无线电工程2025，Vol.55Issue(6)：1244-1255,12.DOI:10.3969/j.issn.1003-3106.2025.06.012
基于干扰地物排除的时序特征优选与水稻精准制图
Temporal Feature Optimization and Accurate Mapping of Rice Based on Interference Elimination
摘要
Abstract
Rice planting information extraction is of great significance for ensuring food security.Previous research mainly focused on multi-temporal image feature selection for rice mapping based on the features of different growth stages of rice.By taking Shouxian County in Anhui Province as the study area,a feature selection strategy from the perspective of excluding interfering objects is proposed.Based on the spectral differences between rice and interfering objects at different phenological stages,temporal features that can effectively distinguish rice from interfering objects are extracted from multi-temporal Sentinel-2 images.In addition,the Jeffries-Matusita(J-M)distance,Random Forest(RF)-recursive elimination and Pearson correlation analysis are used to screen out the optimal index feature set.Three classification algorithms,RF,Support Vector Machine(SVM)and Light Gradient Boosting Machine(LGBM),are used for rice mapping.The accuracy of the three classification methods is evaluated,and the optimal classification results are compared with other rice mapping products and rice mapping method extraction results.The experimental results show that based on the selected optimal index feature set,the Overall Accuracy(OA)of rice mapping of the three classification algorithms exceeds 0.96,and the RF classification algorithm has the highest OA,User Accuracy(UA),and area accuracy.Compared with the extraction results of other rice mapping products and rice mapping methods,the proposed method can effectively reduce the commission and omission errors in rice classification while achieving the highest area accuracy,providing a novel solution for precise rice mapping based on multi-temporal images.关键词
水稻制图/特征优选/多时相图像/J-M距离/皮尔森相关性/随机森林/递归消除Key words
rice mapping/feature optimization/multi-temporal images/J-M distance/Pearson correlation/RF/recursive elimination分类
信息技术与安全科学引用本文复制引用
赵萍,周俊,张树衡,吴松,常杰,申奥..基于干扰地物排除的时序特征优选与水稻精准制图[J].无线电工程,2025,55(6):1244-1255,12.基金项目
安徽省自然资源厅公益性地质调查项目(2021-g-2-7) Public Welfare Geological Survey Project of Anhui Provincial Department of Natural Resources(2021-g-2-7) （2021-g-2-7）
