人民长江2025，Vol.56Issue(7)：50-55,6.DOI:10.16232/j.cnki.1001-4179.2025.07.007
基于特征优选的鄱阳湖南矶湿地土地利用分类
Land use classification of Poyang Lake Nanji wetland based on feature optimization
摘要
Abstract
To address the issues of easy confusion and low classification accuracy in wetland land use information extraction,this study proposed a wetland land use classification model based on the fusion of genetic algorithm and support vector machine preprocessed by random forest algorithm(RF-GA-SVM).Based on the data of Landsat 8 remote sensing imagery(bands 1～7),land use information extraction was conducted in Poyang Lake Nanji wetland.The results extracted by the RF-GA-SVM model were compared with the results by the fusion models based on traditional support vector machine(SVM),particle swarm optimization-optimized SVM(PSO-SVM),and gray wolf algorithm optimization-optimized SVM(GWO-SVM).The results showed that the RF-GA-SVM model achieved an overall accuracy of 99.2%in land use classification for the Nanji wetland of Poyang Lake.The feature optimization using the random forest algorithm effectively reduced feature redundancy,and the GA-SVM model classification further enhanced accuracy.Compared to other methods,the proposed model achieved higher classifica-tion accuracy while improving computational efficiency,enabling effective extraction of wetland land use information.The research findings can provide a reference for wetland landform identification and classification.关键词
土地利用信息提取/遥感影像/特征优选/机器学习/随机森林/支持向量机/南矶湿地/鄱阳湖Key words
land use information extraction/remote sensing imagery/feature optimization/machine learning/random forest/support vector machine/Nanji wetland/Poyang Lake分类
天文与地球科学引用本文复制引用
郭松,杨东伟,尹晓星,万程辉,唐旭伟..基于特征优选的鄱阳湖南矶湿地土地利用分类[J].人民长江,2025,56(7):50-55,6.基金项目
江西省自然科学基金项目(2024BAB25199) （2024BAB25199）
江西省教育厅科技项目青年基金项目(GJJ2201512) （GJJ2201512）
