Planet Labs have recently launched a large constellation of small satellites (3U cubesats) capable of imaging the whole Earth landmass everyday. These small satellites capture multiple images of an area on consecutive days or sometimes on the same day with a spatial resolution of 3–4 m. Planet Labs endeavors to operate the constellation in a nadir pointing mode, however, the view angle of these satellites currently varies within a few degrees from the nadir leading to varying B/H ratio for overlapping image pairs. Due to relatively small scene footprint and small off-nadir angle, the baseline to height ratio (B/H) of the overlapping PlanetScope images is often less than 1:10, which is not ideal for 3D reconstruction. Therefore, this paper explores the potential of Digital Elevation Model generation from this multi-date, multi-satellite PlanetScope imagery. The DEM generation from multiple PlanetScope images is achieved using a volumetric stereo reconstruction technique, which applies semi global matching in georeferenced object space. The results are evaluated using a LiDAR based DEM (5 m) over Mount Teide (3718 m) in Canary Islands and the ALOS (30 m) DEM on rugged terrain of the Nanga Parbat massif (8126 m) in the western Himalaya range. The proposed methodology is then applied on images from two PlanetScope satellites overpasses within a couple of minutes difference to compute the DEM of the Khurdopin glacier in the Karakoram range, known for its recent surge. The quantitative assessment of the generated elevation models is done by comparing statistics of the elevation differences between the reference LiDAR and ALOS DEM and the PlanetScope DEM. The Normalized Median of Absolute Deviation (NMAD) of the elevation differences between the computed PlanetScope DEM and LiDAR DEM is 4.1 m and the elevation differences for the ALOS DEM over stable terrain is 3.9 m. The results show that PlanetScope imagery can lead to sufficient quality DEM even with a small baseline to height ratio. Therefore, the daily PlanetScope imagery is a valuable data source and the DEM generated from this imagery can potentially be employed in numerous applications requiring multi temporal DEMs.
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