地理空间信息2025，Vol.23Issue(4)：87-90,113,5.DOI:10.3969/j.issn.1672-4623.2025.04.019
利用监督学习的水稻生育期识别技术研究
Research on Rice Growth Stage Identification Technology Based on Supervised Learning
摘要
Abstract
Utilizing remote sensing technology to identify rice growth stage can effectively enhance the precision of agricultural field manage-ment and provide scientific guidance for farming activities.We integrated Sentinel-2 satellite images,rice growth stage observation data,and land-use information to construct rice growth stage samples with spectral,index,and texture features,employed random forest model for feature selection,and utilized supervised learning algorithms including K-nearest neighbors,support vector machines and decision trees to construct iden-tification models for six key rice growth stages,such as transplanting,tillering,booting,heading,filling,and maturing.Results indicate that the random forest algorithm is employed to evaluate the importance of features,where index features reflecting vegetation growth status are found to be most representative.The support vector machine model demonstrates notable advantages in rice growth stage identification,achieving an over-all accuracy of 84.56％and Kappa coefficient of 0.813.关键词
水稻/遥感/监督学习/生育期识别/Sentinel-2Key words
rice/remote sensing/supervised learning/growth stage identification/Sentinel-2分类
天文与地球科学引用本文复制引用
戴晨,吴昕悦,王秀琴,曹晨,乔娜,张芯瑜..利用监督学习的水稻生育期识别技术研究[J].地理空间信息,2025,23(4):87-90,113,5.基金项目
江苏省气象局青年基金资助项目(KQ202328) （KQ202328）
镇江市重点研发计划资助项目(SH2022019). （SH2022019）
