Use of time series normalized difference vegetation index (NDVI) to monitor fall armyworm (Spodoptera frugiperda) damage on maize production systems in Africa. Issue 1 (31st December 2023)

• Record Type: Journal Article
• Authors: Adan, Marian; Tonnang, Henri E. Z.; Greve, Klaus; Borgemeister, Christian; Goergen, Georg
• Is Part Of: Geocarto international. Volume 38:Issue 1(2023)
• Publication Date: 2023-12-31
• Subjects: Landsat 8 -- Google Earth Engine (GEE) -- vegetation productivity -- fall armyworm -- normalized difference vegetation index; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2023.2186492
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract: Fall armyworm (FAW) Spodoptera frugiperda (J.E. Smith), damage was monitored at a regional scale using time series data in Western and Southern African countries. The study employed the normalized difference vegetation index (NDVI) computed from Landsat 8 imagery using the Google Earth Engine (GEE) using image composites for the years 2013 to 2020 for the study areas. The index was then reclassified based on the NDVI threshold values into low, sparse, moderate, and dense classes. FAW prevalence data were then utilized to validate the correlation between the FAW infestation and NDVI values. FAW was associated with a decrease in vegetation productivity between the years 2016, 2017, and 2018 when the pest infestation was reported in the study areas. The validation results showed that there is a correlation between FAW infestation and NDVI (R 2 0.83). Our study highlighted that NDVI can be used as a proxy to quantify pest damage to vegetation productivity.