湖北文理学院学报2026，Vol.47Issue(2)：5-11,7.
随机森林算法在测绘教学遥感影像分类中的应用
Application of Random Forest Algorithm to Remote Sensing Image Classification for Surveying and Mapping Education
摘要
Abstract
Remote sensing image classification is an indispensable step in remote sensing data analysis and is particularly important for surveying and mapping education.Although traditional classification methods have certain applications,they suffer from issues such as low processing efficiency and limited accuracy when faced with complex and high-dimensional remote sensing image data.With the rapid development of machine learning technology,the Random Forest(RF)algorithm has become a hot topic in remote sensing image classification due to its high classification accuracy and strong noise resistance.This paper proposes a remote sensing image classification teaching method based on the Random Forest algorithm,detailing the teaching design of three major stages:teaching preparation,student experiments,and teaching feedback.It analyzes the practical application of this method in remote sensing image classification and its impact on improving students'surveying and mapping abilities.Through experimental verification,the Random Forest-based teaching method effectively enhances students'remote sensing image data processing skills and machine learning application abilities,providing new ideas and practical guidance for surveying and mapping education.关键词
测绘教学/遥感影像/随机森林算法Key words
surveying and mapping education/remote sensing images/Random Forest algorithm分类
天文与地球科学引用本文复制引用
池深深,安德先,王磊..随机森林算法在测绘教学遥感影像分类中的应用[J].湖北文理学院学报,2026,47(2):5-11,7.基金项目
安徽理工大学教育教学改革研究项目(2023xjxm021) （2023xjxm021）
安徽理工大学课程思政建设研究项目(xjkcszjy2025218) （xjkcszjy2025218）
