Use of time series normalized differencevegetation index (NDVI) to monitor fall armyworm(Spodoptera frugiperda) damage on maizeproduction systems in Africa

Abstract

Fall armyworm (FAW)Spodoptera frugiperda(J.E. Smith), damagewas monitored at a regional scale using time series data inWestern and Southern African countries. The study employed thenormalized difference vegetation index (NDVI) computed fromLandsat 8 imagery using the Google Earth Engine (GEE) usingimage composites for the years 2013 to 2020 for the study areas.The index was then reclassified based on the NDVI threshold val-ues into low, sparse, moderate, and dense classes. FAW preva-lence data were then utilized to validate the correlation betweenthe FAW infestation and NDVI values. FAW was associated with adecrease in vegetation productivity between the years 2016,2017, and 2018 when the pest infestation was reported in thestudy areas. The validation results showed that there is a correl-ation between FAW infestation and NDVI (R20.83). Our study high-lighted that NDVI can be used as a proxy to quantify pestdamage to vegetation productivity