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。

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.