Monitoring Active Mining Areas in Operation using Sentinel-1 Coherence Time Series

Monitoring and mapping open-pit mining activity is essential to identify operation sites and unaffected surfaces of mining areas. Vertical displacements of the earth's surface associated with open pit mining can be detected using high spatial resolution Digital Surface Model (DSM) data or based on all-weather Synthetic Aperture Radar (SAR) Single Look Complex (SLC) satellite images using Differential Interferometry Synthetic Aperture Radar (DInSAR) technique. In some cases, activity in an open pit may not be accompanied by changes in terrain heights but cause violations of land cover integrity accompanied by earth's surface texture changes (for example, deforestation or recultivation, violation of quarries and dump slope integrity, changes in surface conditions, hydrological disturbances, etc.) and can be detected using coherence maps generated from SAR SLC data.Coherence is the modulus of the complex correlation coefficient between two SLC images containing information about the amplitude and phase of the radar signal. If there is no surface change between the two survey dates, the coherence values are close to 1. Mining activities change the surface texture, so the coherence decreases to values close to 0. The frequency approach estimates the total changes in coherence over the season. For example, the Temporal Activity Index (TAI) is a relative coherence frequency below a given threshold across the time series of SAR images. In the case of monitoring open pit mining, activity areas with consistently low coherence over a time series of observations are of primary interest.The study area is an open-pit mining area of the Pyh&amp;#228;salmi Mine located in the Pohjois-Pohjanmaa region, Finland. It includes an old open pit, a backfill open pit, and several waste dumps [1]. Time series of Sentinel-1 SLC Interferometric Wide (IW) images were used to detect active areas in operation for the study area. Images were collected every 12 days from May to &amp;#160;September 2020-2022 and provided by the GOLDEN-AI platform [2].For each observation year, a time series of Sentinel-1 SLC coherence was generated for the Pyh&amp;#228;salmi mine. Active areas in operation were identified for open pits and waste dumps based on TAI maps (Fig. 1), providing information about the intensity of surface changes during the observation periods.Figure 1. Temporal Activity Index maps for the Pyh&amp;#228;salmi Mine area.Funding. This work was funded by the European Union&amp;#8217;s Horizon 2020 research and innovation programme under grant agreement No. 869398 &amp;#8220;Earth observation and Earth GNSS data acquisition and processing platform for safe, sustainable and cost-efficient mining operations&amp;#8221; (Goldeneye).Acknowledgments. The authors gratefully acknowledge Maria H&amp;#228;nninen, Environmental Manager at Pyh&amp;#228;salmi Mine Oy for specification locations for measurements and study planning, and the OPT/NET BV company (opt-net.eu) and GOLDEN-AI platform for supplying Sentinel-1 data. The authors would like to thank the European Commission, the European Space Agency, and the Copernicus Program for providing Sentinel-1 data.References:[1] Siikanen, S., Savolainen, M., Karinen, A., Puputti, J., Kauppinen, T., Uusitalo, S., &amp; Paavola, M., 2022. Drone-based near-infrared multispectral and hyperspectral imaging in monitoring structural changes in mine tailing ponds. Thermal Infrared Applications XLIV, Vol. 12109, pp. 58-64). https://doi.org/10.1117/12.2618294[2] Havisto, J., Matselyukh, T., Paavola, M., Uusitalo, S., Savolainen, M., Gonz&amp;#225;lez, A. S., Knobloch, A. &amp; Bogdanov, K., 2021. Golden AI Data Acquisition and Processing Platform for Safe, Sustainable and Cost-Efficient Mining Operations. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, pp. 5775-5778. https://ieeexplore.ieee.org/document/9554181&amp;#160;