| 刊名 | Agricultural Biotechnology |
| 作者 | Qi’ang HU1, Aichuan LI1*, Xinbing WANG3, Francesco Marinello2, Zhan SHI2 |
| 作者单位 | 1.College of Information and Electrical Engineering, Heilongjiang Bayi Agricultural University, Daqing 163319, China; 2.College of Agronomy, University of Padova, Padova 163319, China; Tangyuan Agricultural Technology Extension Center, Tangyuan 154700, China |
| DOI | DOI:10.19759/j.cnki.2164-4993.2026.01.018 |
| 年份 | 2026 |
| 刊期 | 1 |
| 页码 | 76-81 |
| 关键词 | Satellite remote sensing; Rice cultivation; Spatiotemporal variability; Monitoring; Research review |
| 摘要 | As a vital food crop, rice is an important part of global food crops. Studying the spatiotemporal changes in rice cultivation facilitates early prediction of production risks and provides support for agricultural policy decisions related to rice. With the increasing application of satellite remote sensing technology in crop monitoring, remote sensing for rice cultivation has emerged as a novel approach, offering new perspectives for monitoring rice planting. This paper briefly outlined the current research and development status of satellite remote sensing for monitoring rice cultivation both at home and abroad. Foreign scholars have made innovations in data sources and methodologies for satellite remote sensing monitoring, and utilized multi-source satellite information and machine learning algorithms to enhance the accuracy of rice planting monitoring. Scholars in China have achieved significant results in the study of satellite remote sensing for monitoring rice cultivation. Their research and application in monitoring rice planting areas provide valuable references for agricultural production management. However, satellite remote sensing monitoring of rice still faces challenges such as low spatiotemporal resolution and difficulties related to cloud cover and data fusion, which require further in-depth investigation. Additionally, there are shortcomings in the accuracy of remote sensing monitoring for fragmented farmland plots and smallholder farming. To address these issues, future efforts should focus on developing multi-source heterogeneous data fusion analysis technologies and researching monitoring systems. These advancements are expected to enable high-precision large-scale acquisition of rice planting information, laying a foundation for future smart agriculture. |
