The Comoros, a small island developing state (SIDS) ranking among the poorest nations in Africa, is facing numerous challenges that make it particularly vulnerable to food insecurity: as a remotely located, net-food importing country with a small landmass, limited agricultural land and high exposure to natural catastrophes, the Comoros’ food security is particularly vulnerable to external shocks. While being a net-food importer, agriculture is an essential sector and livelihood source, contributing 30 percent to gross domestic product in 2015. This makes the Comoros a rare exemption across small island developing states. Investing in the Comoros’ agrifood systems and increasing their efficiency is essential to increase food security. So far, a lack of data in the Comoros’ agrifood systems has limited the scope of analyses. The use of remotely sensed data for crop yield models presents a cost-effective opportunity for the Comoros to continuously monitor its agricultural sector, and reduce its data gap and the high cost associated with surveys. Based on two different sensors, MODIS-TERRA and Sentinel-2, and a unique FAO survey conducted in 2021 which georeferenced farm plots, we derive a method to calibrate vegetation indices (NDVI) as a proxy for crop yield in the Comoros. Our results suggest that the MODIS sensor is not well adapted to estimate yields in the Comoros. Plots are on average less than 1 ha, while the MODIS spatial resolution is 250 m by 250 m which leads to less consistency and less variation within a plot. Sentinel 2 images seem more consistent with survey-based crop yield estimates. We finally managed to proxy manioc yields by putting restrictions on the highest yields producers. The coefficient of determination is up to 0.28 when dealing with farmers producing at least 40 percent of manioc.