Detection of the Optimal Temporal Windows for Mapping Paddy Rice Under a Double-Cropping System Using Sentinel-2 Imagery
Accurately mapping paddy rice is crucial for food security, sustainable agricultural management and environmental protection. Recently, Sentinel-2 optical images with a spatial resolution of 10 m and a repeat cycle of five days have demonstrated enormous potential for mapping paddy fields. However,...
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MDPI AG
2024-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/1/57 |
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| author | Li Sheng Yuefeng Lv Zhouqiao Ren Hongkui Zhou Xunfei Deng |
| author_facet | Li Sheng Yuefeng Lv Zhouqiao Ren Hongkui Zhou Xunfei Deng |
| author_sort | Li Sheng |
| collection | DOAJ |
| description | Accurately mapping paddy rice is crucial for food security, sustainable agricultural management and environmental protection. Recently, Sentinel-2 optical images with a spatial resolution of 10 m and a repeat cycle of five days have demonstrated enormous potential for mapping paddy fields. However, the influence of the temporal selection of Sentinel-2 optical images on mapping paddy rice is still unclear. In this study, the optimal temporal windows were detected by considering all possible temporal combinations during the growing stages from the constructed cloud-free 10-day time series and assessing the classification performances of all combination schemes on paddy rice mapping by F1_score. The results indicated that the combination of two or three phases is necessary for mapping early-cropping paddy rice (EP) and late-cropping paddy rice (LP), achieving the F1_score aim of 0.96. The detection of single-cropping paddy rice (SP) requires a combination of three to five phases and can obtain the F1_score aim of 0.94. Additionally, an automatic workflow for paddy rice mapping has been developed, which does not require any cloud removal but provides complete spatial coverage, suitable for regions with frequent rain and clouds. Through verification in the study area of Yiwu, China, the discrepancies between mapping results and agricultural statistics were within 5%, demonstrating the rationality and efficiency of the proposed framework. |
| format | Article |
| id | doaj-art-7e19ffc1b2ea4da5b1ab00bc78eaf2c3 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-7e19ffc1b2ea4da5b1ab00bc78eaf2c32025-01-10T13:20:06ZengMDPI AGRemote Sensing2072-42922024-12-011715710.3390/rs17010057Detection of the Optimal Temporal Windows for Mapping Paddy Rice Under a Double-Cropping System Using Sentinel-2 ImageryLi Sheng0Yuefeng Lv1Zhouqiao Ren2Hongkui Zhou3Xunfei Deng4Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, ChinaSchool of Public Administration, Zhejiang University of Finance and Economics, Hangzhou 310018, ChinaInstitute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, ChinaInstitute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, ChinaInstitute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, ChinaAccurately mapping paddy rice is crucial for food security, sustainable agricultural management and environmental protection. Recently, Sentinel-2 optical images with a spatial resolution of 10 m and a repeat cycle of five days have demonstrated enormous potential for mapping paddy fields. However, the influence of the temporal selection of Sentinel-2 optical images on mapping paddy rice is still unclear. In this study, the optimal temporal windows were detected by considering all possible temporal combinations during the growing stages from the constructed cloud-free 10-day time series and assessing the classification performances of all combination schemes on paddy rice mapping by F1_score. The results indicated that the combination of two or three phases is necessary for mapping early-cropping paddy rice (EP) and late-cropping paddy rice (LP), achieving the F1_score aim of 0.96. The detection of single-cropping paddy rice (SP) requires a combination of three to five phases and can obtain the F1_score aim of 0.94. Additionally, an automatic workflow for paddy rice mapping has been developed, which does not require any cloud removal but provides complete spatial coverage, suitable for regions with frequent rain and clouds. Through verification in the study area of Yiwu, China, the discrepancies between mapping results and agricultural statistics were within 5%, demonstrating the rationality and efficiency of the proposed framework.https://www.mdpi.com/2072-4292/17/1/57paddy rice mappingdouble-cropping systemSentinel-2temporal window analysis |
| spellingShingle | Li Sheng Yuefeng Lv Zhouqiao Ren Hongkui Zhou Xunfei Deng Detection of the Optimal Temporal Windows for Mapping Paddy Rice Under a Double-Cropping System Using Sentinel-2 Imagery Remote Sensing paddy rice mapping double-cropping system Sentinel-2 temporal window analysis |
| title | Detection of the Optimal Temporal Windows for Mapping Paddy Rice Under a Double-Cropping System Using Sentinel-2 Imagery |
| title_full | Detection of the Optimal Temporal Windows for Mapping Paddy Rice Under a Double-Cropping System Using Sentinel-2 Imagery |
| title_fullStr | Detection of the Optimal Temporal Windows for Mapping Paddy Rice Under a Double-Cropping System Using Sentinel-2 Imagery |
| title_full_unstemmed | Detection of the Optimal Temporal Windows for Mapping Paddy Rice Under a Double-Cropping System Using Sentinel-2 Imagery |
| title_short | Detection of the Optimal Temporal Windows for Mapping Paddy Rice Under a Double-Cropping System Using Sentinel-2 Imagery |
| title_sort | detection of the optimal temporal windows for mapping paddy rice under a double cropping system using sentinel 2 imagery |
| topic | paddy rice mapping double-cropping system Sentinel-2 temporal window analysis |
| url | https://www.mdpi.com/2072-4292/17/1/57 |
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