测绘通报 ›› 2025, Vol. 0 ›› Issue (2): 180-184.doi: 10.13474/j.cnki.11-2246.2025.0232

• 测绘地理信息技术应用案例 • 上一篇    

陕北某煤矿浅埋层地表移动规律研究

赵思佳, 王晓宇, 张若兰, 张萍丽, 李宏超   

  1. 河南测绘职业学院, 河南 郑州 450001
  • 收稿日期:2024-10-30 发布日期:2025-03-03
  • 作者简介:赵思佳(1988—),女,讲师,长期从事国土资源管理、土地规划方面的研究。E-mail:zhaosijia2024@126.com
  • 基金资助:
    河南省科技厅软科学资助(242400411047);河南省高校人文社会科学研究项目(2024-ZDJH-181)

Study on surface movement law of shallow buried layer in a coal mine in northern Shaanxi

ZHAO Sijia, WANG Xiaoyu, ZHANG Ruolan, ZHANG Pingli, LI Hongchao   

  1. Henan Vocational College of Surveying and Mapping, Zhengzhou 450001, China
  • Received:2024-10-30 Published:2025-03-03

摘要: 陕北侏罗纪煤田位于我国生态环境较为敏感的区域。长期以来,煤炭开采活动对该地区的生态造成了深远影响。监测和分析地表移动规律能够评估受影响的范围和受损最严重的地区,进而制定出有针对性的修复措施。本文利用陕西某煤矿的实际开采数据,经过计算分析,得出了地表沉降和水平位移的具体数值,以及地表移动的动态和静态角度参数;并依据概率积分法的原理,利用Matlab拟合求参确定了概率积分参数。本文研究成果可为理解陕北地区浅层煤矿地表移动规律,以及治理生态环境提供一定的参考。

关键词: 浅埋煤层, 地表移动规律, 动态参数, 静态参数, 概率积分法, Matlab参数拟合

Abstract: The Jurassic coalfield in Northern Shaanxi is located in a region of China that is ecologically sensitive. Long-term coal mining activities have had a profound impact on the ecology of this area. By monitoring and analyzing the patterns of surface movement, it is possible to assess the extent of the affected areas and the regions that are most severely damaged, thereby formulating targeted remediation measures. This study utilizes actual mining data from a coal mine in Shaanxi to calculate and analyze the specific values of surface subsidence and horizontal displacement, as well as the dynamic and static angular parameters of surface movement. Based on the principle of the probability integration method, probability integration parameters are determined using Matlab for parameter fitting. The findings of this study provide a reference for understanding the patterns of surface movement over shallow coal mines in the Northern Shaanxi region and for the management of the ecological environment.

Key words: shallow coal seam, the law of surface movement, dynamic parameters, static parameter, probability integral method, Matlab parameter fitting

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