Measuring Carbonate Rock Strength using Spectroscopy across the Optical and Thermal Region

We seek to define new empirical relations between the spectral signature of rock surfaces and their geomechanical characteristics. By this means, proxy tools can be developed to classify the quality of rock masses in situations where access is restricted or impossible. In rock mechanics research, remote sensing technologies are mainly used for mapping surface geometry and rock discontinuities. However, the characterization of intact rock's mechanical properties via remote sensing is a technique that has not yet been developed. In this study, spectral information is implemented using optical and thermal spectral regions. This technique enables identifying and recognizing objects based on the spectral absorption features of specific chemical attributes. In general, spectral acquisition of rocks can be done using stationary or moving (airborne) platforms. Assuming the chemical and physical attributes of rocks correlate to the material physical and chemical properties we find the spectral-based model for assessing rock strength remotely. As part of a preliminary proof-of-concept stage, we collected multiple cylindrical samples of different carbonate formations from several rock outcrops in Israel. We used point and imaging hyperspectral remote sensors to measure the surfaces of the samples in the visible and infrared regions. We determined the uniaxial compressive strength of the rock samples and analyzed them, to generate a model describing the strength of the samples, solely from spectral readings at both ranges. In addition, we conducted in-situ measurements of rock strength using a Schmidt hammer and rock surface spectra in the visible region on rock outcrops. The results of this pioneering study show that the correlation between carbonated rock strength and its spectral signatures enabled the remote assessment of the carbonate rock strength and led the way to an airborne remote sensing application. We continue to extend the database and further refine the analytical method, using this to establish a solid spectral-based model to depict rock strength remotely through exploiting the hyperspectral technology from stationary and airborne platforms.