机器学习在遥感影像分类中的应用  

Application of machine learning in remote sensing image classification

作　　者：高昂 唐世浩[1] 肖萌[1] 郑伟[1] GAO Ang;TANG Shihao;XIAO Meng;ZHENG Wei(National Satellite Meteorological Center,Beijing 100081,China)

机构地区：[1]国家卫星气象中心,北京100081

出　　处：《科技导报》2021年第15期67-74,共8页Science & Technology Review

基　　金：国家重点研发计划重点专项(2018YFC1506500)。

摘　　要：概述了机器学习的主要方法及其在遥感影像的主要应用方向,涵盖环境生态遥感中机器学习技术的研究、应用情况及近年来的新进展。通过使用深度学习对FY-3C气象卫星资料进行积雪检测的应用实例,说明深度学习模型可以利用大数据的优势不断提高检测精度,在某些指标中取得了更优于传统机器学习的精度,可解决传统机器学习难以解决的一些问题,从而带动遥感应用模式的创新。This paper summarizes the main methods of machine learning and its main application direction in remote sensing image. It covers the research and application of machine learning technology in environmental ecological remote sensing, and the new progress in recent years. Through the application of deep learning to snow detection of FY-3C meteorological satellite data,it is shown that the deep learning model can improve the detection accuracy by means of big data advantages, and has achieved better precision than traditional machine learning in some indexes, thus solving some problems that are difficult to solve using traditional machine learning method, and driving the innovation of remote sensing application mode.

关 键 词：机器学习 遥感影像分类 深度学习 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TP751[自动化与计算机技术—控制科学与工程]