首都师范大学学报（自然科学版）2026，Vol.47Issue(2)：1-7,7.DOI:10.19789/j.1004-9398.2026.02.001
基于高清遥感影像的城区常绿植被提取方法
Method for extracting evergreen vegetation in urban areas based on high-resolution remote sensing images
摘要
Abstract
The extraction of evergreen vegetation in urban areas holds significant importance for environmental monitoring and sustainable urban development.To address the limitations of existing visible light vegetation indices in environmental adaptability and the critical role of sample annotation in vegetation segmentation,this paper proposes a sample optimization method that integrates color theory and EfficientSAM,aiming to enhance the accuracy of evergreen vegetation extraction in urban areas.This method utilizes high-resolution remote sensing images from the visible light spectrum,combining the color sensitivity of visible light vegetation indices with the prompting capabilities of EfficientSAM to optimize samples.The optimized results are then used to train semantic segmentation models,effectively achieving precise extraction of evergreen vegetation.Experimental results demonstrate that the proposed method achieves improvements of 83.83%,92.23%,89.72%,and 90.96%in mI,mP,mR,and mF metrics,respectively,compared to traditional manually annotated sample training results.Furthermore,the method effectively distinguishes vegetation in water bodies from evergreen vegetation,providing a valuable reference for the accurate extraction of evergreen vegetation using visible-band imagery.关键词
城区常绿植被提取/EfficientSAM/颜色理论/深度学习Key words
urban evergreen vegetation extraction/efficientSAM/color theory/deep learning分类
天文与地球科学引用本文复制引用
李照芊,王艳慧..基于高清遥感影像的城区常绿植被提取方法[J].首都师范大学学报（自然科学版）,2026,47(2):1-7,7.基金项目
国家自然科学基金项目(42171224) （42171224）
