北京测绘2026，Vol.40Issue(8)：1076-1081,6.DOI:10.19580/j.cnki.1007-3000.2026010084
基于监督分类和DEM的山脚线提取方法
A method for foothill line extraction based on supervised classification and digital elevation model
摘要
Abstract
To address the issues of high subjectivity,poor adaptability,and low efficiency in existing foothill line extraction methods,this paper proposed a foothill line extraction approach based on supervised classification and digital elevation model(DEM).The proposed method integrated three terrain factors—elevation,slope,and profile curvature—to construct a multi-channel terrain feature image.Three supervised image classification methods,namely the minimum distance method,maxi-mum likelihood method,and neural network method,were applied to identify and distinguish mountain and non-mountain pixels in the feature image,thereby extracting the boundaries of the foothill line.The results demonstrate that the image-based supervised classification approach can effectively achieve foothill line extraction.Among the three supervised classifi-cation methods,the neural network method achieves the highest extraction accuracy,significantly outperforming both the minimum distance method and the maximum likelihood method.关键词
山脚线/地形因子/波段合成/监督分类/数字高程模型(DEM)Key words
foothill line/terrain factor/band synthesis/supervised classification/digital elevation model(DEM)分类
天文与地球科学引用本文复制引用
罗晔,金晓彤,蒋汪洋,王久懿..基于监督分类和DEM的山脚线提取方法[J].北京测绘,2026,40(8):1076-1081,6.基金项目
中国地质调查局地质调查项目(DD20251300222) （DD20251300222）
东北地质科技创新中心区创基金(QCJJ2023-33). （QCJJ2023-33）
