Coal exploration technology based on visible-infrared spectra and remote sensing data

In the modern society, coal is used as the main source of energy. In this paper, based on the theory of the remote sensing, the distributions of the coal mine area through the satellite imagery are measured. First, the satellite pictures of coal mining regions in Quangninh of Vietnam and Huolinhe of China were gathered as the experimental data. Second, spectrometer was used to measure the spectral data of the coal samples of these two regions. The measured data provide comprehensive and accurate spectral characteristics of the coal. Then the classification model can be built by the improved extreme learning machines algorithm based on the measured data and the remote sensing data. Finally, the distribution image of the coal mine area is obtained accurately based on the classification model. © 2017 Taylor & Francis.