Advanced remote sensing technologies, such as light detection and ranging (LiDAR), offer significant potential to mapping the alpine treeline ecotone (ATE) based on its actual definition (tree height ≥ 3 m) and contribute to the generation of baseline data for future change detection investigations. We propose an approach for combining LiDAR-derived absolute tree height data with elevation data to delineate the ATE in Uttarakhand, India. The approach was implemented using observations from the recently launched Global Ecosystem Dynamics Investigation system and validated with field measurements. The LiDAR-derived treeline was compared with the traditional normalized difference vegetation index (NDVI) treeline. The treeline derived from LiDAR was found to have root mean square error of ∼60 m with respect to the ground verified treeline location. The NDVI treeline was overestimated in comparison to the LiDAR treeline by an average surface distance of 290, 232, 257, and 237 m in the south, north, west, and east aspects, respectively. It is observed that the overestimation was higher at the lowest and highest elevation zones. We prove that LiDAR-based treeline mapping is an efficient method to delineate alpine treelines at a landscape scale.