Climate change is impacting polar regions at an accelerated rate, causing rapid changes in land cover and biodiversity. One case is the “greening up” of the Western Antarctic Peninsula (WAP), the result of receding glacial fronts exposing substrate for plants and soil development, together with higher temperatures and potential increases in cloud-free conditions conducive to plant growth. The 2019/2020 austral summer was the warmest on record for the WAP, yet the controls on land surface temperature (LST) here are not well understood. We investigated the relationships between land cover type, solar radiation, and LST for several vegetated coastal outcrops (0.3 to 0.5 ha) distributed from 64 to 65°S along the WAP. Remote sensing data was collected in February/March 2020 using a consumer-grade unmanned aerial vehicle (UAV), additionally equipped with near-IR and thermal-IR sensors. Digital surface models produced from the UAV imagery were used to calculate surface solar radiation. NDVI was used to identify four land cover classes: healthy vegetation, unhealthy vegetation, loose substrate, bedrock. Thermal-IR data provided sub-decimeter LST mapping. LST ranges varied depending on atmospheric conditions. A site surveyed under cloud-free conditions and air temperature of 6.6°C showed a 37.2°C range in LST, while a nearby site surveyed the next day under overcast conditions and air temperature of 2°C showed a 10.4°C range in LST. Vegetation at these two sites reached maximum temperatures of 27°C and 11.6°C, respectively. We found little within-site difference in either mean or range of LST among the land cover classes. Using linear regression, solar radiation explained less than 50% of the observed LST. Healthy vegetation showed the strongest relationship between solar radiation and LST. It was determined that LST in the WAP was strongly affected by factors other than solar radiation, implying latent heat effects. As the abundance of healthy vegetation increases in these areas, LST may show a stronger relationship with solar radiation, thus effecting local feedbacks to warming. This study presents the first application of UAV-derived thermal-IR data for the analysis of LST controls in Antarctica, highlighting the capability of UAV as a data collection platform for use in remote and relatively data-poor environments.