Conference paper
Estimating Sub-Surface Snow Density Using GPR and the Surface Reflection Method
Proceedings of the Regional Conference on Permafrost 2021 and the 19th International Conference on Cold Regions Engineering, 232
Regional Conference on Permafrost 2021 and the 19th International Conference on Cold Regions Engineering (Virtual, 24-Oct-2021–29-Oct-2021)
American Society of Civil Engineers
2021
Abstract
The surface reflection method is a popular method of determining layer dielectrics in road pavements. Previous research has also applied this technique to snow to estimate surface snow density. Here, this method is extended to estimate sub-surface snow density and layer thicknesses. An air-coupled 800 MHz ground penetrating radar (GPR) antenna was used to image alpine snow, and comparison was made with an ideal reflector, a metal plate. Quantitative analysis of the GPR trace and application of the surface reflection technique allowed sub-surface snow density and surface layer thickness to be resolved. Although discrimination of second layer thickness was poor, this technique introduces a simple method by which surface and sub-surface snow layer density and thickness could be rapidly estimated over large spatial areas.
Details
- Title
- Estimating Sub-Surface Snow Density Using GPR and the Surface Reflection Method
- Authors
- Adrian McCallum (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
- Publication details
- Proceedings of the Regional Conference on Permafrost 2021 and the 19th International Conference on Cold Regions Engineering, 232; 227
- Conference details
- Regional Conference on Permafrost 2021 and the 19th International Conference on Cold Regions Engineering (Virtual, 24-Oct-2021–29-Oct-2021)
- Publisher
- American Society of Civil Engineers
- Date published
- 2021
- DOI
- 10.1061/9780784483589.021; 10.1061/9780784483589
- Organisation Unit
- Indigenous and Transcultural Research Centre; University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Cancer Research Cluster
- Language
- English
- Record Identifier
- 99585806702621
- Output Type
- Conference paper
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