The capability of very high-resolution satellite imagery for plot-level early wheat stem rust disease detection, monitoring, and phenotyping in Ethiopia

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Abstract

Very high‑resolution satellites (VHRS) have potential for early crop disease detection and enhanced food security. The capability of multispectral SkySat and Pleiades‑Neo imagery for early detection and monitoring was assessed for wheat stem rust (SR) at the plot level. In randomized trials with contrasting fungicide and irrigation treatments, six bread wheat varieties with differing SR susceptibility were monitored using VHRS. 113 multispectral features were evaluated for their association with SR progression and associated yield loss. Several features demonstrated moderate to strong correlations with SR disease levels. Across early disease stages (healthy-mild-moderate), spectral sensitivity was dominated by Blue (B)‑based features, with Red-Blue (R-B) and Green-Blue (G-B) two-band features at mild and moderate levels, respectively. During late stages (severely-fully diseased), spectral sensitivity was driven by R-based features (e.g., R-B, R-G on both sensors) and by Deep Blue (DB), Red-Edge-DB (RE-DB), and R-DB combinations on Pleiades‑Neo. Early SR detection under moderate disease pressure was possible using ratio (RSI) and normalized difference (NDSI) spectral indices with B-G combinations. Key SkySat features such as RSI(NIR,B), RSI(R,B), and RSI(G,B) were sensitive across scenarios. This work delivers the first VHRS-based SR detection, advancing monitoring from plot to regional scales.

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