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

• Published in: International journal of remote sensing 2004-01, Vol.25 (2), p.489-498
• Main Authors: Apan, A., Held, A., Phinn, S., Markley, J.
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Fundamental and applied biological sciences. Psychology; Fungal plant pathogens; Pathology, epidemiology, host-fungus relationships. Damages, economic importance; Phytopathology. Animal pests. Plant and forest protection
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431160310001618031

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.