The data made available here supports two articles: 1) "Multiscale very-high resolution topographic models in Alpine ecology: pros and cons of airborne LiDAR and drone-based stereo-photogrammetry technologies" (Remote Sensing). This study is based in two valleys of the western Swiss Alps in the state of Vaud. The two study sites, Para and Martinets, are situated above the tree-line between 1800-2400m asl, with target site areas of 0.5km2. Here, we provide the base digital elevation models (DEMs) acquired via Light Detection and Ranging (LiDAR) and stereo-photogrammetry (PHOTO) methods for each site. The finest resolution for LiDAR DEMs is 0.5m and for PHOTO DEMs is 6.25cm. These were then generalised to 32m for LiDAR and 8m for PHOTO using the impyramid function in MATLAB and cropped to remove incorrect borders before being used to derive 23 variables in SAGA GIS. The site outline shape files (as zip) show the limitations of each study site, which were used to crop the DEMs and derived variables to the target site. The georef_points.csv file contains point data of geo-referenced points (±3cm accuracy) used to assess the DEM accuracies. The Aalpina_presence_points.csv file contains the point data of the Arabis alpina plant presence locations for both sites, which were used in MaxEnt analyses. 2) "An approach to integrate multiscale very high resolution environmental proxies in genotype-environment association studies" (Evolutionary Applications). This landscape genomics study includes 4 regions where Arabis alpina plants were sampled in the Swiss prealps. The 4 regions are available as .gpkg files grouped within study.areas.EPSG2056.zip file. The main dataset is the digital elevation model with a spatial resolution of 50 cm covering the whole area. It is made available as a .geotiff file (dem.05m.genescale.tif) and as a SAGA binary grid dataset, made of an ASCII header (.SGRD) and a binary data (.SDAT) file with a common basename (dem.05m.genescale.zip). The projection system for all data is CH1903+ / LV95 (EPSG2056).