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 (KLIP) addresses this 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 objective of this study is to produce an updated, cloud-based NDVI product, potentially allowing for earlier payouts that may help herders to prevent, minimize, or offset drought-induced losses. The new product, named reNDVI (rapid enhanced NDVI), provides an updated cloud filtering algorithm and brings the entire processing chain to the cloud. Access to the scripts used for the processing described and resulting data is openly available. To test the performance of the new product, we provide a robust evaluation of reNDVI and eMODIS NDVI and their derived payout indices against historical drought, payouts provided, and mortality data. The implications of potential payout differences are also discussed. The products show good comparability; the monthly average NDVI per UAI has correlation values over 0.95 and MAPD under 5% for most UAIs. However, there are moderate differences when assessing year-to-year payout amounts triggered. Because the payouts are currently calculated based on the 20th and first percentile of index values from 2003–2016, payouts are very sensitive to even small changes in NDVI. Where livestock mortality was available, payouts for reNDVI and eMODIS had similar correlations (r = 0.453 and r = 0.478, respectively) with mortality rates. Therefore, with the potential reduced latency and updated cloud filtering, the reNDVI product could be a suitable replacement for eMODIS in the Kenya Livestock Insurance Program. The updated reNDVI product shows promise as a vegetation index that could address a pressing drought insurance challenge.

中文翻译：

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评估时空一致的MODIS衍生NDVI产品在基于指数的干旱保险中的应用

在东部和南部非洲的干旱和半干旱地区，干旱可能对牧民造成严重破坏，而牧民依靠健康的草畜作为牧群。肯尼亚牲畜保险计划（KLIP）通过其保险计划解决了这一挑战，该保险计划依赖于源自eMODIS NDVI（增强的标准化差异植被指数）的植被指数产品。当指数值低于保险单位面积（UAI）的特定阈值时，将触发保险支出。这项研究的目的是生产一种更新的基于云的NDVI产品，有可能允许较早的支出，这可能有助于牧民预防，减少或抵消干旱引起的损失。新产品名为reNDVI（快速增强型NDVI），提供了更新的云过滤算法，并将整个处理链带到了云中。可以公开访问用于描述的处理脚本和结果数据。为了测试新产品的性能，我们对reNDVI和eMODIS NDVI及其相对于历史干旱，提供的支出和死亡率数据的派生支出指数进行了可靠的评估。还讨论了潜在支出差异的含义。产品具有良好的可比性；对于大多数UAI，每个UAI的月平均NDVI具有超过0.95的相关值，而MAPD则低于5％。但是，评估触发的年度支付金额时存在中等差异。由于目前的支出是基于2003-2016年指数值的第20个百分点和第一个百分位数计算的，因此即使对NDVI的微小变化也非常敏感。有牲畜死亡率的地方，reNDVI和eMODIS的支出与死亡率具有相似的相关性（分别为r = 0.453和r = 0.478）。因此，由于潜在的延迟减少和更新的云过滤，reNDVI产品可能是肯尼亚牲畜保险计划中eMODIS的合适替代品。更新后的reNDVI产品显示出作为植被指数的希望，可以解决紧迫的干旱保险挑战。