Slope monitoring is vital for open pit mines during operations and nearing closure where pit wall instabilities are present. Change detection using terrestrial LiDAR scanning (TLS) has become part of the state of practice for collecting accurate measurements with extensive spatial coverage. The approach can detect displacements associated with global slope movement, as well as surficial occurrences such as rockfalls and sloughs. However, TLS acquisition quality is vulnerable to atmospheric interference and reflectivity of the target materials. In this regard, the high-density surface information obtained from TLS could be complemented with other, less detailed, remote sensing information in order to construct a complete surface model. Such an approach, however, requires a systematic workflow and a means to calculate surface model reliability. The subject of this study is an unstable pit wall at an open pit coal mine transitioning to closure. The site is located in the Canadian Cordillera, in a setting with intermittent fog and cloud cover, wildfire haze, and seepage within the slope face and toe. Insufficient TLS data can be obtained in local areas of the slope impacted by these conditions, as well as in shadowed areas on the benches above the TLS base elevation. Aerial photogrammetry was undertaken using UAV and combined with the TLS scan to generate a representative surface model. This paper presents a methodology for registration improvement between the TLS and UAV photogrammetry clouds, and evaluation of the combined surface using concepts of Limit of Detection (LOD) adopted from change detection techniques.