Over the last few decades, mobile mapping systems (MMS) such as uncrewed aerial vehicles (UAVs) and terrestrial platforms have been demonstrated in collecting geospatial data for a wide range of applications. MMS continue to evolve due to the unprecedented developments in sensor technology and emerging application domains. Integration of image and LiDAR data acquired by these systems can provide a comprehensive 3D model of the area of interest. However, ensuring good alignment of derived products from single or multiple platforms is crucial. Although many studies have been conducted in this area, there is still a need for a comprehensive integration approach that minimizes discrepancies between imagery and LiDAR data due to inaccurate calibration parameters or trajectory artifacts. To address this issue, a tightly-coupled camera/LiDAR integration workflow denoted as Unified Multi-Sensor Advanced Triangulation (UMSAT) is proposed. UMSAT can handle point, linear, and areal features derived from imaging and ranging systems while utilizing the position and orientation information provided by the navigation unit. This paper explores the feasibility of the proposed framework in two applications – archaeological mapping and geometric documentation of transportation corridors – for improving the quality of derived data/products from imaging and ranging remote sensing systems. Experimental results demonstrate that the UMSAT framework successfully aligns multi-temporal, multi-sensor, and multi-platform geospatial data.