基于光谱特征的煤矿覆煤区遥感识别与监测方法研究:以云南小龙潭矿区为例

doi:10.19741/j.issn.1673-4831.2018.0178

生态与农村环境学报 ›› 2019, Vol. 35 ›› Issue (1): 9-15.doi: 10.19741/j.issn.1673-4831.2018.0178

• 矿山生态保护与修复专题 • 上一篇下一篇

基于光谱特征的煤矿覆煤区遥感识别与监测方法研究:以云南小龙潭矿区为例

倪衡¹, 李效顺^1,2, 鹿瑶¹, 闫庆武¹, 卞正富¹

1. 中国矿业大学江苏省资源环境信息工程重点实验室, 江苏徐州 221116;
2. 南京农业大学中国土地问题研究中心, 江苏南京 210095

收稿日期:2018-04-02 出版日期:2019-01-25 发布日期:2019-01-22
通讯作者: 李效顺 E-mail:lxsh@cumt.edu.cn
作者简介:倪衡(1990-),男,江苏宿迁人,博士生,主要研究方向为矿区识别监测与生态修复治理。E-mail:niheng@cumt.edu.cn
基金资助:
国家科技基础性工作专项重点项目（2014FY110800）；国家自然科学基金（71473249，71704177）

Research on Remote Sensing Recognition and Monitoring Method of Coal-Covered Area Based on Spectral Characteristics: A Case Study of Xiaolongtan Mining Area

NI Heng¹, LI Xiao-shun^1,2, LU Yao¹, YAN Qing-wu¹, BIAN Zheng-fu¹

1. Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, China;
2. China Land Problem Research Center, Nanjing Agricultural University, Nanjing 210095, China

Received:2018-04-02 Online:2019-01-25 Published:2019-01-22
Contact: 35 E-mail:lxsh@cumt.edu.cn

摘要/Abstract

摘要：

面对煤矿区土地退化日益加重带来的严峻生态环境问题，以及露天矿区覆煤地表范围难以准确界定的现实难题，基于煤矿区典型地物水体、植被、裸地和煤堆的光谱特征以及Landsat 8遥感数据的波段特性，提出了归一化差异煤矿指数（normalized difference coal mine index，NDCMI），并结合地物样本的NDCMI值设定阈值，对煤堆与矿区背景地物信息加以区分识别。结果表明：（1）利用Landsat 8的蓝光、红光、近红外和中红外波段组成的NDCMI方法对小龙潭矿区（下辖小龙潭露天矿和布沼坝露天矿）具有较强的适用性；（2）2013-2018年，布沼坝露天矿开采面积增加1.03倍，而小龙潭露天矿开采面积减少42%；（3）在空间上小龙潭矿区的煤炭开采活动重心呈现自东北向西南、从小龙潭露天矿向布沼坝露天矿转移的趋势，大大增加了布沼坝露天矿的生态环境压力。

关键词: 地物光谱, 遥感监测, 小龙潭矿区, 归一化差异煤矿指数(NDCMI)

Abstract:

Facing the severe ecological problems brought by the increasing land degradation in the coal mining areas and the difficulties on the defining of the scope of coal-covered surface in the open-pit mining areas, a normalized difference coal mine index (NDCMI) was proposed based on the spectral characteristics of typical water bodies, vegetation, bare land and coal piles in the coal mining areas as well as the band characteristics of Landsat 8 remote sensing data. The NDCMI value of the ground object samples was used to set the threshold value to distinguish and identify the ground object information of the coal pile and the mining area. The results show that:First, consisting of blue, red, near-infrared and mid-infrared bands of Landsat 8, the NDCMI method was applicative to the Xiaolongtan mining area; Second, from 2013 to 2018, the area of the Buzhaoba open-pit mining area increased by 1.03 times, while the area of Xiaolongtan open-pit mining area decreased by 42%; The gravity of coal mining activities in Xiaolongtan mining area showed a spatial trend from northeast to southwest and the trend from Xiaolongtan open-pit mining area to Buzhaoba open-pit mining area, which greatly increased the pressure on ecology and environment of the Buzhaoba open pit mining area.

Key words: spectrum, remote sensing monitoring, Xiaolongtan mining area, NDCMI

中图分类号:

X87
P237

倪衡, 李效顺, 鹿瑶, 闫庆武, 卞正富. 基于光谱特征的煤矿覆煤区遥感识别与监测方法研究:以云南小龙潭矿区为例[J]. 生态与农村环境学报, 2019, 35(1): 9-15.

NI Heng, LI Xiao-shun, LU Yao, YAN Qing-wu, BIAN Zheng-fu. Research on Remote Sensing Recognition and Monitoring Method of Coal-Covered Area Based on Spectral Characteristics: A Case Study of Xiaolongtan Mining Area[J]. Journal of Ecology and Rural Environment, 2019, 35(1): 9-15.

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基于光谱特征的煤矿覆煤区遥感识别与监测方法研究:以云南小龙潭矿区为例

Research on Remote Sensing Recognition and Monitoring Method of Coal-Covered Area Based on Spectral Characteristics: A Case Study of Xiaolongtan Mining Area

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