A 30 m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel Images
As the second largest producer of maize, China contributes 23% of global maize production and plays an important role in guaranteeing maize markets stability. In spite of its importance, there is no 30 m spatial resolution distribution map of maize for all of China. This study used a time-weighted d...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2022-01-01
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| Series: | Journal of Remote Sensing |
| Online Access: | http://dx.doi.org/10.34133/2022/9846712 |
| _version_ | 1798001701293129728 |
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| author | Ruoque Shen Jie Dong Wenping Yuan Wei Han Tao Ye Wenzhi Zhao |
| author_facet | Ruoque Shen Jie Dong Wenping Yuan Wei Han Tao Ye Wenzhi Zhao |
| author_sort | Ruoque Shen |
| collection | DOAJ |
| description | As the second largest producer of maize, China contributes 23% of global maize production and plays an important role in guaranteeing maize markets stability. In spite of its importance, there is no 30 m spatial resolution distribution map of maize for all of China. This study used a time-weighted dynamic time warping method to identify planting areas of maize by comparing the similarity of time series of a satellite-based vegetation index at each pixel with a standard time series derived from known maize fields and mapped maize distribution from 2016 to 2020 over 22 provinces accounting for more than 99% of the maize planting area in China. Based on 18800 field-surveyed pixels at 30-meter spatial resolution, the distribution map yields 76.15% and 81.59% of producer’s and user’s accuracies averaged over the entire investigated provinces, respectively. Municipality- and county-level census data also show a good performance in reproducing the spatial distribution of maize. This study provides an approach to mapping maize over large areas based on a small volume of field survey data. |
| first_indexed | 2024-04-11T11:40:28Z |
| format | Article |
| id | doaj.art-d57b78adea7d45d08de94ee637645847 |
| institution | Directory Open Access Journal |
| issn | 2694-1589 |
| language | English |
| last_indexed | 2024-04-11T11:40:28Z |
| publishDate | 2022-01-01 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | Article |
| series | Journal of Remote Sensing |
| spelling | doaj.art-d57b78adea7d45d08de94ee6376458472022-12-22T04:25:50ZengAmerican Association for the Advancement of Science (AAAS)Journal of Remote Sensing2694-15892022-01-01202210.34133/2022/9846712A 30 m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel ImagesRuoque Shen0Jie Dong1Wenping Yuan2Wei Han3Tao Ye4Wenzhi Zhao5School of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai, 519082 Guangdong, ChinaCollege of Geomatics & Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou, 310018 Zhejiang, ChinaSchool of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai, 519082 Guangdong, ChinaAgro-Technical Station, Shandong Province, Shandong, ChinaKey Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, ChinaKey Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, ChinaAs the second largest producer of maize, China contributes 23% of global maize production and plays an important role in guaranteeing maize markets stability. In spite of its importance, there is no 30 m spatial resolution distribution map of maize for all of China. This study used a time-weighted dynamic time warping method to identify planting areas of maize by comparing the similarity of time series of a satellite-based vegetation index at each pixel with a standard time series derived from known maize fields and mapped maize distribution from 2016 to 2020 over 22 provinces accounting for more than 99% of the maize planting area in China. Based on 18800 field-surveyed pixels at 30-meter spatial resolution, the distribution map yields 76.15% and 81.59% of producer’s and user’s accuracies averaged over the entire investigated provinces, respectively. Municipality- and county-level census data also show a good performance in reproducing the spatial distribution of maize. This study provides an approach to mapping maize over large areas based on a small volume of field survey data.http://dx.doi.org/10.34133/2022/9846712 |
| spellingShingle | Ruoque Shen Jie Dong Wenping Yuan Wei Han Tao Ye Wenzhi Zhao A 30 m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel Images Journal of Remote Sensing |
| title | A 30 m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel Images |
| title_full | A 30 m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel Images |
| title_fullStr | A 30 m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel Images |
| title_full_unstemmed | A 30 m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel Images |
| title_short | A 30 m Resolution Distribution Map of Maize for China Based on Landsat and Sentinel Images |
| title_sort | 30 m resolution distribution map of maize for china based on landsat and sentinel images |
| url | http://dx.doi.org/10.34133/2022/9846712 |
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