期刊
GEOCARTO INTERNATIONAL
卷 33, 期 11, 页码 1223-1236出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/10106049.2017.1343391
关键词
Field spectroscopy; grey leaf spot; spectral re-sampling; multispectral remote sensing
In this study, we tested whether GLS field symptoms on maize can be detected using hyperspectral data re-sampled to WorldView-2, Quickbird, RapidEye and Sentinel-2 resolutions. To achieve this objective, Random Forest algorithm was used to classify the 2013 re-sampled spectra to represent the three identified disease severity categories. Results showed that Sentinel-2, with 13 spectral bands, achieved the highest overall accuracy and kappa value of 84% and 0.76, respectively, while the WorldView-2, with eight spectral bands, yielded the second highest overall accuracy and kappa value of 82% and 0.73, respectively. Results also showed that the 705 and 710nm red edge bands were the most valuable in detecting the GLS for Sentinel-2 and RapidEye, respectively. On the re-sampled WorldView 2 and Quickbird sensor resolutions, the respective 608 and 660nm in the yellow and red bands were identified as the most valuable for discriminating all categories of infection.
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