A new method for classifying maize by combining the phenological information of multiple satellite-based spectral bands
Introduction: Using satellite data to identify the planting area of summer crops is difficult because of their similar phenological characteristics.Methods: This study developed a new method for differentiating maize from other summer crops based on the revised time-weighted dynamic time warping (TW...
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2022.1089007/full |
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| author | Qiongyan Peng Ruoque Shen Jie Dong Wei Han Jianxi Huang Tao Ye Wenzhi Zhao Wenping Yuan |
| author_facet | Qiongyan Peng Ruoque Shen Jie Dong Wei Han Jianxi Huang Tao Ye Wenzhi Zhao Wenping Yuan |
| author_sort | Qiongyan Peng |
| collection | DOAJ |
| description | Introduction: Using satellite data to identify the planting area of summer crops is difficult because of their similar phenological characteristics.Methods: This study developed a new method for differentiating maize from other summer crops based on the revised time-weighted dynamic time warping (TWDTW) method, a phenology-based classification method, by combining the phenological information of multiple spectral bands and indexes instead of one single index. First, we compared the phenological characteristics of four main summer crops in Henan Province of China in terms of multiple spectral bands and indexes. The key phenological periods of each band and index were determined by comparing the identification accuracy based on the county-level statistical areas of maize. Second, we improved the TWDTW distance calculation for multiple bands and indexes by summing the rank maps of a single band or index. Third, we evaluated the performance of a multi-band and multi-period TWDTW method using Sentinel-2 time series of all spectral bands and some synthetic indexes for maize classification in Henan Province.Results and Discussion: The results showed that the combination of red edge (740.2 nm) and short-wave infrared (2202.4 nm) outperformed all others and its overall accuracy of maize planting area was about 91.77% based on 2431 field samples. At the county level, the planting area of maize matched the statistical area closely. The results of this study demonstrate that the revised TWDTW makes effective use of crop phenological information and improves the extraction accuracy of summer crops’ planting areas over a large scale. Additionally, multiple band combinations are more effective for summer crops mapping than a single band or index input. |
| first_indexed | 2024-04-11T00:59:38Z |
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| id | doaj.art-48bea32c2d944bd3928d862839b9d4da |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-04-11T00:59:38Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Environmental Science |
| spelling | doaj.art-48bea32c2d944bd3928d862839b9d4da2023-01-04T17:22:06ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2023-01-011010.3389/fenvs.2022.10890071089007A new method for classifying maize by combining the phenological information of multiple satellite-based spectral bandsQiongyan Peng0Ruoque Shen1Jie Dong2Wei Han3Jianxi Huang4Tao Ye5Wenzhi Zhao6Wenping Yuan7Southern Marine Science and Engineering Guangdong Laboratory, School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, Guangdong, ChinaSouthern Marine Science and Engineering Guangdong Laboratory, School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, Guangdong, ChinaCollege of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou, Zhejiang, ChinaShandong General Station of Agricultural Technology Extension, Jinan, Shandong, ChinaCollege of Land Science and Technology, China Agricultural University, Beijing, ChinaFaculty of Geographical Science, Beijing Normal University, Beijing, ChinaFaculty of Geographical Science, Beijing Normal University, Beijing, ChinaSouthern Marine Science and Engineering Guangdong Laboratory, School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai, Guangdong, ChinaIntroduction: Using satellite data to identify the planting area of summer crops is difficult because of their similar phenological characteristics.Methods: This study developed a new method for differentiating maize from other summer crops based on the revised time-weighted dynamic time warping (TWDTW) method, a phenology-based classification method, by combining the phenological information of multiple spectral bands and indexes instead of one single index. First, we compared the phenological characteristics of four main summer crops in Henan Province of China in terms of multiple spectral bands and indexes. The key phenological periods of each band and index were determined by comparing the identification accuracy based on the county-level statistical areas of maize. Second, we improved the TWDTW distance calculation for multiple bands and indexes by summing the rank maps of a single band or index. Third, we evaluated the performance of a multi-band and multi-period TWDTW method using Sentinel-2 time series of all spectral bands and some synthetic indexes for maize classification in Henan Province.Results and Discussion: The results showed that the combination of red edge (740.2 nm) and short-wave infrared (2202.4 nm) outperformed all others and its overall accuracy of maize planting area was about 91.77% based on 2431 field samples. At the county level, the planting area of maize matched the statistical area closely. The results of this study demonstrate that the revised TWDTW makes effective use of crop phenological information and improves the extraction accuracy of summer crops’ planting areas over a large scale. Additionally, multiple band combinations are more effective for summer crops mapping than a single band or index input.https://www.frontiersin.org/articles/10.3389/fenvs.2022.1089007/fullmaizetime-weighted dynamic time warpingsummer cropspectral bandseasonal change |
| spellingShingle | Qiongyan Peng Ruoque Shen Jie Dong Wei Han Jianxi Huang Tao Ye Wenzhi Zhao Wenping Yuan A new method for classifying maize by combining the phenological information of multiple satellite-based spectral bands Frontiers in Environmental Science maize time-weighted dynamic time warping summer crop spectral band seasonal change |
| title | A new method for classifying maize by combining the phenological information of multiple satellite-based spectral bands |
| title_full | A new method for classifying maize by combining the phenological information of multiple satellite-based spectral bands |
| title_fullStr | A new method for classifying maize by combining the phenological information of multiple satellite-based spectral bands |
| title_full_unstemmed | A new method for classifying maize by combining the phenological information of multiple satellite-based spectral bands |
| title_short | A new method for classifying maize by combining the phenological information of multiple satellite-based spectral bands |
| title_sort | new method for classifying maize by combining the phenological information of multiple satellite based spectral bands |
| topic | maize time-weighted dynamic time warping summer crop spectral band seasonal change |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2022.1089007/full |
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