DOI: 10.1594/pangaea.845724
title: Visible and near-infrared orthomosaic of Samoylov Island, Siberia, summer 2015 (5.3 GB)

description: High-resolution land cover mapping is needed in the heterogeneous arctic landscapes that change land surface parameters over a range of a few meters. Polygonal tundra on Samoylov Island features a network of dry polygonal rims interspersed with patches of wet tundra and polygon ponds. We obtained sub-meter resolution aerial images of Samoylov Island by mounting two Nikon D200 cameras on a helium-filled balloon. Images were acquired in the visible (VIS) and near-infrared (NIR) ranges. The internal IR-filters were removed from the cameras in a laboratory (LPD LLC, USA), allowing them to capture a maximum range from about 330 to 1200 nm. A Schneider Kreuznach B+W 486 UV-IR cut filter was used for one of the cameras to obtain images in the VIS range, from about 400 to 690 nm, while the second camera was fitted with a Schneider Kreuznach B+W IR-filter 093 to acquire images in the NIR range, above about 830 nm. Flights took place on August 12, 15 and 16, 2015. Flight altitudes ranged between 100 m to about 1500 m. The post-processing steps in Agisoft Photoscan (V 1.1.6) were identical for both NIR and VIS images to generate two separate orthomosaics in the visible and the near-infrared range. In total, 505 image pairs (Appendix A) were selected for stereophotogrammetric image alignment. All images were checked manually for the absence of clouds and image sharpness. Camera positions for raw image alignment were available for the VIS images by an internal GPS log and had to be estimated by the software for the NIR images. After image alignment, all points with a reprojection error greater than 0.5 pixels were deleted from the raw point clouds. Since there were no Ground Control Points (GCPs) measured during field work, an artificial network of GCPs had to be developed. We evenly distributed 91 "Virtual Ground Control Points (Appendix B) across the whole island, using the Orthomosaic Samoylov from the year 2007 (Boike et al., 2012) as base reference. The same virtual GCPs were already used for georeferencing the VIS and NIR orthomosaics from the year 2008 (Boike et al. 2015). 57 (VIS) and 56 (NIR) GCPs could be detected in the images. The coordinates of the GCPs (WGS 1984, UTM Zone 52N) were imported into Photoscan and placed in each image. The georeferenced and optimized point cloud was filtered once again, using the same reprojection error threshold of 0.5 pixels to delete misaligned points. The overall spatial error of the placed markers for the VIS images is 0.34 m or 1.08 pix and 0.74 m or 1.31 pix for the NIR images, respectively. A mesh was built from the sparse point clouds and exported as Geotiff with a planimetric resolution of 0.07 m. See the developer's tutorial (Appendix C) to retrace the orthophoto processing chain in Agisoft Photoscan. See Appendix D for the reconstruction parameters of each GCP and the estimated position of each image. Missing image coverage is evident along the margins of the islands and in smaller patches across the island surface. Slight distortions compared to the Orthomosaic Samoylov 2007 (Boike et al., 2012) occur especially on the floodplain in the western part of the orthomosaics. Here, no GCPs could be retrieved in the newly acquired images due to the high activity of sedimentary processes. The extents and the no-data areas of the VIS and NIR mosaics vary slightly due to a small shift in the angle of view of the two mounted cameras. Appendices: App. A: Images used for stereophotogrammetric processing in Agisoft Photoscan in VIS and NIR range App. B: Virtual Ground Control Points used for image alignment in Agisoft Photoscan App. C: Tutorial (Beginner level): Orthophoto and DEM Generation with Agisoft PhotoScan Pro 1.1 (with Ground Control Points) App. D: Marker and image placement properties in Agisoft Photoscan for VIS and NIR images