Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and Future
Northeast China plays a crucial role as a major grain-producing region, and attention to its land use and land cover changes (LUCC), especially farmland changes, are crucial to ensure food security and promote sustainable development. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS...
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MDPI AG
2024-10-01
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| Series: | Agriculture |
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| author | Xuhua Hu Yang Xu Peng Huang Dan Yuan Changhong Song Yingtao Wang Yuanlai Cui Yufeng Luo |
| author_facet | Xuhua Hu Yang Xu Peng Huang Dan Yuan Changhong Song Yingtao Wang Yuanlai Cui Yufeng Luo |
| author_sort | Xuhua Hu |
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| description | Northeast China plays a crucial role as a major grain-producing region, and attention to its land use and land cover changes (LUCC), especially farmland changes, are crucial to ensure food security and promote sustainable development. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data and a decision tree model, land types, especially those of paddy fields in Northeast China from 2000 to 2020, were extracted, and the spatiotemporal changes in paddy fields and their drivers were analyzed. The development trends of paddy fields under different future scenarios were explored alongside the Coupled Model Intercomparison Project Phase 6 (CMIP6) data. The findings revealed that the kappa coefficients of land use classification from 2000 to 2020 reached 0.761–0.825, with an overall accuracy of 80.5–87.3%. The proposed land classification method can be used for long-term paddy field monitoring in Northeast China. The LUCC in Northeast China is dominated by the expansion of paddy fields. The centroids of paddy fields gradually shifted toward the northeast by a distance of 292 km, with climate warming being the main reason for the shift. Under various climate scenarios, the temperature in Northeast China and its surrounding regions is projected to rise. Each scenario is anticipated to meet the temperature conditions necessary for the northeastward expansion of paddy fields. This study provides support for ensuring sustainable agricultural development in Northeast China. |
| format | Article |
| id | doaj-art-5fb1055de61e4583ba795d38ccb11bbc |
| institution | OA Journals |
| issn | 2077-0472 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
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| series | Agriculture |
| spelling | doaj-art-5fb1055de61e4583ba795d38ccb11bbc2025-08-20T02:26:50ZengMDPI AGAgriculture2077-04722024-10-011411195610.3390/agriculture14111956Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and FutureXuhua Hu0Yang Xu1Peng Huang2Dan Yuan3Changhong Song4Yingtao Wang5Yuanlai Cui6Yufeng Luo7State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, ChinaInner Mongolia Water Conservancy Research Institute, Hohhot 010051, ChinaState Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, ChinaHeilongjiang Water Conservancy Investment Group Co., Ltd., Harbin 150090, ChinaHeilongjiang Provincial Water Conservancy and Hydroelectric Power Investigation, Design and Research Institute, Harbin 150080, ChinaState Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, ChinaState Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan 430072, ChinaNortheast China plays a crucial role as a major grain-producing region, and attention to its land use and land cover changes (LUCC), especially farmland changes, are crucial to ensure food security and promote sustainable development. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data and a decision tree model, land types, especially those of paddy fields in Northeast China from 2000 to 2020, were extracted, and the spatiotemporal changes in paddy fields and their drivers were analyzed. The development trends of paddy fields under different future scenarios were explored alongside the Coupled Model Intercomparison Project Phase 6 (CMIP6) data. The findings revealed that the kappa coefficients of land use classification from 2000 to 2020 reached 0.761–0.825, with an overall accuracy of 80.5–87.3%. The proposed land classification method can be used for long-term paddy field monitoring in Northeast China. The LUCC in Northeast China is dominated by the expansion of paddy fields. The centroids of paddy fields gradually shifted toward the northeast by a distance of 292 km, with climate warming being the main reason for the shift. Under various climate scenarios, the temperature in Northeast China and its surrounding regions is projected to rise. Each scenario is anticipated to meet the temperature conditions necessary for the northeastward expansion of paddy fields. This study provides support for ensuring sustainable agricultural development in Northeast China.https://www.mdpi.com/2077-0472/14/11/1956paddy field expansionremote sensingland use and land cover changeclimate warming |
| spellingShingle | Xuhua Hu Yang Xu Peng Huang Dan Yuan Changhong Song Yingtao Wang Yuanlai Cui Yufeng Luo Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and Future Agriculture paddy field expansion remote sensing land use and land cover change climate warming |
| title | Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and Future |
| title_full | Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and Future |
| title_fullStr | Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and Future |
| title_full_unstemmed | Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and Future |
| title_short | Identifying Changes and Their Drivers in Paddy Fields of Northeast China: Past and Future |
| title_sort | identifying changes and their drivers in paddy fields of northeast china past and future |
| topic | paddy field expansion remote sensing land use and land cover change climate warming |
| url | https://www.mdpi.com/2077-0472/14/11/1956 |
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