Early mapping of winter wheat in Henan province of China using time series of Sentinel-2 data
Accurate mapping of winter wheat in its early stages is crucial for crop growth monitoring and crop yield forecasting. However, early mapping of winter wheat using remotely sensed data is challenging because remote sensing observations can only be used for a part of the growth period. In this study,...
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| Published in | GIScience and remote sensing Vol. 59; no. 1; pp. 1534 - 1549 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Taylor & Francis
31.12.2022
Taylor & Francis Group |
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| Online Access | Get full text |
| ISSN | 1548-1603 1943-7226 1943-7226 |
| DOI | 10.1080/15481603.2022.2104999 |
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| Abstract | Accurate mapping of winter wheat in its early stages is crucial for crop growth monitoring and crop yield forecasting. However, early mapping of winter wheat using remotely sensed data is challenging because remote sensing observations can only be used for a part of the growth period. In this study, a framework was proposed for early season mapping of winter wheat using spectral and temporal information of Sentinel-2 images. First, time series of temporal and spectral features were derived using Whittaker smoothing. Subsequently, sensitivities of different parameters (i.e. input features, time interval, and length of time-series data) to early mapping were analyzed. Finally, early maps of winter wheat were generated based on optimal parameters. Results show that the earliest identifiable timing was delayed as the time interval of the time series increased. Winter wheat can be mapped in the early overwintering period (5 months before harvest) with an overall accuracy of 0.91, which is comparable to that of post-season mapping (0.94). In addition, the misclassification in early mapping was caused by uneven sample spatial patterns, natural conditions, and planting management; however, most errors can be gradually amended during the green-up and jointing periods, and the overall accuracy remained stable after the jointing stage. This study demonstrates that it is feasible to implement large-scale early mapping of winter wheat using satellite observations. The proposed approach potentially provides a reference for early mapping of other crop types in agricultural regions worldwide. |
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| AbstractList | Accurate mapping of winter wheat in its early stages is crucial for crop growth monitoring and crop yield forecasting. However, early mapping of winter wheat using remotely sensed data is challenging because remote sensing observations can only be used for a part of the growth period. In this study, a framework was proposed for early season mapping of winter wheat using spectral and temporal information of Sentinel-2 images. First, time series of temporal and spectral features were derived using Whittaker smoothing. Subsequently, sensitivities of different parameters (i.e. input features, time interval, and length of time-series data) to early mapping were analyzed. Finally, early maps of winter wheat were generated based on optimal parameters. Results show that the earliest identifiable timing was delayed as the time interval of the time series increased. Winter wheat can be mapped in the early overwintering period (5 months before harvest) with an overall accuracy of 0.91, which is comparable to that of post-season mapping (0.94). In addition, the misclassification in early mapping was caused by uneven sample spatial patterns, natural conditions, and planting management; however, most errors can be gradually amended during the green-up and jointing periods, and the overall accuracy remained stable after the jointing stage. This study demonstrates that it is feasible to implement large-scale early mapping of winter wheat using satellite observations. The proposed approach potentially provides a reference for early mapping of other crop types in agricultural regions worldwide. Accurate mapping of winter wheat in its early stages is crucial for crop growth monitoring and crop yield forecasting. However, early mapping of winter wheat using remotely sensed data is challenging because remote sensing observations can only be used for a part of the growth period. In this study, a framework was proposed for early season mapping of winter wheat using spectral and temporal information of Sentinel-2 images. First, time series of temporal and spectral features were derived using Whittaker smoothing. Subsequently, sensitivities of different parameters (i.e. input features, time interval, and length of time-series data) to early mapping were analyzed. Finally, early maps of winter wheat were generated based on optimal parameters. Results show that the earliest identifiable timing was delayed as the time interval of the time series increased. Winter wheat can be mapped in the early overwintering period (5 months before harvest) with an overall accuracy of 0.91, which is comparable to that of post-season mapping (0.94). In addition, the misclassification in early mapping was caused by uneven sample spatial patterns, natural conditions, and planting management; however, most errors can be gradually amended during the green-up and jointing periods, and the overall accuracy remained stable after the jointing stage. This study demonstrates that it is feasible to implement large-scale early mapping of winter wheat using satellite observations. The proposed approach potentially provides a reference for early mapping of other crop types in agricultural regions worldwide. |
| Author | Huang, Xianda Chen, Zhengchao Huang, Jianxi Li, Xuecao Shen, Qianrong |
| Author_xml | – sequence: 1 givenname: Xianda surname: Huang fullname: Huang, Xianda organization: China Agricultural University – sequence: 2 givenname: Jianxi surname: Huang fullname: Huang, Jianxi email: jxhuang@cau.edu.cn organization: Ministry of Agriculture – sequence: 3 givenname: Xuecao surname: Li fullname: Li, Xuecao organization: Ministry of Agriculture – sequence: 4 givenname: Qianrong surname: Shen fullname: Shen, Qianrong organization: China Agricultural University – sequence: 5 givenname: Zhengchao surname: Chen fullname: Chen, Zhengchao organization: Aerospace Information Research Institute, Chinese Academy of Sciences |
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| SubjectTerms | China crop mapping crop yield early season overwintering remote sensing satellites Sentinel-2 time series time series analysis Winter wheat |
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| Title | Early mapping of winter wheat in Henan province of China using time series of Sentinel-2 data |
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