Snowpit near-infrared (NIR) images collected during the MOSAiC expedition

DOI

A NIR camera allows a measurement of the reflectance of the snow profile wall to identify layers of snow grains with different specific surface area (SSA) with a spatial resolution of about 1 mm. The processing of the images of RGB-cameras must consider the sensitivity of the different color pixels. The setup of the reference targets, the flat surface and the diffuse illumination is important to get high-quality images. A geometrically corrected NIR-photo gives an objective measure of the snow stratigraphy and is observer independent. This efficient measurement has been adapted for use in polar night and day by blocking out external sunlight and packaging the camera and the illuminating infrared lights into a wooden box. The width and height of the inside of the box was 500 x 675 mm. A blanket was used to prevent any light seeping through. Inside the box, lambertian reflectance targets were mounted to account for any irregular light conditions. For MOSAiC, we used lights with two different wavelengths, 850 nm and 940 nm. We used the NIR camera in excavated snowpit walls to record the vertical and horizontal spatial variability of the SSA and snow stratigraphy. If the snowpit was higher than the NIR box, then measurement was repeated for different heights, using a ruler as a reference. NIR was also used to take images of the surface to account for small-scale spatial variability of the SSA of the snow/SSL surface. For each set of images, a dark image (without any lamps, recorded in this dataset as 0 nm) was taken, followed by images with each of the two lamps (using external light switches), to account for potential light leaks. The MAPIR camera (Survey3N Camera - Near Infrared (NIR) - MAPIR CAMERA) was built into the box and triggered by an external button. Please direct inquiries to; David Wagner (PS122/1), Martin Schneebeli (PS122/2), Amy Macfarlane (PS122/3 and PS122/4), Ruzica Dadic (PS122/5).

Identifier
DOI https://doi.org/10.1594/PANGAEA.940129
Related Identifier https://doi.org/10.1594/PANGAEA.935934
Metadata Access https://ws.pangaea.de/oai/provider?verb=GetRecord&metadataPrefix=datacite4&identifier=oai:pangaea.de:doi:10.1594/PANGAEA.940129
Provenance
Creator Macfarlane, Amy R; Schneebeli, Martin; Dadic, Ruzica; Wagner, David N; Arndt, Stefanie; Clemens-Sewall, David; Hämmerle, Stefan; Hannula, Henna-Reetta; Jaggi, Matthias; Kolabutin, Nikolai; Krampe, Daniela; Lehning, Michael; Matero, Ilkka; Nicolaus, Marcel; Oggier, Marc; Pirazzini, Roberta; Polashenski, Chris; Raphael, Ian; Regnery, Julia; Shimanchuck, Egor; Smith, Madison M; Tavri, Aikaterini
Publisher PANGAEA
Publication Year 2022
Funding Reference Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, AFMOSAiC 1_00; Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, AWI_PS122_00; Horizon 2020, 730965; Swiss Federal Institute for Forest, Snow and Landscape Research, WSL_201812N1678; Swiss National Science Foundation, 179130; Swiss Polar Institute, DIRCR 2018 003
Rights Creative Commons Attribution 4.0 International; https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Representation
Language English
Resource Type Dataset
Format text/tab-separated-values
Size 17044 data points
Discipline Earth System Research
Spatial Coverage (-2.646W, 79.115S, 128.147E, 89.153N); Arctic Ocean
Temporal Coverage Begin 2019-10-25T01:15:00Z
Temporal Coverage End 2020-09-30T09:00:00Z