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Improved Paddy Rice Classification Utilizing Sentinel-1/2 Imagery in Anhui China: Phenological Features, Algorithms, Validation and Analysis

文献类型：期刊论文

作者Wang, Zeling3,4,5; Sun, Xiaobing2,4; Liu, Xiao2,4; Xu, Feifei1; Huang, Honglian4; Ti, Rufang4; Yu, Haixiao4,5; Wang, Yuxuan4,5; Wei, Yichen4,5
刊名AGRICULTURE-BASEL
出版日期2024-08-01
卷号14期号:8页码:21
关键词phenology rice automatic sample expansion spectral index
DOI10.3390/agriculture14081282
产权排序5
英文摘要Enhancing the accuracy of paddy rice mapping is crucial for bolstering global food security. Prior research incorporating Sentinel imagery with phenological characteristics has identified paddy rice fields effectively. However, challenges such as reliance on a single index, cloud cover interference, and a lack of sufficient training samples continue to complicate the mapping of paddy rice. This study introduces a comprehensive paddy rice mapping framework that incorporates annual phenological features throughout the entire growth phase. This was achieved by expanding the sample size through the extraction of phenological features, and the visually verified samples were then integrated with distinct phenological phases and relevant indices, utilizing hybrid Sentinel-1/2 imagery to map paddy rice distribution. The accuracy of the generated rice map was validated against trusted samples, corroborative agricultural statistics, and another high-resolution 10 m mapping product. Compared with ground-truth samples, the algorithm has achieved an overall accuracy of approximately 92% in most rice production regions with a confusion matrix. Additionally, the estimated rice area in Anhui and several other rice-producing regions shows less than 10% error when compared with governmental statistical records from the yearbook. When compared with another recent paddy rice map at the same spatial resolution (10 m), our approach provided cleaner details and more effectively reduced omission errors. It received values of R2 = 0.991 and slope = 1.08 in a prefecture-level statistical comparison with a counterpart. Our proposed approach is proven to be valid and is expected to offer significant benefits to agricultural sustainability and technological applications in farming.
WOS关键词LAND-USE CHANGE ; SPATIOTEMPORAL PATTERNS ; AREAS
资助项目Aerospace Science and Technology Innovation Application Research Project ; Aviation Science and Technology Innovation Application Research Project[62502510201] ; Key Laboratory Project of Chinese Academy of Sciences[E33Y0HB42P1] ; China High-resolution Earth Observation System[30-Y20A010-9007-17/18] ; China Center for Resource Satellite Data and Applications Project[HFWZ2020080302] ; [E23Y0H555S1]
WOS研究方向Agriculture
语种英语
WOS记录号WOS:001305359900001
出版者MDPI
资助机构Aerospace Science and Technology Innovation Application Research Project ; Aviation Science and Technology Innovation Application Research Project ; Key Laboratory Project of Chinese Academy of Sciences ; China High-resolution Earth Observation System ; China Center for Resource Satellite Data and Applications Project
源URL[http://ir.igsnrr.ac.cn/handle/311030/208849]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Sun, Xiaobing
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Suzhou 215100, Peoples R China
2.Chief Studio Agr Ind Hefei, Hefei 230031, Peoples R China
3.Hefei Normal Univ, Comp & Artificial Intelligence Dept, Hefei 230601, Peoples R China
4.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Hefei 230031, Peoples R China
5.Univ Sci & Technol China, Sci Isl Branch, Hefei 230026, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Zeling,Sun, Xiaobing,Liu, Xiao,et al. Improved Paddy Rice Classification Utilizing Sentinel-1/2 Imagery in Anhui China: Phenological Features, Algorithms, Validation and Analysis[J]. AGRICULTURE-BASEL,2024,14(8):21.
APA Wang, Zeling.,Sun, Xiaobing.,Liu, Xiao.,Xu, Feifei.,Huang, Honglian.,...&Wei, Yichen.(2024).Improved Paddy Rice Classification Utilizing Sentinel-1/2 Imagery in Anhui China: Phenological Features, Algorithms, Validation and Analysis.AGRICULTURE-BASEL,14(8),21.
MLA Wang, Zeling,et al."Improved Paddy Rice Classification Utilizing Sentinel-1/2 Imagery in Anhui China: Phenological Features, Algorithms, Validation and Analysis".AGRICULTURE-BASEL 14.8(2024):21.

入库方式： OAI收割

来源：地理科学与资源研究所

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