With an escalating skiing tourism industry where tourists are getting bolder every year in theirsearch for untouched snow, avalanche prediction gets more and more important. Avalancheprediction is often designated manual labour and many years of establishing avalanchedatabases. With GIS and high resolution DEM data it is possible to identify areas withavalanche danger over large areas at low costs. Using parameters as: roughness, inclination,curvature and vegetation models like the ones tested in this study can predict potential releaseareas (PRA). The results that the models present needs to be validated. This can be done eitherby manual labour by avalanche experts or by comparing the results at a validated resolutionfrom another area with avalanche databases. The present study is testing two PRA identifyingmodels on different DEM resolutions trying to identify if higher resolutions yields better resultsthan lower or vice versa. The validation of the results was a challenge, because of the lack ofavalanche databases in Sweden. In this study a 5 m resolution DEM and a model set updeveloped for Davos in Switzerland, was used as a as a reference model. The results showsthat a DEM with a high resolution of 2x2m do not identify PRAs (potential release areas) asgood as the resampled resolutions of 5x5m or 25x25m.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-126517 |
| Date | January 2016 |
| Creators | Waldenström, Björn |
| Publisher | Stockholms universitet, Institutionen för naturgeografi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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