Improved drought detection to support crop insurance models: powerpoint
Anomaly assessment for drought monitoring, as required for index insurance applications, is commonly done by comparing actual NDVI measurements against their historical records on a pixel-by-pixel basis. Limited years of satellite records with operational real-time availability result in time-series with a relative low count in annual repeats, e.g., the VEGETATION sensor onboard SPOT and Proba-V has completed at present only 19 full annual repeats. This number is too low for agricultural index insurance models that require accurate assessments of impacts of perils (e.g.