矿区煤及矸石压占灾害决策树分类提取方法

矿业活动为现代工业提供物质基础的同时,极大扰动矿区原有生态结构。煤与矸石压占是矿区多种地质灾害的一种,煤与矸石压占直接造成矿区珍贵的土地资源的浪费,同时,煤与矸石自燃、淋溶、扬尘以及天然放射性对矿区环境有严重影响。近年来,遥感技术以其大范围、实时性等技术优势,在探索矿业活动与生态保护共同途径方面做了大量有益的尝试,尤其在地质灾害监测预警方面体现了广阔应用前景。本文通过对矿区遥感影像的一系列处理(如图像校正,图像增强,图像分类),探索性地采用基于人工智能的决策树分类方法,有效地排除掉同谱异物的现象的影响,高精度地提取出矿区煤与矸石堆放场,为统计煤与矸石压占,预知煤与矸石自燃,判断煤与矸石淋溶、扬尘以及天然放射性对周围环境的影响,以及为今后煤与矸石场的选址规划,提供第一手定量化的地理属性资料。

DENTIFYING COAL & GANGUE STACK SITE BY DECISION TREE CLASSIFIER METHOD

To provide a plenty of foundation materials for modern industry,mining activities have greatly undermined the original ecological structure of the mining area.Coal gangue stack occupation area,brining about land resources waste in mining area,is one of the geological disasters.At the same time,it leads to the resulting of spontaneous combustion of coal and waste rock,noxious liquid leaching,dust and natural radioactive and impacts on the environment of mining field seriously.In recent years,remote sensing technology with large-scale,real-time technical advantage has done a great deal of useful attempt to finding the common ways contacting resources exploration and ecological protection.Especially in geological disaster monitoring and early warning it reflects a broad application prospects.In this paper,a series method of remote sensing image processing such as image correction,image enhancement,and image classifier is applied.As a kind of exploration,Decision Tree classifier method is adopted based on the artificial intelligence,which greatly exclude the phenomena of different spectra characteristics with the same object.The information of coal gangue stack areas is extracted in highly precision.It will provide first-hand quantitative information on the geographical attributes for the statistics of coal and gangue stack areas,prediction of spontaneous combustion of coal and gangue,determination the impact of leaching,dust and the natural radioactivity of coal gangue on the surrounding environment of mining area,and election site and disposing of coal gangue.