Monitoring paddy rice cultivation adjustments in Northeast China through time series remote sensing and deep learning
文献类型：期刊论文
| 作者 | Wang, Shihao3,4; Huang, Chong6; Huang, Lingxiao6; Xu, Xinliang6; Shi, Huading3; Gu, Qingbao4; Xue, Qiang1; Liu, Shiai5; Zhang, Chenchen2 |
| 刊名 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
 |
| 出版日期 | 2025-08-01 |
| 卷号 | 142页码:104739 |
| 关键词 | Paddy rice Agricultural policy Deep learning Deep neural networks |
| ISSN号 | 1569-8432 |
| DOI | 10.1016/j.jag.2025.104739 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Northeast China is one of China's most important rice production bases, contributing about one-fifth of the country's rice production. In recent years, several agricultural policies have been implemented in Northeast China to adjust crop structures, driven by economic and ecological benefits. Timely monitoring of the changed pattern of rice cultivation is a prerequisite for policy assessment. Current paddy rice mapping methods are experiencing uncertainties due to confusion with wetlands and are highly parameter-dependent. To these, in this study, we developed a paddy rice mapping framework that integrates automatically generated training samples, time series features from key cultivation stages, and a deep learning model to improve paddy rice identification accuracy in Northeast China, which is a typical rice-wetland coexisting area. We produced 10 m paddy rice maps for 2019-2023 in Northeast China and examined their changes under agricultural policy implementation. The resultant paddy rice maps have high accuracies, with overall accuracies >0.97, producer's accuracies >0.94, user's accuracies >0.93, and F1 scores of >0.95, respectively. Our proposed mapping method effectively identified small patches of paddy rice and reduced confusion with wetlands. Paddy rice areas in Northeast China estimated in this study continued to decrease annually from 71.1 x 10(3) km(2 )in 2019 to 56.4 x 10(3) km(2) in 2023. Hot spots of rice conversion to other crops were found in the Sanjiang Plain, mainly due to the Soybean Revitalization Plan. The rice cultivation expansion was mainly found in the Songnen Plain, resulting from policies on Rehabilitation and Utilization of Saline Soils. Observed changes in paddy rice plantation emphasize the importance and necessity of timely and continuous crop cultivation monitoring under the influence of agricultural policy adjustment. |
| URL标识 | 查看原文 |
| WOS关键词 | GROSS PRIMARY PRODUCTION ; MODIS ; PATTERNS ; AGRICULTURE ; NETWORK ; IMAGES ; ASIA |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001549915700001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/215626]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Huang, Chong; Zhang, Chenchen |
| 作者单位 | 1.Gansu Prov Geol Disaster Control Ctr, Lanzhou 730000, Peoples R China; 2.Univ Oklahoma, Ctr Earth Observat & Modeling, Sch Biol Sci, Norman, OK 73019 USA 3.Minist Ecol & Environm, Tech Ctr Soil Agr & Rural Ecol & Environm, Beijing 100012, Peoples R China; 4.Chinese Res Inst Environm Sci, State Key Lab Environm Criteria & Risk Assessment, Beijing 100012, Peoples R China; 5.Dongying Agr & Rural Bur, Dongying 257091, Peoples R China; 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Wang, Shihao,Huang, Chong,Huang, Lingxiao,et al. Monitoring paddy rice cultivation adjustments in Northeast China through time series remote sensing and deep learning[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2025,142:104739. |
| APA | Wang, Shihao.,Huang, Chong.,Huang, Lingxiao.,Xu, Xinliang.,Shi, Huading.,...&Zhang, Chenchen.(2025).Monitoring paddy rice cultivation adjustments in Northeast China through time series remote sensing and deep learning.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,142,104739. |
| MLA | Wang, Shihao,et al."Monitoring paddy rice cultivation adjustments in Northeast China through time series remote sensing and deep learning".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 142(2025):104739. |
入库方式： OAI收割
来源：地理科学与资源研究所
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