Hierarchical multi-scale segmentation-based information extraction and dynamic monitoring for the Tagaung Taung nickel deposit, Myanmar

High-resolution remote sensing images have been widely applied to classification of ore deposits. However, there is a lack of studies on the information extraction and dynamic monitoring of open-pit lateritic nickel deposits. Using high-resolution remote sensing images from the Pleiades and GF-2 satellites, this study investigated the famous open-pit Tagaung Taung nickel deposit in Myanmar. First, information about surface features was extracted using object-oriented classification based on hierarchical multi-scale segmentation. Then, the dynamic changes in the nickel deposit were analyzed. Finally, qualitative and quantitative assessments of the classification accuracy were carried out. The results indicate that the hierarchical multi-scale segmentation technology exhibited encouraging classification and identification effects, with overall classification accuracy of 94.24% and 89.02% and the Kappa coefficients of 0.889 and 0.816, respectively for images from the Pleiades and GF-2 satellites. Therefore, the proposed method is suitable for the information extraction of open-pit lateritic nickel deposits. The dynamic change analysis reveals that the Tagaung Taung nickel deposit experienced continuous expansion of mining at high mining speeds from 2015 to 2017. It can be inferred that this deposit has great potential and broad prospects for resource development. The results of this study can provide technical support for the dynamic monitoring of the Tagaung Taung nickel deposit in Myanmar.