Abstract
ABSTRACT Predictable outcomes from precision agriculture (PA) solutions require accurate measurements of crop status and a remote sensing knowledgebase that spans ecoregions. This paper evaluates the relationships between 20 multispectral vegetation indices derived from small unmanned aircraft system (sUAS) image collection and on-farm measurements of crop chlorophyll content at two smallholder experimentation maize farms in Malawi with varied nitrogen fertilizer treatments. Results of this analysis show that prominent green-based multispectral indices, such as the green normalized difference vegetation index (GNDVI), were among the models with the strongest correlations. This study is consistent with other research in this field, contributes to mounting evidence supporting a shift in status quo for greater adoption of green-based indices in PA, and offers data specific to the semi-arid sub-Saharan context.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
