<p>Mechanical microscopy allows for the imaging of mechanical properties at multiple length scales. Nanoindentation mapping is usually performed at the microstructural scale, but many manufacturing processes create property variations on larger scales. Using displacement-controlled nanoindentation mapping, multi-scale mechanical microscopy can be performed to connect large-scale variations in mechanical properties to those occurring on the microstructural scale. In this work, a nanoindentation mapping method is applied over three orders of magnitude in lateral resolution on a case-hardened medium-carbon steel. A Gaussian mixture machine-learning algorithm is employed to extract the properties of each phase as a function of length scale.</p> Graphical abstract <p></p>