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

被引:249
作者
Apan, A [1 ]
Held, A
Phinn, S
Markley, J
机构
[1] Univ So Queensland, Fac Engn & Surveying, Geospatial Informat & Remote Sensing Grp, Toowoomba, Qld 4350, Australia
[2] CSIRO Land & Water, Environm Remote Sensing Grp, Canberra, ACT 2601, Australia
[3] Univ Queensland, Sch Geog Planning & Architecture, Biophys Remote Sensing Grp, Brisbane, Qld 4072, Australia
[4] Mackay Sugar, Pleystowe, Qld 4741, Australia
关键词
D O I
10.1080/01431160310001618031
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
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.
引用
收藏
页码:489 / 498
页数:10
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