High Resolution Distribution Dataset of Double-Season Paddy Rice in China
Although China is the largest producer of rice, accounting for about 25% of global production, there are no high-resolution maps of paddy rice covering the entire country. Using time-weighted dynamic time warping (TWDTW), this study developed a pixel- and phenology-based method to identify planting...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/22/4609 |
| _version_ | 1797508597141209088 |
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| author | Baihong Pan Yi Zheng Ruoque Shen Tao Ye Wenzhi Zhao Jie Dong Hanqing Ma Wenping Yuan |
| author_facet | Baihong Pan Yi Zheng Ruoque Shen Tao Ye Wenzhi Zhao Jie Dong Hanqing Ma Wenping Yuan |
| author_sort | Baihong Pan |
| collection | DOAJ |
| description | Although China is the largest producer of rice, accounting for about 25% of global production, there are no high-resolution maps of paddy rice covering the entire country. Using time-weighted dynamic time warping (TWDTW), this study developed a pixel- and phenology-based method to identify planting areas of double-season paddy rice in China, by comparing temporal variations of synthetic aperture radar (SAR) signals of unknown pixels to those of known double-season paddy rice fields. We conducted a comprehensive evaluation of the method’s performance at pixel and regional scales. Based on 145,210 field surveyed samples from 2018 to 2020, the producer’s and user’s accuracy are 88.49% and 87.02%, respectively. Compared to county-level statistical data from 2016 to 2019, the relative mean absolute errors are 34.11%. This study produced distribution maps of double-season rice at 10 m spatial resolution from 2016 to 2020 over nine provinces in South China, which account for more than 99% of the planting areas of double-season paddy rice of China. The maps are expected to contribute to timely monitoring and evaluating rice growth and yield. |
| first_indexed | 2024-03-10T05:06:12Z |
| format | Article |
| id | doaj.art-8febfd005a4c4248a2b75dfab46a8216 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T05:06:12Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-8febfd005a4c4248a2b75dfab46a82162023-11-23T01:20:26ZengMDPI AGRemote Sensing2072-42922021-11-011322460910.3390/rs13224609High Resolution Distribution Dataset of Double-Season Paddy Rice in ChinaBaihong Pan0Yi Zheng1Ruoque Shen2Tao Ye3Wenzhi Zhao4Jie Dong5Hanqing Ma6Wenping Yuan7Southern Marine Science and Engineering Guangdong Laboratory, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, ChinaSouthern Marine Science and Engineering Guangdong Laboratory, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, ChinaSouthern Marine Science and Engineering Guangdong Laboratory, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, ChinaFaculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaFaculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaCollege of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, ChinaNorthwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 519082, ChinaSouthern Marine Science and Engineering Guangdong Laboratory, School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, ChinaAlthough China is the largest producer of rice, accounting for about 25% of global production, there are no high-resolution maps of paddy rice covering the entire country. Using time-weighted dynamic time warping (TWDTW), this study developed a pixel- and phenology-based method to identify planting areas of double-season paddy rice in China, by comparing temporal variations of synthetic aperture radar (SAR) signals of unknown pixels to those of known double-season paddy rice fields. We conducted a comprehensive evaluation of the method’s performance at pixel and regional scales. Based on 145,210 field surveyed samples from 2018 to 2020, the producer’s and user’s accuracy are 88.49% and 87.02%, respectively. Compared to county-level statistical data from 2016 to 2019, the relative mean absolute errors are 34.11%. This study produced distribution maps of double-season rice at 10 m spatial resolution from 2016 to 2020 over nine provinces in South China, which account for more than 99% of the planting areas of double-season paddy rice of China. The maps are expected to contribute to timely monitoring and evaluating rice growth and yield.https://www.mdpi.com/2072-4292/13/22/4609early ricelate ricedouble-season ricetime-weighted dynamic time warpingsynthetic aperture radarplanting area |
| spellingShingle | Baihong Pan Yi Zheng Ruoque Shen Tao Ye Wenzhi Zhao Jie Dong Hanqing Ma Wenping Yuan High Resolution Distribution Dataset of Double-Season Paddy Rice in China Remote Sensing early rice late rice double-season rice time-weighted dynamic time warping synthetic aperture radar planting area |
| title | High Resolution Distribution Dataset of Double-Season Paddy Rice in China |
| title_full | High Resolution Distribution Dataset of Double-Season Paddy Rice in China |
| title_fullStr | High Resolution Distribution Dataset of Double-Season Paddy Rice in China |
| title_full_unstemmed | High Resolution Distribution Dataset of Double-Season Paddy Rice in China |
| title_short | High Resolution Distribution Dataset of Double-Season Paddy Rice in China |
| title_sort | high resolution distribution dataset of double season paddy rice in china |
| topic | early rice late rice double-season rice time-weighted dynamic time warping synthetic aperture radar planting area |
| url | https://www.mdpi.com/2072-4292/13/22/4609 |
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