In the heart of southwest Poland, a former copper mine is undergoing a transformation, and researchers are using cutting-edge technology to understand the changes. Anna Buczyńska, a geodesy and geoinformatics expert from the Wrocław University of Science and Technology, has led a groundbreaking study that could reshape how we approach post-mining land reclamation and water management.
The study, published in the journal *Dalekosensoring* (Remote Sensing), focuses on the dynamic surface water conditions in post-mining areas. Despite successful land reclamation efforts, these areas often face secondary effects of mineral extraction, such as surface deformations and changes to surface water resources. Buczyńska and her team aimed to detect areas with statistically significant changes in surface water between 2015 and 2024 and identify the main factors influencing these changes.
The researchers integrated open remote sensing datasets from Landsat and Sentinel-1 missions to derive spectral indices like the Modified Normalized Difference Water Index (MNDWI) and the Normalized Difference Moisture Index (NDMI), as well as the Surface Soil Moisture index (SSM). They also employed spatial statistics methods, including Emerging Hot Spot analysis, and regression models like Random Forest Regression (RFR) and Geographically Weighted Regression (GWR).
“The results were quite revealing,” Buczyńska explained. “We observed a general increase in vegetation water content, a reduction in the extent of surface water, and minor soil moisture changes during the analyzed period.” The Emerging Hot Spot analysis pinpointed new hot spots, indicating regions with statistically significant increases in surface water content.
One of the most intriguing findings was that global regression models (RFR) outperformed local models (GWR), with R2 values ranging between 74.7% and 87.3% for the studied dependent variables. “The most important factors influencing these changes were the distance from groundwater wells, surface topography, vegetation conditions, and distance from active mining areas,” Buczyńska noted. “Surface geology conditions and permeability had the least importance in the regression models.”
This research offers a comprehensive framework for integrating multi-source data to support the analysis of environmental changes in post-mining regions. The implications for the energy sector are significant. Understanding surface water dynamics in post-mining areas can help energy companies manage water resources more effectively, mitigate risks, and ensure sustainable operations.
As the energy sector continues to evolve, the need for innovative solutions to environmental challenges becomes increasingly critical. Buczyńska’s work provides a valuable tool for stakeholders to make informed decisions and develop strategies that balance economic interests with environmental sustainability.
“This study is just the beginning,” Buczyńska said. “We hope our findings will inspire further research and practical applications in the field of post-mining environmental management.”
With the energy sector facing growing pressure to adopt sustainable practices, the insights from this research could shape future developments in the field. By leveraging advanced remote sensing and spatial analysis techniques, companies can better understand and manage the environmental impacts of their operations, paving the way for a more sustainable future.