自然资源遥感2025，Vol.37Issue(2)：56-65,10.DOI:10.6046/zrzyyg.2023358
基于HSV和纹理特征的裸地分层精细提取
Hierarchical fine-scale information extraction of bare land based on hue-saturation-value and texture features
摘要
Abstract
Extracting information about bare land is crucial for territorial planning,environmental protection,and sustainable development.However,current information extraction methods for bare land struggle to balance the extraction efficiency and accuracy in large-scale and multitemporal applications.This study constructed normalized difference indices based on the analysis of the hue-saturation-value(HSV)features.By combining texture features and vegetation index,this study proposed a simple,efficient hierarchical fine-scale information extraction method for bare land.This proposed method was applied to the urban area of Qufu City,Shandong Province,China.First,with three GF-1 satellite images as the data source,the red,green,and blue bands from the images were converted to the HSV color space.Based on the differences in H,S,and V components between bare land and other land types,the normalized difference SH and SV indices were constructed for preliminary hierarchical information extraction of bare land.Second,texture features were introduced to low-rise building areas and bare land,where the differences in H,S,and V components are nonsignificant.Different texture features were comparatively analyzed for further information extraction of bare land.Third,the normalized difference vegetation indices were used to achieve the final information extraction of bare land,followed by post-processing of the results.The results of this study demonstrate that the constructed normalized difference indices,combined with homogeneous texture features,showed the optimal extraction performance,with an overall accuracy of above 93％and a Kappa coefficient of above 0.84,outperforming other classification methods.Therefore,the proposed method proves effective in extracting information about bare land,serving as a novel approach for bare land information ex-traction.关键词
高分一号/裸地分层精细提取/HSV/纹理特征Key words
GF-1/hierarchical fine-scale information extraction of bare land/HSV/texture feature分类
信息技术与安全科学引用本文复制引用
卫虹宇,姚文举,孙建,孙嵩,张焕雪..基于HSV和纹理特征的裸地分层精细提取[J].自然资源遥感,2025,37(2):56-65,10.基金项目
山东省鲁南地质工程勘察院(山东省地质矿产勘查开发局第二地质大队)2022年开放基金项目"基于深度学习的高分遥感影像裸地及防尘网自动识别研究"(编号:LNY202205)资助. （山东省地质矿产勘查开发局第二地质大队）
