Remote Sensing for Index Insurance: Findings and Lessons so Far

This case study provides an overview of a project undertaken by the International Fund for Agricultural Development and World Food Programme that intends to evaluate the feasibility of remote sensing for index insurance to fill critical gaps of quality, long-term weather, and yield data. It assesses the efficiency of different remote sensing methodologies that were used in the 2013 crop season. The study also highlights lessons learned after the first test season of developing and analyzing remote sensing products for index insurance to accurately depict yield loss in smallholder farming due to weather and other perils. Key lessons include:

• Although the performance of the different methodologies has been encouraging, some improvement is needed;
• In most cases, the season-start timing detected by the methodologies was found to be within the range of the observed start-of-season periods;
• Performance of remote sensing methodologies varied for different crops;
• Remote sensing provides a spatial zoning tool that makes it possible to segment geographical areas by risk profile and thus identify appropriately sized unit areas of insurance;
• Some of the project methodologies had the potential to generate more effective results if they were able to segment areas to be monitored.