Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026

相关实验视频

Updated: May 31, 2025

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
06:49

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Published on: June 16, 2014

17.1K

时间序列变化检测使用KOMPSAT-5数据与统计均像素选择算法.

Mirza Muhammad Waqar1, Heein Yang1, Rahmi Sukmawati1

  • 1Satellite Image Application Team, CONTEC, Daejeon 34074, Republic of Korea.

Sensors (Basel, Switzerland)
|January 25, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种强大的方法,用于使用KOMPSAT-5时间序列合成光圈雷达 (SAR) 数据检测城市变化. 该方法实现了92%的准确性,提高了城市监测的变化检测能力.

关键词:
KOMPSAT-5 探测振幅变化的探测.变化检测检测的变化检测统计均像素 (SHP) 是指统计均像素.

更多相关视频

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.8K
Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

314

相关实验视频

Last Updated: May 31, 2025

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
06:49

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences

Published on: June 16, 2014

17.1K
Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.8K
Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

314

科学领域:

  • 遥感 遥感 遥感 遥感
  • 地理空间分析是什么
  • 地球观测 地球观测

背景情况:

  • 振幅变化检测 (ACD) 和连贯变化检测 (CCD) 是合成光圈雷达 (SAR) 变化检测的常用方法.
  • 时间序列SAR数据经常受到噪音和变异的影响,使分析复杂化,需要强大的预处理.
  • 空间变化和环境因素可能会影响传统SAR变化检测方法的准确性.

研究的目的:

  • 开发和验证使用KOMPSAT-5时间序列SAR数据进行城市变化检测的强有力的方法.
  • 通过全面的预处理来解决SAR数据中的噪声和变化.
  • 为了提高基于SAR的城市变化检测的可靠性和准确性,用于监控应用.

主要方法:

  • 实施了预处理框架,包括联合注册,放射测量地形校正,规范化和斑点过.
  • 使用统计同质像素 (SHPs) 进行稳定的目标识别和基于连贯性的分析,以获得时间背景相关性.
  • 应用了适应性值,形态操作和小片段去除,以改进变化和降低噪音.

主要成果:

  • 在检测城市变化方面取得了92%的整体准确性,通过混矩阵分析验证.
  • 成功识别城市变化,证明了开发方法的有效性.
  • 预处理和分析框架被证明是可靠的,用于一致和准确的SAR数据解释.

结论:

  • 开发的方法提供了一种可靠的方法,用于使用KOMPSAT-5时间序列SAR数据检测城市变化.
  • 这些发现凸显了KOMPSAT-5数据在灾后监测和城市规划方面的潜力.
  • 对InSAR轨道稳定的进一步研究可以提高探测精度并扩大SAR时间序列应用.