Logo image
Back
Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi
Journal article   Peer reviewed

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

Brad G. Peter, Joseph P. Messina, Jon W. Carroll, Junjun Zhi, Vimbayi Chimonyo, Shengpan Lin and Sieglinde S. Snapp
Photogrammetric engineering and remote sensing, Vol.86(2), pp.107-119
02/01/2020
DOI: https://doi.org/10.14358/PERS.86.2.107
url
https://doi.org/10.14358/PERS.86.2.107View
Published (Version of record) Open

Abstract

Geography, Physical Geology Geosciences, Multidisciplinary Imaging Science & Photographic Technology Physical Geography Physical Sciences Remote Sensing Science & Technology Technology
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, Pleiades, 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.

Metrics

1 Record Views

Details

Logo image