Assessment of a spatially and temporally consistent MODIS derived NDVI product for application in index-based drought insurance

In arid and semi-arid regions of Eastern and Southern Africa, drought can be devastating to pastoralists who depend on healthy vegetation for their herds. The Kenya Livestock Insurance Program addresses this persistent challenge through its insurance program that relies on a vegetation index product derived from eMODIS NDVI (enhanced Normalized Difference Vegetation Index). Insurance payouts are triggered when index values fall below a certain threshold for a Unit Area of Insurance (UAI). The NDVI product has a latency of about one month to allow for cloud filtering, which delays insurance payouts. This study produced a reduced-latency NDVI product, potentially allowing for earlier payouts, which may equip herders to prevent, minimize, or offset drought-induced losses. This product, named reNDVI (rapid enhanced NDVI), is compared to the existing NDVI product using statistical analyses to test its potential as a suitable replacement. Statistics included correlation, regression analysis, and mean absolute percent error (MAPE). Implications in potential payout differences were also evaluated. The products show good comparability; monthly average NDVI per UAI have correlation values over 0.95 and MAPE under 5% for most UAIs. However, there were moderate differences when assessing year-to-year payout amounts triggered. Because the payouts are currently calculated based on the 20th and 1st percentile of index values from 2003-2016, payouts are very sensitive to even small changes in NDVI. Though reNDVI does not perfectly mimic payouts calculated from eMODIS, it shows promise as a lower-latency vegetation index that could address a pressing drought risk transfer challenge.