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Particle Size Sampling and Object-Oriented Image Analysis for Field Investigations of Snow Particle Size, Shape, and Distribution
Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi och kvartärgeologi (INK).
Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi och kvartärgeologi (INK).
Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi och kvartärgeologi (INK).
Vise andre og tillknytning
2013 (engelsk)Inngår i: Arctic, Antarctic and Alpine research, ISSN 1523-0430, E-ISSN 1938-4246, Vol. 45, nr 3, s. 330-341Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Snow particle size is an important parameter strongly affecting snow cover broadband albedo from seasonally snow covered areas and ice sheets. It is also important in remote sensing analyses because it influences the reflectance and scattering properties of the snow. We have developed a digital image processing method for the capture and analysis of data of snow particle size and shape. The method is suitable for quick and reliable data capture in the field. Traditional methods based on visual inspection of samples have been used but do not yield quantitative data. Our method provides an alternative to both simpler and more complex methods by providing a tool that limits the subjective effect of the visual analysis and provides a quantitative particle size distribution. The method involves image analysis software and field efficient instrumentation in order to develop a complete process-chain easily implemented under field conditions. The output from the analysis is a two-dimensional analysis of particle size, shape, and distributions for each sample. The results of the segmentation process were validated against manual delineation of snow particles. The developed method improves snow particle analysis because it is quantitative, reproducible, and applicable for different types of field sites.

sted, utgiver, år, opplag, sider
2013. Vol. 45, nr 3, s. 330-341
HSV kategori
Identifikatorer
URN: urn:nbn:se:su:diva-100676DOI: 10.1657/1938-4246-45.3.330ISI: 000329533200003OAI: oai:DiVA.org:su-100676DiVA, id: diva2:695461
Forskningsfinansiär
Swedish Research Council
Merknad

AuthorCount:6;

Tilgjengelig fra: 2014-02-11 Laget: 2014-02-10 Sist oppdatert: 2018-01-11bibliografisk kontrollert

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Ingvander, SusanneBrown, Ian A.Jansson, PeterHolmlund, PerRosqvist, Gunhild
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