**5. Conclusion**

In this study a methodology for rapid identification of mines and precise delineation of theirs boundaries is presented, with the use of both freely-available data and open-source software. For this reason a cloudless Sentinel-2A imagery was obtained covering the area of interest. Following the initial processing steps, image segmentation was carried out using Mean-Shift algorithm and an unsupervised segmentation evaluation metric was calculated for different parameters' values. It is combined by an autocorrelation index that identifies separability between segments and variance, an indicator that depicts the global homogeneity of segments. Then, NDVI and its mean values for each segment were computed. Finally, the mine area was extracted by implementing some spatial analysis tools including dissolve algorithm in order to aggregate segments that share a common boundary.
