AerialStamp: dating aerial orthophotos from visual cues and Sentinel-2 time series

Clemens Mosig , David Montero Loaiza, Miguel Mahecha, Janusch Vajna-Jehle, Teja Kattenborn

Aerial imagery from drones and airplanes is increasingly used as reference data for satellite remote sensing. Linking an orthophoto to the satellite observations of the same time requires its acquisition date. In crowd-sourced aerial archives, this reported acquisition date can be incorrect or incomplete. Yet no method exists to verify or estimate it from the data. Here, we develop AerialStamp, a method that estimates the acquisition date of an aerial orthophoto, from a drone or an aircraft, as a calibrated probability distribution over the days of the flight year. The model combines DINOv2 embeddings of 10 cm patches of the orthophoto with the Sentinel-2 time series of the site. For every week of that series, spatial correlation features describe how well the orthophoto, averaged to 10 m, correlates across pixels with the Sentinel-2 image of that week. We used 6,984 publicly available orthophotos from 129 countries in the crowd-sourced database deadtrees.earth. Spatial block cross-validation yields a median absolute error of 18.5 days (mean 30.3 days), where for 7% of orthophotos the estimated and submitted dates differed by more than 90 days. Within the dataset of crowd-sourced aerial images, at least 1.3% of the acquisition dates were detected to be wrong. A further 10.3% fall on the 1st or 15th of a month, days that are submitted about 1.6 times as often as expected by chance and therefore likely serve as placeholders. The resulting framework is available as a Python package (github.com/cmosig/aerialstamp) and is being integrated into the platform deadtrees.earth.