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Snow particle size investigations using digital image analysis - implications for ground observations and remote sensing of snow
Stockholm University, Faculty of Science, Department of Physical Geography and Quaternary Geology (INK). (Glaciology)
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 [en]
snow, remote sensing, particle size, Antarctica, in-situ sampling, seasonal snow
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
URN: urn:nbn:se:su:diva-62800ISBN: 978-91-7447-371-1 (print)OAI: oai:DiVA.org:su-62800DiVA: diva2:444840
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
List of papers
1. Spatial and temporal variations in Antarctic snow particle size identified in AMSR-E 89 GHz data
Open this publication in new window or tab >>Spatial and temporal variations in Antarctic snow particle size identified in AMSR-E 89 GHz data
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Here we use in situ observations to identify spatio-temporal variations of snow particle size in 89 GHz AMSR-E passive microwave satellite imagery. We have correlated high temporal resolution data daily AMSR-E with reference to high spatial resolution Envisat ASAR images to a validation dataset of snow particle size acquired during the Japanese Swedish Antarctic Expedition (JASE) 2007/2008. We have found strong correlations between the 89 GHz AMSR-E data and two different size parameters: particle length and estimated Specific Surface Area (SSA). These correlations have been used to model the grain size variations over the entire region of interest. The daily AMSR-E data have been used to study the evolution of the snowpack over time revealing a seasonal metamorphosis of snow particles at the coast that is largely absent on the polar plateau. Furthermore, the AMSR-E data may exhibit effects from the passing of coastal weather systems on 3-6 day cycles. These effects penetrate to the polar plateau and may represent the drainage of cold air from the plateau drawn-down by passing coastal weather systems.

National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-62811 (URN)
Available from: 2011-09-30 Created: 2011-09-30 Last updated: 2011-10-03Bibliographically approved
2. Method study: Grain size sampling and digital object oriented image analysis for explanation of snow grain size, shape and distribution
Open this publication in new window or tab >>Method study: Grain size sampling and digital object oriented image analysis for explanation of snow grain size, shape and distribution
Show others...
(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
Methods, snow, particle size, object oriented, image analysis
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-62808 (URN)
Available from: 2011-09-30 Created: 2011-09-30 Last updated: 2017-12-08Bibliographically approved
3. Spatial snow grain size variability along the JASE 2007/2008 traverse route in Dronning Maud Land, Antarctica, and its relation to MOA NDSI index, MEDRIS and MODIS sattelite data
Open this publication in new window or tab >>Spatial snow grain size variability along the JASE 2007/2008 traverse route in Dronning Maud Land, Antarctica, and its relation to MOA NDSI index, MEDRIS and MODIS sattelite data
2010 (English)In: Proceedings of ESA Living Planet Symposium: 28 June - 2 July 2010, Bergen, Norway / [ed] H. Lacoste-Francis, Noordwijk: ESA (European Space Agency) , 2010Conference paper, Published paper (Other academic)
Abstract [en]

Snow grain size is an important parameter for determining albedo of the ice sheets and for calibration of optical and microwave remote sensing scattering processes. Snow grain size is a function of the local climate determined by moisture content, air and snow temperature, their gradients within the snow and firn, and wind patterns. Furthermore, it is an indicator on snow metamorphism. We have developed The Digital Grain Size Properties method (DGSP-method) using object oriented image analysis of very high resolution snow grain size images. Commonly used methods are based on visual interpretation, which is a subjective method providing only mean grain size does not retrieve size distribution within each sample.

This is a first attempt to validate satellite information by the in situ measurements from JASE (Japanese Swedish Antarctic Expedition) 2007/2008 using digital image processing. The DSGP-method is based on in-field photography of snow and pixel-based object oriented image analysis. The results show shows decreasing grain size towards the centre of Antarctica and larger grains in the coastal areas. The data used to validate is three different products based on two different types of optic satellite sensors; MERIS (Medium Resolution Imaging Spectrometer) and MODIS (Moderate Resolution Imaging Spectroradiometer).  A first validation captures a cluster relation between grain size in the coastal and at the plateau and optical satellite reflection.

Place, publisher, year, edition, pages
Noordwijk: ESA (European Space Agency), 2010
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-53791 (URN)978-92-9221-250-6 (ISBN)
Available from: 2011-01-24 Created: 2011-01-24 Last updated: 2011-10-03Bibliographically approved
4. Regional and local Snow Grain Size variations in Dronning Maud Land, Antarctica and analysis of various distribution scales
Open this publication in new window or tab >>Regional and local Snow Grain Size variations in Dronning Maud Land, Antarctica and analysis of various distribution scales
Show others...
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Understanding spatial snow particle size variations are key to help interpretation of remotely sensed data of snow cover. In the case of Antarctica, remote sensing is the only viable option to estimate the surface mass balance of the ice sheet on continental scale. We have investigated snow particle size variability along a transect from the coast onto the polar plateau in Dronning Maud Land, Antarctica, to better understand the spatial and temporal variations in surface snow properties. Two daily samples were collected during a 55 day traverse to capture the regional variability. Local variability was assessed by sampling in grids at selected locations and the particle size and shape distributions for each site was analysed through digital image analysis, which has the benefit of yielding large quantities of reproducible quantitative data without the need for advanced laboratory analysis. The results provide an understanding of the complexity of snow particle size variability at different scales and show a variability range from 0.18–3.31 mm depending on the sample type (surface, grid or pit). We can verify relationships between grain size and both elevation and distance to the coast (moisture source) but have also identified regional seasonal changes, particularly on the lower elevations of the polar plateau. Our data provide possibilities to quantitatively assess the optical properties of the surface snow for remote sensing. The details of the spatial and temporal variations observed in our data provides a basis for further studies of the complex and coupled processes affecting snow particle size and the interpretation of remote sensing of snow covered areas.

Keyword
Antarctica, particle size, snow, traverse, JASE
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-62810 (URN)
Available from: 2011-09-30 Created: 2011-09-30 Last updated: 2011-10-03Bibliographically approved
5. Comparison between digital and manual methods of snow grain size determination
Open this publication in new window or tab >>Comparison between digital and manual methods of snow grain size determination
2012 (English)In: Hydrology Research, ISSN 0029-1277, Vol. 43, no 3, 192-202 p.Article in journal (Refereed) Published
Abstract [en]

Maintaining long time series of observations of the Cryosphere is a key issue in climate research. Long observational time series involve problems due to change in methodology or observers. In order to extend time series and introduce new methods, careful comparisons must be made to ensure homogeneity in the observational data. We have compared an established method for snow grain-size observations used by the Abisko Scientific Research Station (ASRS) in northern Sweden, based on visual interpretation, with a newly developed method for Digital Snow Particle Properties (DSPP) analysis. Transition from subjective visual method into digital reproducible analysis creates less subjective and more comparable results. The ASRS method generates size classifications excluding quantitative analysis size ranges. By determining the sizes of the classified snow using the DSPP-method, actual size ranges for classified snow can be established. By performing a digital analysis of the reference samples and the snow samples classified, we can compare the ASRS classification system to existing official classification systems. The results indicate underestimation of the visual particle size in comparison to the reference samples. Our results show how to quantify the historical data set, which enables us to perform quantitative analysis on the historical data set.

Keyword
Abisko Scientific Research Station, classification, methods, particle size, snow
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-62809 (URN)10.2166/nh.2012.078 (DOI)000300635000003 ()
Available from: 2011-09-30 Created: 2011-09-30 Last updated: 2013-01-28Bibliographically approved

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