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Method study: Grain size sampling and digital object oriented image analysis for explanation of snow grain size, shape and distribution
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology (INK).
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology (INK).
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology (INK).
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology (INK).
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(English)In: Journal of Glaciology, ISSN 0022-1430, E-ISSN 1727-5652Article in journal (Refereed) Submitted
Abstract [en]

We have developed a digital image processing method for snow particle size and shape analysis suitable for quick and reliable analysis in the eld. Snow particle size is an important parameter strongly aecting snow cover albedo from seasonally snow covered areas and ice sheets. It is also important in remote sensing analysis because it influences the reflectance and scattering properties of the snow. Alternatively traditional methods based on visual inspection of samples can be used but they do not yield quantitative data. Our method provides an additional alternative to both simpler and more complex methods by providinga tool that limits the subjective eect of the visual analysis and provides a quantitativeparticle 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 results from the analysis are a two dimensional analysis of particle size, shape and distributions for each sample. The developed method improves snow particle analysis being quantitative, reproducible and applicable for dierent types of eld sites.

Keyword [en]
Methods, snow, particle size, object oriented, image analysis
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
URN: urn:nbn:se:su:diva-62808OAI: oai:DiVA.org:su-62808DiVA: diva2:444904
Available from: 2011-09-30 Created: 2011-09-30 Last updated: 2017-12-08Bibliographically approved
In thesis
1. Snow particle size investigations using digital image analysis - implications for ground observations and remote sensing of snow
Open this publication in new window or tab >>Snow particle size investigations using digital image analysis - implications for ground observations and remote sensing of snow
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

During the past century climate warming has caused rapid changes in the Cryosphere. This has increased the need to accurately monitor rates of change in snow and ice in remote or sparsely populated areas where environmental observing capacity is limited. Monitoring snow cover requires understanding of the snow pack and the snow surface attributes. Snow particle size is an important parameter for characterization of snow pack properties. The size and shape of the snow particles affects the snow/air-ratio which in turn affect how energy is reflected on the snow surface. This governs the snow pack energy balance by changing the albedo or backscattering properties of the snow. Both the albedo and the snow particle size can be quantified by remote sensing. However, the snow particle size estimated by remote sensing, also called the optically equivalent particle size, represents only an approximation of the true or physical particle size of snow. Thus, there is demand for methods that relate both parameters and help to improve the interpretation of remote sensing data of snow at higher spatial and temporal scales. To address this demand the aim of this dissertation thesis is to improve existing sampling methods of the physical snow particle size to retrieve high-resolution, spatial and temporal data sets for validation of remote sensing data. A field sampling method based on object-oriented analysis of digital images was developed that allows measurements of various snow particle size parameters such as length, width, area, specific surface area and shape. The method generates a continuous snow particle size distribution that supports the detailed statistical characterization of a large number of samples. The results show its possibility to compare data from different existing methods. The sampling method was applied in field sites in Antarctica and in northern Sweden, to characterize the spatial variability in the physical snow particle size and to estimate correlations between various remote sensing products and the observed physical snow particle size. The results of the presented studies show that more detailed measurements of snow particle size in the field at higher temporal and spatial scales can improve the interpretation of active and passive satellite retrieved data.

Place, publisher, year, edition, pages
Stockholm: Department of Physical Geography and Quaternary Geology (INK), Stockholm University, 2011. 38 p.
Series
Dissertations from the Department of Physical Geography and Quaternary Geology, ISSN 1653-7211 ; 27
Keyword
snow, remote sensing, particle size, Antarctica, in-situ sampling, seasonal snow
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-62800 (URN)978-91-7447-371-1 (ISBN)
Public defence
2011-11-11, De Geersalen, Geovetenskapens hus, Svante Arrhenius väg 14, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 2: Submitted. Paper 4: Manuscript. Paper 5: Accepted. Available from: 2011-10-20 Created: 2011-09-30 Last updated: 2011-10-03Bibliographically approved

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