文献类型：期刊文献

中文题名：多对象特征融合的海南特色经济作物分类方法

英文题名：Classification method for hainan’s distinctive economic crop based on multi-object feature fusion

作者：蒙方鑫[1,2] 覃先林[1,2] 黄水生[1,2] 俞琳锋[1,2] 胡心雨[1,2] 蒋凤[1,2]

第一作者：蒙方鑫

机构：[1]中国林业科学研究院资源信息研究所,北京100091;[2]国家林业和草原局林业遥感与信息技术重点实验室,北京100091

年份：2025

卷号：50

期号：7

起止页码：171-183

中文期刊名：测绘科学

外文期刊名：Science of Surveying and Mapping

收录：;北大核心:【北大核心2023】；

基金：国家重点研发计划项目(2022YFD1400400)。

语种：中文

中文关键词：GF-2;随机森林;特征选择;面向对象

外文关键词：GF-2;random forest;feature selection;object-oriented

分类号：P237

摘要：针对槟榔、椰子和胡椒等海南特色经济作物结构复杂以及碎片化分布问题,利用随机森林算法,探究基于GF-2数据的特色经济作物精细分类框架。采用GF-2融合影像,通过影像分割、特征分析与筛选处理,分别采用随机森林、支持向量机和K最近邻算法,对多对象特征融合数据进行分类,并建立混淆矩阵对结果进行精度评价:①当分割尺度为138、形状为0.3、紧致度为0.5时,各分割对象间能够实现较高的区分度;②基于多对象特征融合后的随机森林分类结果,总体精度和Kappa系数分别可达84%和0.81;③随机森林相较于支持向量机和K最近邻算法,总体精度分别提高了8%和12%,Kappa系数分别提升了0.1和0.12。研究结果为海南地区特色经济作物遥感精细分类与槟榔黄化病研究提供了技术支持。
To address the complex structure and fragmented distribution of specialty economic crops such as betel nut,coconut,and pepper in Hainan,this study explored a detailed classification framework based on GF-2satellite data using the Random Forest algorithm.GF-2fused imagery underwent image segmentation,feature analysis,and feature selection.Classification was conducted using the Random Forest,Support Vector Machine,and K-Nearest Neighbor algorithms on multi-object feature-fused data.A confusion matrix was used to evaluate classification accuracy.The segmented objects exhibited high differentiation when the segmentation scale was set to 138,with a shape parameter of 0.3and a compactness parameter of 0.5.The Random Forest classification results based on multi-object featurefused data achieved an overall accuracy of 84%and a Kappa coefficient of 0.81.Comparing with the Support Vector Machine and K-Nearest Neighbor algorithms,the overall accuracy improved by 8%and 12%,and increased the Kappa coefficient by 0.1and 0.12by using Random Forest,respectively.The results provide technical support for the classification of specialty economic crops using remote sensing and contribute to the scientific management of agriculture in Hainan.