Quarry materials play a central role in construction and paving industries. Understanding the mechanical characteristics of rock materials is essential for selecting appropriate rock aggregates for engineering applications. However, current methods for assessing rock mechanical properties primarily rely on invasive techniques that require significant resources and often cause environmental disturbance.
This study investigates the evaluation of mechanical properties of carbonate rocks using hyperspectral remote sensing techniques. This method enables precise mapping of mineralogical components and structural features of rock crystals. Since these parameters directly influence mechanical behaviour, the underlying hypothesis is that empirical correlations can be established between the reflected light spectrum of rock surfaces and their mechanical properties.
More than 160 carbonate rock samples were collected for the study. The following mechanical properties were examined: density, porosity, uniaxial compressive strength, and water absorption. Rock fragments were scanned in a laboratory using two hyperspectral cameras operating in the 400–1000 nm and 900–1700 nm wavelength ranges. The collected data underwent advanced processing and analysis to identify empirical correlations between the hyperspectral reflectance data and laboratory-measured mechanical properties.
The findings revealed empirical relationships between hyperspectral data and key mechanical properties of carbonate rocks. Data analysis demonstrated the potential for accurately predicting mechanical characteristics using machine learning models. These preliminary results highlight the potential of remote sensing tools for effective rock property assessment.
The research introduces an innovative, non-invasive approach combining hyperspectral imaging and machine learning to assess rock mechanics. This method offers a more efficient and environmentally friendly alternative to traditional techniques by integrating mineralogical and structural mapping. The developed technology enhances evaluation processes, reduces environmental impact, and is especially suitable for areas with limited accessibility. Additionally, it contributes to the conservation of natural resources and supports improved monitoring and management practices in the mining industry.
Overall, the study contributes to scientific advancement and policy development by offering a novel technological solution for non-invasive rock evaluation. This tool provides accurate and efficient support for decision-making, with the potential to enhance natural resource management and promote environmental sustainability in Israel and beyond.