您好，欢迎访问四川省农业科学院 机构知识库！

Extraction of Areas of Rice False Smut Infection Using UAV Hyperspectral Data

文献类型： 外文期刊

作者： An, Gangqiang 1 ; Xing, Minfeng 1 ; He, Binbin 1 ; Kang, Haiqi 3 ; Shang, Jiali 4 ; Liao, Chunhua 5 ; Huang, Xiaodong; 1 ;

作者机构： 1.Univ Elect Sci & Technol China, Sch Resources & Environm, Chengdu 611731, Sichuan, Peoples R China

2.Univ Elect Sci & Technol China, Yangtze Delta Reg Inst Huzhou, Huzhou 313001, Peoples R China

3.Sichuan Acad Agr Sci, Crop Res Inst, Chengdu 610066, Sichuan, Peoples R China

4.Agr & Agri Food Canada, Ottawa Res & Dev Ctr, 960 Carling Ave, Ottawa, ON K1A 0C6, Canada

5.Sun Yat Sen Univ, Sch Geospatial Engn & Sci, Zhuhai 519082, Peoples R China

6.Appl Geosolut, 15 Newmarket Rd, Durham, NH 03824 USA

关键词： UAV; hyperspectral data; rice; rice false smut

期刊名称：REMOTE SENSING （ 影响因子：4.848； 五年影响因子：5.353 ）

ISSN：

年卷期： 2021 年 13 卷 16 期

页码：

收录情况： SCI

摘要： 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 to obtain spatiotemporal change information, multitemporal hyperspectral UAV data were used in this study to determine the sensitive wavebands for RFS identification, 665-685 and 705-880 nm. Then, two methods were used for the extraction of rice false smut-infected areas, one based on spectral similarity analysis and one based on spectral and temporal characteristics. The final overall accuracy of the two methods was 74.23 and 85.19%, respectively, showing that the second method had better prediction accuracy. In addition, the classification results of the two methods show that the areas of rice false smut infection had an expanding trend over time, which is consistent with the natural development law of rice false smut, and also shows the scientific nature of the two methods.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：四川省农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台