High resolution orthophoto images from Geoeye, WorldView-2 and Pléaides processed in OrthoEngine module of PCI Geomatica. Data format: grid, UTM 33X / EGM 2008. Spatial resolution: 0.5 m (panchromatic and pansharpened) and 2 m (multispectral).

DEMs from WorldView-2 and Pléaides were extracted using the Rational Function Model (RFM). To improve images orientation, one ground control points (GCPs) was used for each stereo pair. Data format: grid (2m), UTM 33X / EGM 2008. DEMs were developed in OrthoEngine module of PCI Geomatica 2016 with the low level of detail and mountainous type of relief.

High-resolution orthomosaic derived from aerial images captured in 2020 over Hornsund, Svalbard by Dornier aircraft. The spatial resolution of the orthomosaic is 0.087 m. Aerial images for the area were provided by the SIOS through a dedicated call of proposals (https://sios-svalbard.org/AirborneRS). The dataset is the supplement to the paper: Błaszczyk, M.; Laska, M.; Sivertsen, A.; Jawak, S.D. Combined Use of Aerial Photogrammetry and Terrestrial Laser Scanning for Detecting Geomorphological Changes in Hornsund, Svalbard. Remote Sens. 2022, 14, 601. https://doi.org/10.3390/rs14030601

Digital elevation model (DEM) with high spatial resolution derived from aerial images captured in 2020 over Hornsund, Svalbard by Dornier aircraft. The spatial resolution of the orthomosaic is 0.174 m. Aerial images for the area were provided by the SIOS through a dedicated call of proposals (https://sios-svalbard.org/AirborneRS). The dataset is the supplement to the paper: Błaszczyk, M.; Laska, M.; Sivertsen, A.; Jawak, S.D. Combined Use of Aerial Photogrammetry and Terrestrial Laser Scanning for Detecting Geomorphological Changes in Hornsund, Svalbard. Remote Sens. 2022, 14, 601. https://doi.org/10.3390/rs14030601

Digital elevation model (DEM) combined from DEM derived from aerial images captured in 2020 over Hornsund, Svalbard by Dornier aircraft and from terrestrial laser scanner campaign in 2021. Both DEMs contain data gaps; therefore, they were combined to create a continuous product with the best possible accuracy and resolution. The dataset is the supplement to the paper: Błaszczyk, M.; Laska, M.; Sivertsen, A.; Jawak, S.D. Combined Use of Aerial Photogrammetry and Terrestrial Laser Scanning for Detecting Geomorphological Changes in Hornsund, Svalbard. Remote Sens. 2022, 14, 601. https://doi.org/10.3390/rs14030601

High-resolution orthomosaic derived from aerial images captured in 2020 over Hornsund, Svalbard by Dornier aircraft. The spatial resolution of the orthomosaic is 0.0843 m. Aerial images for the area were provided by the SIOS through a dedicated call of proposals (https://sios-svalbard.org/AirborneRS). The dataset is the supplement to the paper: Błaszczyk, M.; Laska, M.; Sivertsen, A.; Jawak, S.D. Combined Use of Aerial Photogrammetry and Terrestrial Laser Scanning for Detecting Geomorphological Changes in Hornsund, Svalbard. Remote Sens. 2022, 14, 601. https://doi.org/10.3390/rs14030601

Digital elevation model (DEM) with high spatial resolution derived from aerial images captured in 2020 over Hornsund, Svalbard by Dornier aircraft. The spatial resolution of the orthomosaic is 0.169 m. Aerial images for the area were provided by the SIOS through a dedicated call of proposals (https://sios-svalbard.org/AirborneRS). The dataset is the supplement to the paper: Błaszczyk, M.; Laska, M.; Sivertsen, A.; Jawak, S.D. Combined Use of Aerial Photogrammetry and Terrestrial Laser Scanning for Detecting Geomorphological Changes in Hornsund, Svalbard. Remote Sens. 2022, 14, 601. https://doi.org/10.3390/rs14030601

Point cloud collected using the Riegl VZ®-6000 long-range terrestrial laser scanner. The TLS survey was carried out on 15th August 2021. The dataset is the result of relative and absolute registration of four point clouds. The dataset is the supplement to the paper: Błaszczyk, M.; Laska, M.; Sivertsen, A.; Jawak, S.D. Combined Use of Aerial Photogrammetry and Terrestrial Laser Scanning for Detecting Geomorphological Changes in Hornsund, Svalbard. Remote Sens. 2022, 14, 601. https://doi.org/10.3390/rs14030601