基于机器学习的遥感数据处理方法综述

Survey of Remote Sensing Data Processing Methods Based on Machine Learning

随着科技的不断发展,遥感技术在人类社会的发展中发挥着重要的作用。但是传统遥感数据处理方法也存在诸多问题,例如在遥感图像分类时,通过人工方式对遥感图像进行标注需要耗费大量的时间和人力,如果使用机器学习方法处理此类问题就能够有效提高分类效率。本文主要介绍遥感领域常用的机器学习方法,并举例阐述机器学习方法在复杂遥感领域的应用。

With the continuous development of technology,remote sensing technology plays an important role in the development of human society.However,there are also many problems in traditional remote sensing data processing methods.For example,in the classification of remote sensing images,it takes a lot of time and manpower to manually label remote sensing images.If machine learning methods are used to deal with such problems,the classification efficiency can be effectively improved.This paper mainly introduces how machine learning methods are applied in various fields of remote sensing technology.