## 4 Discussion
PlanetScope's ability to provide daily high-resolution images, coupled with the use of machine learning algorithms such as kNN, allows for the rapid identification of impacted areas and the prioritization of mitigation actions. This approach can also be integrated into public management systems, enabling regulatory bodies such as the National Mining Agency (ANM) to use updated data to monitor mining activities in near real time. This integration provides a solid foundation for monitoring illegal activities, planning environmental recovery strategies, and promoting more sustainable use of mineral resources. This technical association allows for spatial and temporal validation of the obtained data, especially in areas where the 3 m spatial resolution of PlanetScope may generate uncertainties due to spectral similarities between classes, such as urban area and exposed soil. Additionally, the use of historical images from Google Earth enables a retrospective analysis of environmental transformations, enriching the understanding of spatial dynamics and providing a visual history to support strategic decisions in environmental and mining management. This integrated approach demonstrates considerable potential for future applications in continuous monitoring and environmental oversight, contributing to greater accuracy in identifying environmental impacts in mining-affected areas. Other methodological advances should focus on recognizing and distinguishing different stages of rehabilitation in mining areas (e.g., herbaceous, shrub, and forest cover) from high-resolution satellite systems and unmanned aerial vehicles to remotely track the environmental progress of revegetation areas [33]. According to [PERSON] et al. [80], environmental changes caused by human factors, such as industrialization, urbanization, economy, and technology, surpass even those caused by natural factors in intensity and have a decisive impact on short-term land cover changes in mining areas, where social and economic factors are more important. As a result, the traditional farming mode may be affected, leading to the destruction of the ecological environment. The expansion of mining activities and the associated vegetation degradation in the Serrita-Cedro Project region have caused significant environmental and socioeconomic impacts. From an environmental perspective, extensive vegetation removal has led to a loss of biodiversity and a decline in ecosystem services. This degradation has disrupted the local hydrological cycle, increasing erosion risks and reducing soil infiltration. Furthermore, waste generated by mining activities has polluted soil and water resources, compromising the quality of essential water supplies for local communities. These environmental challenges have heightened the region's ecological vulnerabilities, threatening long-term sustainability [81]. From a socioeconomic perspective, mining activities in the Serrita-Cedro Project and other areas in Brazil have provided immediate economic opportunities, such as job creation and increased local income. However, economic dependence on mining has left communities vulnerable, particularly as mines near resource depletion. Additionally, the displacement of local populations and territorial conflicts have impacted traditional communities, exacerbating social inequalities. Atmospheric pollution from mining activities has further contributed to a rise in respiratory diseases, highlighting the need for more robust strategies to mitigate these damages [82]. RS monitoring and evaluation of the effects of mining on long-term changes can provide a solid understanding to guide mine ecological restoration and local ecosystem sustainability [83], despite some limitations of this technology. However, in the future, with the development of new sensors and satellites with better resolutions, integrated with new methodological processes, RS monitoring of mining areas will become more efficient.