Self-supervised contrastive learning clustering method for InSAR time series deformation data

WU Hanfei; FENG Bin; LI Menghua; YANG Mengshi; ZHANG Zhen; TANG Bohui

doi:10.11834/jrs.20254393

InSAR Deformation Monitoring | Views:821Downloads:2917CSCD:0

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Self-supervised contrastive learning clustering method for InSAR time series deformation data
- role：First author第一作者
- Affiliation：
  School of Land and Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
- Email：20212201138@stu.kust.edu.cn
- Introduction：吴晗飞，研究方向为InSAR形变数据处理。E-mail： 20212201138@stu.kust.edu.cn
WU Hanfei
1 * ,
- Affiliation：
  School of Land and Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
FENG Bin
1 * ,
- role：Corresponding author通信作者
- Affiliation：
  School of Land and Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
  Yunnan Provincial Key Laboratory of Quantitative Remote Sensing (Under Preparation), Kunming 650093, China
  Yunnan International Joint Laboratory for Integrated Intelligent Monitoring of Mountain Hazards by Sky and Land, Kunming 650093, China
- Email：menghuali@kust.edu.cn
- Introduction：李梦华，研究方向为InSAR地质灾害监测。E-mail： menghuali@kust.edu.cn
LI Menghua
123 * ,
- Affiliation：
  School of Earth Sciences, Yunnan University, Kunming 650500, China
YANG Mengshi
4 * ,
- Affiliation：
  School of Land and Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
  Yunnan Provincial Key Laboratory of Quantitative Remote Sensing (Under Preparation), Kunming 650093, China
  Yunnan International Joint Laboratory for Integrated Intelligent Monitoring of Mountain Hazards by Sky and Land, Kunming 650093, China
ZHANG Zhen
123 * ,
- Affiliation：
  School of Land and Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
  Yunnan Provincial Key Laboratory of Quantitative Remote Sensing (Under Preparation), Kunming 650093, China
  Yunnan International Joint Laboratory for Integrated Intelligent Monitoring of Mountain Hazards by Sky and Land, Kunming 650093, China
TANG Bohui
123 *
Vol. 29, Issue 7, Pages: 2442-2456(2025)
DOI：10.11834/jrs.20254393
Accepted：

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Self-supervised contrastive learning clustering method for InSAR time series deformation data

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Self-supervised contrastive learning clustering method for InSAR time series deformation data

WU Hanfei

FENG Bin

LI Menghua

YANG Mengshi

ZHANG Zhen

TANG Bohui

DOI：10.11834/jrs.20254393

AI Introduction

Full Text(HTML)

Figs( 30 ) Tabs( 2 )

References

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