Artificial Intelligence for Remote Sensing Data Analysis: A review of challenges and opportunities

IF 16.2 1区 地球科学 Q1 GEOCHEMISTRY & GEOPHYSICS
Lefei Zhang, Liangpei Zhang
{"title":"Artificial Intelligence for Remote Sensing Data Analysis: A review of challenges and opportunities","authors":"Lefei Zhang, Liangpei Zhang","doi":"10.1109/mgrs.2022.3145854","DOIUrl":null,"url":null,"abstract":"Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI, particularly machine learning algorithms, range from initial image processing to high-level data understanding and knowledge discovery. AI techniques have emerged as a powerful strategy for analyzing RS data and led to remarkable breakthroughs in all RS fields. Given this period of breathtaking evolution, this work aims to provide a comprehensive review of the recent achievements of AI algorithms and applications in RS data analysis. The review includes more than 270 research papers, covering the following major aspects of AI innovation for RS: machine learning, computational intelligence, AI explicability, data mining, natural language processing (NLP), and AI security. We conclude this review by identifying promising directions for future research.","PeriodicalId":48660,"journal":{"name":"IEEE Geoscience and Remote Sensing Magazine","volume":"10 1","pages":"270-294"},"PeriodicalIF":16.2000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"116","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Geoscience and Remote Sensing Magazine","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1109/mgrs.2022.3145854","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 116

Abstract

Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI, particularly machine learning algorithms, range from initial image processing to high-level data understanding and knowledge discovery. AI techniques have emerged as a powerful strategy for analyzing RS data and led to remarkable breakthroughs in all RS fields. Given this period of breathtaking evolution, this work aims to provide a comprehensive review of the recent achievements of AI algorithms and applications in RS data analysis. The review includes more than 270 research papers, covering the following major aspects of AI innovation for RS: machine learning, computational intelligence, AI explicability, data mining, natural language processing (NLP), and AI security. We conclude this review by identifying promising directions for future research.
遥感数据分析的人工智能:挑战与机遇综述
人工智能在遥感中发挥着越来越重要的作用。人工智能的应用,特别是机器学习算法,从最初的图像处理到高级数据理解和知识发现。人工智能技术已成为分析遥感数据的强大策略,并在所有遥感领域取得了显著突破。鉴于这一惊人的发展时期,这项工作旨在全面回顾人工智能算法及其在RS数据分析中的应用的最新成就。该综述包括270多篇研究论文,涵盖了RS人工智能创新的以下主要方面:机器学习、计算智能、人工智能可解释性、数据挖掘、自然语言处理(NLP)和人工智能安全。我们通过确定未来研究的有希望的方向来结束这篇综述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
IEEE Geoscience and Remote Sensing Magazine
IEEE Geoscience and Remote Sensing Magazine Computer Science-General Computer Science
CiteScore
20.50
自引率
2.70%
发文量
58
期刊介绍: The IEEE Geoscience and Remote Sensing Magazine (GRSM) serves as an informative platform, keeping readers abreast of activities within the IEEE GRS Society, its technical committees, and chapters. In addition to updating readers on society-related news, GRSM plays a crucial role in educating and informing its audience through various channels. These include:Technical Papers,International Remote Sensing Activities,Contributions on Education Activities,Industrial and University Profiles,Conference News,Book Reviews,Calendar of Important Events.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信