首页 | 本学科首页   官方微博 | 高级检索  
     检索      

机器学习在遥感影像分类中的应用
引用本文:高昂,唐世浩,肖萌,郑伟.机器学习在遥感影像分类中的应用[J].科技导报(北京),2021,39(15):67-74.
作者姓名:高昂  唐世浩  肖萌  郑伟
作者单位:国家卫星气象中心, 北京 100081
基金项目: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。

关 键 词:机器学习  遥感影像分类  深度学习  
收稿时间:2020-10-25

Application of machine learning in remote sensing image classification
GAO Ang,TANG Shihao,XIAO Meng,ZHENG Wei.Application of machine learning in remote sensing image classification[J].Science & Technology Review,2021,39(15):67-74.
Authors:GAO Ang  TANG Shihao  XIAO Meng  ZHENG Wei
Institution:National Satellite Meteorological Center, Beijing 100081, China
Abstract: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.
Keywords:machine learning  remote sensing image classification  deep learning  
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《科技导报(北京)》浏览原始摘要信息
点击此处可从《科技导报(北京)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号