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自然资源遥感  2023, Vol. 35 Issue (3): 310-318    DOI: 10.6046/zrzyyg.2022170
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黔西南采煤塌陷区高分遥感动态监测——以六盘水市煤矿采空塌陷区为例
于航(), 安娜(), 汪洁, 邢宇, 许文佳, 步凡, 王晓红, 杨金中
中国自然资源航空物探遥感中心,北京 100083
High-resolution remote sensing-based dynamic monitoring of coal mine collapse areas in southwestern Guizhou: A case study of coal mine collapse areas in Liupanshui City
YU Hang(), AN Na(), WANG Jie, XING Yu, XU Wenjia, BU Fan, WANG Xiaohong, YANG Jinzhong
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China
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摘要 

我国西南地区是地质灾害高发区,在矿产资源开发过程中极易引发地质灾害和相关次生灾害。为研究采煤塌陷区遥感动态监测技术,以贵州省六盘水市煤矿开采集中区为研究区,利用高空间分辨率遥感影像,通过建立黔西南山原地区采煤塌陷遥感地质解译标志,对六盘水地区2009—2018年地质灾害情况进行了动态监测,并分析了研究区的地质灾害现状。根据遥感解译成果,发现该地区地质灾害情况多年来明显加剧,相较于2009年,2018年地质灾害面积扩大167%,且新增地质灾害区域面积占40%、变差区域面积增加34%。根据研究区地质灾害程度划分出4个地质灾害集中区,发现地质灾害集中区和该地区采矿密集区域高度重合。根据遥感数据剖析了矿山地质灾害损毁地类类型,判断研究区矿山地质灾害可能对广大人民和生态环境产生的危害情况,其中对土地严重损毁的灾害类型中,毁损面积最大的为林地和耕地(共193处),面积总计约为333.55 hm2。研究区内共有潜在隐患威胁区域360处,面积为506.36 hm2,其中对道路威胁数量最多(共有126处),面积为110.04 hm2。研究结果可为当地生态环境修复和矿山地质灾害治理提供可靠参考数据和重要研究思路,并针对研究区的特点,深入分析该地区矿山地质灾害成因,探讨治理方案,提出对策建议。

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于航
安娜
汪洁
邢宇
许文佳
步凡
王晓红
杨金中
关键词 六盘水市矿山地质灾害遥感监测采煤塌陷区    
Abstract

Southwestern China suffers frequent geological disasters. The exploitation of mineral resources in southwestern China is highly liable to induce geological disasters and related secondary disasters. This study investigated the remote sensing-based dynamic monitoring technology for coal mine collapse areas in the coal mining concentration areas in Liupanshui City, Guizhou Province. Based on the high-resolution remote sensing images, this study established remote sensing geological interpretation symbols of coal mine collapse areas in the mountainous plateau of southwestern Guizhou and then dynamically monitored the geological disasters in Liupanshui from 2009 to 2018. Moreover, this study analyzed the present geological disasters in the study area. The remote sensing interpretation revealed that geological disasters in the study area were significantly aggravated over the years. Compared with 2009, 2018 witnessed an increase of 167% in the geological disasters, including 40% of new geological disaster areas and 34% of areas with deteriorated geological disasters. According to the geological disaster degrees in the study area, this study identified four geological disaster concentration areas, which were highly consistent with the mining concentration areas in the study area. Based on the remote sensing data, this study analyzed the types of land damaged by geological disasters in mines and investigated possible resulting damage to the people and the ecological environment in the study area. The results show that disasters that severely damaged land caused the largest damage area for forest and cultivated lands, which had a total number of 193 and a total area of about 333.55 hm2. There are 360 areas with potential hazards in the study area, covering an area of 506.36 hm2. They are dominated by 126 threats to roads, which cover an area of 110.04 hm2. The results of this study can provide a reliable data reference and a critical research approach for restoring the local ecological environment and controlling geological disasters in mines. Moreover, based on the characteristics of the study area, this study further analyzed the causes of the geological disasters in mines, explored the geological disaster control schemes, and proposed countermeasures and suggestions.

Key wordsLiupanshui City    geological disasters in mines    remote sensing monitoring    coal mine collapse area
收稿日期: 2022-04-28      出版日期: 2023-09-19
ZTFLH:  TP79  
基金资助:中国地质调查局项目“全国矿山开发及重点地区生态空间遥感监测”(202012000000210017)
通讯作者: 安 娜(1980-),女,高级工程师,主要从事遥感矿产地质、自然资源、土地研究。Email:an_na826@163.com
作者简介: 于 航(1990-),男,工程师,主要从事遥感矿产地质、自然资源、土地研究。Email: 591701381@qq.com
引用本文:   
于航, 安娜, 汪洁, 邢宇, 许文佳, 步凡, 王晓红, 杨金中. 黔西南采煤塌陷区高分遥感动态监测——以六盘水市煤矿采空塌陷区为例[J]. 自然资源遥感, 2023, 35(3): 310-318.
YU Hang, AN Na, WANG Jie, XING Yu, XU Wenjia, BU Fan, WANG Xiaohong, YANG Jinzhong. High-resolution remote sensing-based dynamic monitoring of coal mine collapse areas in southwestern Guizhou: A case study of coal mine collapse areas in Liupanshui City. Remote Sensing for Natural Resources, 2023, 35(3): 310-318.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2022170      或      https://www.gtzyyg.com/CN/Y2023/V35/I3/310
Fig.1  六盘水市研究区RapidEye遥感影像煤矿分布
年度 数据源 空间分辨率/m 处理方法
2009年 RapidEye 5 全色与多光谱数据融合
2018年 P1+GJ1+
SPOT6+RE
0.5+2.5 全色与多光谱数据融合
Tab.1  研究区2009年和2018年卫星数据
Fig.2  研究区遥感数据解译标志
年份 塌陷
坑(群)
地裂
缝(群)
有隐患
滑坡
滑塌(群) 合计
2009年 6.43 1.26 141.30 191.02 340.01
2018年 22.47 10.46 293.57 241.59 568.09
Tab.2  研究区地质灾害变化情况统计(2009—2018年)
Fig.3  2009—2018年地质灾害主要分布区变化情况统计
灾害程度 塌陷坑(群) 地裂缝(群) 有隐患滑坡 滑塌(群) 合计
特别严重 1/0.41 - 2/1.22 16/170.77 19/172.40
严重 3/4.42 2/4.30 132/142.25 16/44.77 153/195.74
较严重 8/8.15 7/4.69 169/105.01 5/20.06 189/137.91
一般 10/9.49 4/1.47 79/45.09 3/5.99 96/62.04
合计 22/22.47 13/10.46 382/293.57 40/241.59 457/568.09
Tab.3  Statistics of severity of geological disasters(处/hm2)
Fig.4  研究区矿山地质灾害集中区分布
被损毁地类 塌陷坑(群) 地裂缝(群) 有隐患滑坡 滑塌(群) 合计
其他地类 18/20.22 8/3.91 223/165.03 7/41.17 256/230.33
草地 1/0.94 7/3.27 8/4.21
林地及耕地 3/1.31 5/6.54 152/125.28 33/200.42 193/333.55
合计 22/22.47 13/10.45 382/293.58 40/241.59 457/568.09
Tab.4  Statistics of damage caused by geological disasters(处/hm2)
地灾隐患类型 道路 果园 建筑物 城镇 村庄 煤矿 水库 水系 煤矿中转场地 合计
滑塌(群) 21.19 0 8.71 64.50 88.51 50.84 0 0 0 233.75
有隐患滑坡 79.46 0.75 60.66 6.58 55.74 41.33 3.70 5.91 4.34 258.47
地裂缝(群) 1.72 0 0.76 0 0.62 0.31 0 0 0.21 3.62
塌陷坑(群) 7.67 0 0.74 1.08 1.03 0 0 0 0 10.52
合计 110.04 0.75 70.87 72.16 145.90 92.48 3.70 5.91 4.55 506.36
Tab.5  地质灾害威胁面积统计
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