Boike, Julia; Veh, Georg; Stoof, Günter; Sachs, Torsten; Busse, Henning; Muster, Sina (2015): Near-infrared orthomosaic of Samoylov Island, Siberia, summer 2014 (854 MB) [dataset]. Alfred Wegener Institute - Research Unit Potsdam, PANGAEA, https://doi.org/10.1594/PANGAEA.845723

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.

On August 08, 2014, high-resolution aerial images were acquired during a helicopter flight using a Nikon D200 in the near infra-red (NIR) range. The internal IR-filter was removed from the camera in a laboratory (LPD LLC, USA). The camera was fitted with a Schneider Kreuznach B+W IR-filter 093 to acquire images in the NIR range, above about 830 nm. Flight distances from the island's surface ranged from c. 400 m to c. 1700 m.

In total, 212 images (Appendix A) were used for stereo photogrammetric processing using Agisoft Photoscan (V 1.1.6). The decisive criteria for image selection were the absence of clouds and the image sharpness. Hence, no pictures from the southeastern and southwestern part of the island met these criteria.

Camera positions for raw image alignment were estimated by the software due to the lack of an internal GPS log. In addition, no measured Ground Control Points (GCPs) were available to support georeferencing of the images. As a solution, an evenly distributed network of 91 "Virtual Ground Control Points (Appendix B) was pegged out across the whole island based on the Orthomosaic Samoylov from the year 2007 (Boike et al., 2012). The same virtual GCPs were already used for georeferencing the VIS and NIR orthomosaics from the year 2008 (Boike et al. 2015). 56 of these points (excluding Point 2, 5, 7, 11, 16, 28, 30, 31, 33, 36, 37, 39, 42-44, 46, 48, 51, 52, 56, 60, 61, 63, 67, 69-71, 73-75, 77, 78, 82, 83, 89) could be detected in the NIR images of 2014. The coordinates of the GCPs (WGS 1984, UTM Zone 52N) were imported into Photoscan and placed in each image. Thus, the previous raw camera alignment could be optimized with an overall spatial error of 1.24 m and a pixel error of 1.44.

A mesh was built from the sparse point cloud and exported as Geotiff with a planimetric resolution of 0.18 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.

Slight differences compared to the Orthomosaic Samoylov 2007 (Boike et al., 2012) occur especially at the southeastern edges of the near infra-red orthomosaic. Here, only few overlapping images exist for building the mosaic. The other parts of the mosaic show a very good agreement with the reference mosaic. Geomorphological units, i.e. the polygonal tundra, as well as major waterbodies are clearly detectable.

Image meta data:

Image format: 1 NIR band

Data value range: 0-190

Coordinate system: WGS 1984 UTM Zone 52N

WKID: 32652 Authority: EPSG

Resolution: 0.18 m

Image extent: Top: 8034451.06777856

Left: 413787.139735231

Right: 416455.639735231

Bottom: 8031572.68777856

Pixel type &depth: 16 bit unsigned integer

NoData value: 256

File size: 452 MB (uncompressed)

Appendices:

App. A: Images used for stereophotogrammetric processing in Agisoft Photoscan

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