Spatial and temporal characteristics analysis of land subsidence in the Beijing Plain based on ST-PCA

SONG Zongwen; WANG Yanbing; LI Xiaojuan; LI Chenxia; ZHAO Yali; LI Yanxin; YANG Xiyue; CHENG Haowen

doi:10.11834/jrs.20254142

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Spatial and temporal characteristics analysis of land subsidence in the Beijing Plain based on ST-PCA
“Researchers used PS InSAR technology to obtain land subsidence data in the Beijing Plain area from 2010 to 2016. The ST-PCA method was used to reveal the spatiotemporal evolution characteristics of land subsidence in the area, and it was found that the data showed a continuous linear trend combined with seasonal fluctuations in time, and uneven distribution and regional agglomeration in space, providing important data support for land subsidence prevention and control.”
- role：First author第一作者
- Affiliation：
  College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
  Key Laboratory of 3D information acquisition and application, Ministry of Education, Capital Normal University, Beijing 100048, China
  Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
- Email：songzw@cnu.edu.cn
- Introduction：宋宗雯，研究方向为地理信息科学与InSAR地面沉降监测及分析。E-mail： songzw@cnu.edu.cn
SONG Zongwen
123 * ,
- role：Corresponding author通信作者
- Affiliation：
  College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
  Key Laboratory of 3D information acquisition and application, Ministry of Education, Capital Normal University, Beijing 100048, China
  Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
- Email：wyb@cnu.edu.cn
- Introduction：王彦兵，研究方向为基于InSAR的地面沉降研究、空间数据挖掘。E-mail： wyb@cnu.edu.cn
WANG Yanbing
123 * ,
- Affiliation：
  College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
  Key Laboratory of 3D information acquisition and application, Ministry of Education, Capital Normal University, Beijing 100048, China
  Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
LI Xiaojuan
123 * ,
- Affiliation：
  College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
  Key Laboratory of 3D information acquisition and application, Ministry of Education, Capital Normal University, Beijing 100048, China
  Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
LI Chenxia
123 * ,
- Affiliation：
  Beijing Institute of Surveying and Mapping, Beijing 100038, China
ZHAO Yali
4 * ,
- Affiliation：
  College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
  Key Laboratory of 3D information acquisition and application, Ministry of Education, Capital Normal University, Beijing 100048, China
  Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
LI Yanxin
123 * ,
- Affiliation：
  College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
  Key Laboratory of 3D information acquisition and application, Ministry of Education, Capital Normal University, Beijing 100048, China
  Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
YANG Xiyue
123 * ,
- Affiliation：
  College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
  Key Laboratory of 3D information acquisition and application, Ministry of Education, Capital Normal University, Beijing 100048, China
  Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
CHENG Haowen
123 *
Vol. 29, Issue 9, Pages: 2810-2822(2025)
DOI：10.11834/jrs.20254142
Accepted：

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Spatial and temporal characteristics analysis of land subsidence in the Beijing Plain based on ST-PCA

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Spatial and temporal characteristics analysis of land subsidence in the Beijing Plain based on ST-PCA

SONG Zongwen

WANG Yanbing

LI Xiaojuan

LI Chenxia

ZHAO Yali

LI Yanxin

YANG Xiyue

CHENG Haowen

DOI：10.11834/jrs.20254142

AI Introduction

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Figs( 34 ) Tabs( 2 )

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