Do Satellite Data Correlate with In Situ Rainfall and Smallholder Crop Yields? Implications for Crop Insurance

Adverse weather is one of the most prevalent sources risk in agriculture. Its impacts are aggravated by lack effective management mechanisms. That why resource-poor farmers tend to respond risks adopting low-capital investment, low-return, and low-risk agricultural practices. This challenge needs be addressed with innovative strategies. One tools that gaining traction, especially developing countries, weather-index-based insurance (WII). However, WII uptake still low because several constraints, which basis risk. study attempts address this problem evaluating suitability TAMSAT, CHIRPS, MODIS, Sentinel-2 data for WII. We evaluated first three datasets against situ rainfall measurements at different spatial temporal scales over maize-growing season a smallholder farming area South Africa. CHIRPS had higher correlations measured than TAMSAT MODIS NDVI. performed equally well 10 km 25 scales, better monthly daily 16-day time steps (maximum R = 0.78, mean 0.72). Due reliable historical yield data, we conducted surveys consecutive seasons using an objective crop cut method. then assessed how NDVI related maize yield. There was poor relationship between these variables (R2 ≤ 0.14). The concludes pointing out does not always have linear vegetation indices, water main yield-limiting factor systems. To minimize risk, process designing must include identification factors specific localities. Alternatively, insurers could use requirement methods design