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Detecting sugarcane 'orange rust' disease using EO-1 Hyperion hyperspectral imagery

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Abstract:

This Letter evaluates several narrow-band indices from EO-1 Hyperion imagery in discriminating sugarcane areas affected by 'orange rust' (Puccinia kuehnii) disease. Forty spectral vegetation indices (SVIs), focusing on bands related to leaf pigments, leaf internal structure, and leaf water content, were generated from an image acquired over Mackay, Queensland, Australia. Discriminant function analysis was used to select an optimum set of indices based on their correlations with the discriminant function. The predictive ability of each index was also assessed based on the accuracy of classification. Results demonstrated that Hyperion imagery can be used to detect orange rust disease in sugarcane crops. While some indices that only used visible near-infrared (VNIR) bands (e.g. SIPI and R800/R680) offer separability, the combination of VNIR bands with the moisture-sensitive band (1660 nm) yielded increased separability of rust-affected areas. The newly formulated 'Disease-Water Stress Indices' (DWSI-1=R800/R1660; DSWI-2=R1660/R550; DWSI-5=(R800+R550)/(R1660+R680)) produced the largest correlations, indicating their superior ability to discriminate sugarcane areas affected by orange rust disease.

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/01431160310001618031

Affiliations: 1: Geospatial Information and Remote Sensing (GIRS) Group, Faculty of Engineering and Surveying University of Southern Queensland Toowoomba 4350 QLD Australia, Email: apana@usq.edu.au 2: Environmental Remote Sensing Group CSIRO Land and Water PO Box 1666 Canberra ACT 2601 Australia 3: Biophysical Remote Sensing Group, School of Geography, Planning & Architecture University of Queensland Brisbane 4072 Australia 4: Mackay Sugar Post Office Pleystowe Pleystowe 4741 QLD Australia

Publication date: January 1, 2004

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