Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi

A collection of spectral indices, derived from a range of remote sensing imagery spatial resolutions, are compared to on-farm measurements of maize chlorophyll content and yield at two trial farms in central Malawi to evaluate what spatial resolutions are most effective for relating multispectral im...

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Bibliographic Details
Published in:Photogrammetric engineering and remote sensing 2020-02, Vol.86 (2), p.107-119
Main Authors: Peter, Brad G., Messina, Joseph P., Carroll, Jon W., Zhi, Junjun, Chimonyo, Vimbayi, Lin, Shengpan, Snapp, Sieglinde S.
Format: Article
Language:English
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Summary:A collection of spectral indices, derived from a range of remote sensing imagery spatial resolutions, are compared to on-farm measurements of maize chlorophyll content and yield at two trial farms in central Malawi to evaluate what spatial resolutions are most effective for relating multispectral images with crop status. Single and multiple linear regressions were tested for spatial resolutions ranging from 7 cm to 20 m using a small unmanned aerial system ( sUAS ) and satellite imagery from Planet, SPOT 6, Pléiades, and Sentinel-2. Results suggest that imagery with spatial resolutions nearer the maize plant scale (i.e., 14-27 cm) are most effective for relating spectral signals with crop health on smallholder farms in Malawi. Consistent with other studies, green-band indices were more strongly correlated with maize chlorophyll content and yield than conventional red-band indices, and multivariable models often outperformed single variable models.
ISSN:0099-1112
DOI:10.14358/PERS.86.2.107