长沙理工大学学报（自然科学版）2025，Vol.22Issue(1)：40-48,61,10.DOI:10.19951/j.cnki.1672-9331.20231206001
基于误差传播定律的地形复杂度误差估计
Error estimation of terrain complexity based on error propagation law
摘要
Abstract
[Purposes]This paper aims to address the issue that the existing terrain complexity error evaluation methods are subjective and lack error analytic formulas.[Methods]The mean square error expressions for local relief,local standard deviation,local rugosity,and local total curvature were derived by using error propagation law.The error estimation model for compound terrain complexity index(CTCI),namely CEEM was constructed by error transfer of compound terrain factors.The effectiveness of CEEM was verified by the simulated digital elevation model(DEM),and the generalization experiment of CEEM was carried out by using the entity DEM of three different landform regions.[Findings]Under the influence of different noises,the maximum values of CEEM's mean error,mean square error,residual error,and mean absolute percentage error are-2.1×10-3,7.99×10-6,8.4×10-3,and 22.8%,respectively,with an absolute coefficient of above 0.961.The overall error of CEEM is small.There are differences in the extraction error of terrain complexity of different landform types,and the experimental statistical results show that the error size in descending order is high mountain,middle mountain,and hill.[Conclusions]The extraction error of terrain complexity can be quantitatively described by CEEM,which provides a reference for extracting compound terrain complexity index in different complex landform regions.关键词
数字地形分析/栅格DEM/误差估计模型/误差传播定律/复合地形复杂度指标Key words
digital terrain analysis/grid DEM/error estimation model/error propagation law/compound terrain complexity index分类
交通运输引用本文复制引用
周访滨,杨自强,朱衍哲,马国伟,钟绍平..基于误差传播定律的地形复杂度误差估计[J].长沙理工大学学报（自然科学版）,2025,22(1):40-48,61,10.基金项目
国家自然科学基金项目(41671446) （41671446）
湖南省自然科学基金项目(2021JJ30702) （2021JJ30702）
长沙市自然科学基金(kq2402013) Project(41671446)supported by the National Natural Science Foundation of China （kq2402013）
Project(2021JJ30702)supported by Natural Science Foundation of Hunan Province （2021JJ30702）
Project(kq2402013)supported by Changsha Municipal Natural Science Foundation （kq2402013）
