世界核地质科学2025，Vol.42Issue(2)：385-399,15.
面向矿物填图的典型高光谱图像分类方法对比研究
Study on mineral identification and classification based on airborne hyperspectral imagery
摘要
Abstract
Hyperspectral remote sensing technology has been widely used in many fields due to its high spectral resolution and rich spectral information.Object classification is one of the key techniques to fully use the hyperspectral data.Based on the investigation and summary of the research status of hyperspectral image classification technology,experiments were conducted in the mining area north of Jinchang,Gansu province.A comparative analysis was mainly carried out from two aspects:supervised classification and unsupervised classification.Taking the spectral Angle method as an example,the key factors affecting the classification performance of different methods were deeply discussed.The results show that the accuracy of supervised classification method is better than that of unsupervised classification for the areas with insufficient spatial characteristics like the experimental area,in which the Maximum Likelihood Classification is the best,and it also proves that unsupervised classification is not suitable for mineral classification in the similar areas.关键词
矿物填图/高光谱遥感/监督分类/非监督分类Key words
mineral mapping/hyperspectral remote sensing/supervision classification/unsupervised classification分类
地质学引用本文复制引用
赵冀唯,伊丕源..面向矿物填图的典型高光谱图像分类方法对比研究[J].世界核地质科学,2025,42(2):385-399,15.基金项目
多模态卫星遥感数据接引设计及典型应用关键技术研究(编号:WDZC_2023_HDYY_101)资助 Supported by Multi-modal satellite remote sensing data access design and typical application key technology research(WDZC_2023_HDYY_101) （编号:WDZC_2023_HDYY_101）
