<p>Slope monitoring is a vital component of geotechnical risk management for open pit mines during operations and nearing closure. Change detection using remote sensing techniques has become part of the state of practice for collecting measurements of both stable and unstable slopes. Terrestrial laser scanning (TLS) is commonly employed for slope monitoring due to its extensive spatial coverage, dense point clouds, and high accuracy acquisitions. However, TLS range and point cloud density have been found to be vulnerable to atmospheric interference and ground conditions (e.g. ground moisture and poor reflectivity materials). In this regard, surface information obtained from TLS could be complemented with other remote sensing information to construct a complete surface model. This 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 steelmaking coal mine transitioning to closure. The site is located in a setting with intermittent fog and cloud cover, wildfire haze, and seepage within the slope face and toe. Insufficient TLS data was obtained in local areas of the slope impacted by these conditions. Notably, reduced reflectivity of the damp coal seams and talus material can result in poor acquisition along the slope face in coal-rich zones. Aerial photogrammetry was undertaken using UAV and combined with the TLS to generate a representative surface. This paper presents a methodology for registration improvement between the TLS and UAV acquisitions, and evaluation of the combined surface using concepts adopted from change detection techniques.</p>