Digital Rock Engineering is a specialized discipline that integrates computational modeling, high-resolution imaging, and geospatial analysis to characterize, simulate, and manage rock mass behavior at multiple scales. Within a GIS framework, practitioners leverage geospatial data derived from sources such as LiDAR point clouds, photogrammetric surveys, drone imagery, and borehole datasets to construct detailed 3D spatial models of rock formations, discontinuities, and subsurface structures. GIS technology enables the spatial analysis of geological features by correlating rock mechanical properties with terrain morphology, fault networks, and stratigraphic data within a unified coordinate reference system. Geospatial workflows support mapping of joint orientations, rock quality designation zones, and failure susceptibility across large engineering project footprints including tunnels, open-pit mines, slopes, and underground excavations. The practical benefits include enhanced hazard assessment accuracy, optimized site investigation planning, streamlined data integration across multidisciplinary teams, and improved decision-making throughout the project lifecycle. By embedding rock engineering parameters within GIS environments, professionals gain powerful visualization, querying, and geostatistical capabilities that transform complex subsurface data into actionable spatial intelligence.