The role of Earth observation and ancillary data to support fall armyworm monitoring in maize crop in Rwanda

Agriculture is the main stain of the Rwandan economy, covering more than 62% of the country’s employment. However, pest infections pose a serious threat to Rwandan agriculture as well as food security with a severe negative impact on smallholder farmers. Fall armyworm (FAW) is one of the most destructive pests of maize and other cereal crops in Rwanda. However, the risks and the damage of the FAW outbreak are not the same across Rwanda because of differences in crop extent and management as well as climatic conditions. Estimating the risk of FAW infestation in maize and other cereal crops is essential to support FAW management and the Rwandan Integrated Pest Management (IPM) Programme. In this study, using a combination of field surveys, sentinel 2 data, and ancillary data, we conducted a two-stage analysis: (1) Using vegetation indices derived from sentinel-2, we monitored maize stress due to FAW infestation in a 24 ha marshland in the Eastern province of Rwanda. (2) We developed a country-wide risk assessment of the FAW outbreak specifically for maize crops. Overall, the results show that FAW is indeed a threat to maize crop, especially in large-scale monoculture maize crop. During the agricultural season A (September-December, 2022), we found a significant decrease in maize biomass in the investigated marshland due to the FAW outbreak. At the country level, we found that FAW follows predictable patterns related to crop management, climatic conditions, and soil fertility conditions. Furthermore, the results suggest that the risk of FAW infestation is higher in the Eastern agroecological (~ 70%) and lower in the Central and Western zones (~40%) likely because of differences in the extent of maize crop production system. The results suggest that long-term monoculture practised in the consolidated agriculture has significantly increased the risk of FAW across Rwanda.   This repository contains data and code used for the analysis of a paper submitted to a special issue and will regularly be updated until the acceptance of the paper.