Synthetic Aperture Radar for Geosciences

地质学 合成孔径雷达 范围(计算机科学) 遥感 计算机科学 雷达 地球物理学 数据科学 系统工程 地球科学 工程类 电信 程序设计语言
作者
Lingsheng Meng,Chi Yan,Suna Lv,Haiyang Sun,Sihan Xue,Quankun Li,Lingfeng Zhou,Deanna Edwing,Kelsea Edwing,Xupu Geng,Yiren Wang,Xiao‐Hai Yan
出处
期刊:Reviews of Geophysics [Wiley]
卷期号:62 (3) 被引量:54
标识
DOI:10.1029/2023rg000821
摘要

Abstract Synthetic Aperture Radar (SAR) has emerged as a pivotal technology in geosciences, offering unparalleled insights into Earth's surface. Indeed, its ability to provide high‐resolution, all‐weather, and day‐night imaging has revolutionized our understanding of various geophysical processes. Recent advancements in SAR technology, that is, developing new satellite missions, enhancing signal processing techniques, and integrating machine learning algorithms, have significantly broadened the scope and depth of geosciences. Therefore, it is essential to summarize SAR's comprehensive applications for geosciences, especially emphasizing recent advancements in SAR technologies and applications. Moreover, current SAR‐related review papers have primarily focused on SAR technology or SAR imaging and data processing techniques. Hence, a review that integrates SAR technology with geophysical features is needed to highlight the significance of SAR in addressing challenges in geosciences, as well as to explore SAR's potential in solving complex geoscience problems. Spurred by these requirements, this review comprehensively and in‐depth reviews SAR applications for geosciences, broadly including various aspects in air‐sea dynamics, oceanography, geography, disaster and hazard monitoring, climate change, and geosciences data fusion. For each applied field, the scientific advancements produced because of SAR are demonstrated by combining the SAR techniques with characteristics of geophysical phenomena and processes. Further outlooks are also explored, such as integrating SAR data with other geophysical data and conducting interdisciplinary research to offer comprehensive insights into geosciences. With the support of deep learning, this synergy will enhance the capability to model, simulate, and forecast geophysical phenomena with greater accuracy and reliability.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
niniwei完成签到,获得积分10
刚刚
自信的昊焱完成签到,获得积分10
刚刚
shichao完成签到,获得积分10
刚刚
xmhxpz完成签到,获得积分10
刚刚
嘻嘻哈哈应助KYT80153841采纳,获得10
1秒前
定位心海的锚完成签到,获得积分10
1秒前
祖f完成签到,获得积分10
1秒前
1秒前
慕容羊青完成签到,获得积分10
1秒前
一蓑烟雨完成签到,获得积分10
1秒前
2秒前
xiaoxiaostar完成签到,获得积分10
2秒前
王乾宇完成签到 ,获得积分10
2秒前
阿呷惹完成签到,获得积分10
3秒前
3秒前
英俊的铭应助痴情的秋尽采纳,获得10
3秒前
123完成签到,获得积分10
3秒前
小纸人完成签到,获得积分10
3秒前
巴巴完成签到,获得积分10
3秒前
xmhxpz发布了新的文献求助10
4秒前
配你zzz完成签到,获得积分10
4秒前
黄毅完成签到,获得积分10
4秒前
niniwei发布了新的文献求助30
5秒前
5秒前
天天快乐应助拔剑老哥采纳,获得10
5秒前
xx发布了新的文献求助10
6秒前
6秒前
liu完成签到,获得积分10
7秒前
芳芳完成签到,获得积分10
7秒前
hadern完成签到,获得积分10
7秒前
董小高儿发布了新的文献求助10
7秒前
7秒前
英俊的铭应助y_y采纳,获得10
8秒前
8秒前
JJ完成签到,获得积分10
8秒前
身体健康完成签到 ,获得积分10
8秒前
Su完成签到 ,获得积分20
8秒前
LYJ完成签到,获得积分10
8秒前
代传芬发布了新的文献求助10
9秒前
AAO完成签到,获得积分10
10秒前
高分求助中
Clinical Epidemiology: The Essentials, 6e 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Graphene Handbook (2019 Edition) 800
Adhesion Science: Principles & Practice 800
Signals, Systems, and Signal Processing 610
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
久松真一著作集〈第5巻〉禅と芸術 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6555791
求助须知:如何正确求助?哪些是违规求助? 8340026
关于积分的说明 17867426
捐赠科研通 5673712
什么是DOI,文献DOI怎么找? 2940398
邀请新用户注册赠送积分活动 1916238
关于科研通互助平台的介绍 1786623