Extraction of Areas of Rice False Smut Infection Using UAV Hyperspectral Data
نویسندگان
چکیده
Rice false smut (RFS), caused by Ustilaginoidea virens, is a significant grain disease in rice that can lead to reduced yield and quality. In order obtain spatiotemporal change information, multitemporal hyperspectral UAV data were used this study determine the sensitive wavebands for RFS identification, 665–685 705–880 nm. Then, two methods extraction of smut-infected areas, one based on spectral similarity analysis temporal characteristics. The final overall accuracy was 74.23 85.19%, respectively, showing second method had better prediction accuracy. addition, classification results show areas infection an expanding trend over time, which consistent with natural development law smut, also shows scientific nature methods.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2021
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs13163185