测绘学报 ›› 2022, Vol. 51 ›› Issue (10): 2107-2116.doi: 10.11947/j.AGCS.2022.20220308

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基于区域参考框架的GNSS滑坡监测

王国权1, 鲍艳2   

  1. 1. 休斯顿大学地球与大气科学系, 休斯顿 77024;
    2. 北京工业大学城市与工程安全减灾教育部重点实验室, 北京 100124
  • 收稿日期:2022-05-29 修回日期:2022-09-06 发布日期:2022-11-05
  • 作者简介:王国权(1972—),男,博士,教授,研究方向为卫星大地测量与自然灾害监测。E-mail:gwang@uh.edu
  • 基金资助:
    国家自然科学基金(51829801)

GNSS landslide monitoring aligned to regional reference frames

WANG Guoquan1, BAO Yan2   

  1. 1. Department of Earth and Atmospheric Sciences, University of Houston, Houston 77024, U. S.;
    2. Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, China
  • Received:2022-05-29 Revised:2022-09-06 Published:2022-11-05
  • Supported by:
    The National Natural Science Foundation of China (No. 51829801)

摘要: 区域参考框架是实现高精度区域大地形变观测和滑坡灾害长期监测的基础设施。结合活动地块的划分和长期的GNSS观测结果,笔者将我国大陆和海域初步划分为7个“刚性骨架地块”,简称“刚性地块”,拟建立覆盖我国陆海全域的区域参考框架系列:东北、华北、华南、西北、青藏、川滇及南海参考框架。本文介绍了从全球参考框架(IGS14)到区域参考框架的坐标转换方法,并例举了华北参考框架(NChina20)和华南参考框架(SChina20)在滑坡长期监测和滑坡初动自动识别领域的应用。

关键词: GNSS, 区域参考框架, 滑坡监测, 隐伏滑坡, 滑坡初动自动识别

Abstract: Regional reference frames are the critical geodetic infrastructure for realizing high-accuracy crustal deformation and long-term landslide monitoring. According to the published results in active tectonic-block zonation and long-term GNSS observations, the authors divide China into seven “rigid-frame blocks” (or “rigid blocks”) and intend to establish the stable regional reference frame series covering the entire land and sea areas of China: Northeast, North, South, Northwest, Qinghai-Tibet, Sichuan-Yunnan, and South China Sea reference frames. This article introduces the method for realizing the coordinate transformation from the global reference frame (IGS14) to regional reference frames and exemplifies the applications of the North China Reference Frame (NChina20) and the South China Reference Frame (SChina20) in long-term landslide monitoring and initial slide automatic detection.

Key words: GNSS, regional reference frame, landslide monitoring, hidden landslide, initial slide automatic detection

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