Decision Tree classifier of coal & gangue Stack Areas

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 of 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 based on the artificial intelligence, which greatly exclude the phenomena of different spectra characteristics with the same object is adopted and 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, the prediction of spontaneous combustion of coal and gangue, the determination of leaching, dust and the natural radioactivity of coal & gangue in the impact on the surrounding environment of mining area and for election site and disposing of coal & gangue.