The SIRIMA project aims to improve the safety and sustainability of areas affected by mining activities by addressing risks such as surface deformation due to subsidence and rising groundwater that can lead to subsidence. The project collects both field and historical data from the partner countries to more accurately predict sinkhole hazards using machine learning models.

Proper mining operations are an essential prerequisite for the safety of land use. This safety includes the health and lives of local residents as well as the conduct of business activities and the use of areas that have been damaged by mining activities. The SIRIMA project focuses on increasing knowledge and experience of the hazards in post-mining landscapes in the EU Member States, particularly in relation to uncontrolled movements of the earth's surface.

In addition to subsidence caused by mining or movements resulting from the effects of mining vibrations, these movements can also take the form of uplifts caused by the rise of the groundwater level in the rock, as well as sudden sinkholes.

The occurrence of sinkholes in urban areas of coal regions poses a real threat to buildings, technical infrastructure, roads and other utilities. They can also pose a threat to people's health and lives, but most often they cause intense anxiety and stress and indicate a lack of control by local authorities over the managed areas.

The SIRIMA project focuses on increasing knowledge and experience on the vulnerability of post-mining landscapes in the EU Member States, particularly in relation to uncontrolled surface movements.

By developing new methods for assessing the risk of uncontrolled earth movements, the project aims to provide insights into how the decommissioning of mining facilities and the subsequent changes in geological and physical parameters can influence the formation of sinkholes.