index insurance have evolved from costly field-sampling-based campaigns towards lower-cost techniques weather data. We identify advances remote sensing crop modelling assessing conditions, but reliably cheaply production remains challenging complex landscapes. illustrate framework can be used gauge enhance based earth-observation data, emphasizing that even as yield-estimation improve, contract insured depends largely well it captures when people suffer most. Strategically improving collection accessibility reliable ground-reference types would facilitate task. Audits account inevitable misestimation complement efforts detect protect against large losses. Improvements earth observation are assess losses, such those resulting adverse weather. This Review examines application remotely sensed index-based opportunities quality