地球信息科学学报 ›› 2013, Vol. 15 ›› Issue (5): 768-774.doi: 10.3724/SP.J.1047.2013.00768

• 遥感科学与应用技术 • 上一篇    下一篇

煤矸石堆场信息遥感提取方法对比

王鹏1, 刘庆生1, 刘高焕1, 申文明2, 李岩3, 张朝忙4, 董金发1   

  1. 1. 中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室, 北京 100101;
    2. 环境保护部卫星环境应用中心, 北京 100029;
    3. 内蒙古自治区固体废物管理中心, 呼和浩特 010000;
    4. 华中农业大学资源与环境学院, 武汉 430070
  • 收稿日期:2012-09-21 修回日期:2013-04-19 出版日期:2013-09-29 发布日期:2013-09-29
  • 通讯作者: 王鹏,E-mail:trueloveismiss@qq.com E-mail:trueloveismiss@qq.com
  • 作者简介:王鹏(1986-),男,宁夏青铜峡人,硕士,主要研究方向为遥感信息提取。E-mail:trueloveismiss@qq.com
  • 基金资助:

    环保公益资助项目(201109043)。

Method Comparison of Extraction of Gangue Yard Based on Remote Sensing

WANG Peng1, LIU Qingsheng1, LIU Gaohuan1, SHEN Wenming2, LI Yan3, ZHANG Chaomang4, DONG Jinfa1   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Satellite Environment Application Center, Ministry of Environment Protection, Beijing 100029, China;
    3. Solid Waste Management Center of Inner Mongolia Autonomous Region, Hohhot 010000, China;
    4. Resource & Environment College of Huazhong Agricultural University, Wuhan 430070, China
  • Received:2012-09-21 Revised:2013-04-19 Online:2013-09-29 Published:2013-09-29

摘要:

煤矸石作为工业特殊固体废物之一,产生于煤炭的采掘与洗煤的过程中,影响着周围的生态环境,因此,通过遥感影像获得煤矸石堆场的位置、面积信息,对于后续的调查也有很好的指导作用。本文选择2011年9月的Land-Sat5 TM影像,通过将研究区的光谱信息与地形、温度等辅助信息相结合的方式,分别使用非监督分类、监督分类、谱间关系法、分层分类法4种方法对研究区煤矸石堆场进行提取。通过对比,分层分类法提取煤矸石堆场信息的识别精度可达到78%。另外,该方法对于继续在高分辨率遥感影像上进行煤矸石堆场位置、面积的提取也有指导作用。

关键词: Landsat 5 TM, 鄂尔多斯, 谱间关系法, 分层分类法, 煤矸石堆场

Abstract:

Gangue, as one of the industry-specific solid waste produced from coal mining and coal washing, effects on around environment significantly. Therefore, monitoring of coal yard is essential for the management and protection of ecological environment. Before gangue yard detailed investigation, obtaining preliminary data of the location and area of gangue yard by remote sensing image is needed and good for subsequent investigations. This article took the image of Landsat5 TM, received in September, 2011 as data source and did the radiometric and geometric correction to the images. According to the composition and formation characteristics of gangue, we extracted the gangue yard with following two steps: firstly, got land classification information that is confused with gangue through spectral analysis and unsupervised classification; secondly, combined spectral information and terrain, temperature and other ancillary information of the study region, and used four methods, i. e., unsupervised classification, supervised classification, spectrum-photometric method and hierarchical classification respectively to extract the gangue yard of the study area. By comparison of the above methods, we found that the unsupervised classification and supervised classification methods had a faster data extraction but with low extraction accuracy. The accuracy of spectrum-photometric method is a little higher than the former two methods. The hierarchical classification method has the highest accuracy in preliminary data extraction, and the identification accuracy of the gangue yard is up to 78% after post-processing. The result basically meets the requirement on dynamic supervision of gangue yard. Thus, these methods are also useful, as guidance, to continuing extract data of the area and location of the gangue yard under high resolution remote sensing images. Especially, the hierarchical classification method is more suitable for gangue yard information extraction.

Key words: spectral method, gangue yard, hierarchical classification, Erdos, Landsat 5 TM