Spatio-temporal analysis of the avalanche hazard in the North of Italy
DOI:
https://doi.org/10.6092/issn.1973-2201/3990Keywords:
snow avalanche events, spatial point process, conditional intensity, space-time pattern, hazard mapAbstract
The study of avalanche events is particularly important to assess and predict the degree of risk involved in a given area and time. In this work we consider an alternative methodology based on a space-time point process where the intensity function indicates the limiting expected rate of occurrence of snow avalanches occurring on day t at location (x, y), conditioned on the historical information available prior to time t . The model depends also on some environmental variables (degree of slope, exposure, altitude, etc.) which may be considered as covariates. In order to show the spatio temporalmodeling of the avalanche hazardwe consider the application to the digitalized Avalanche Database of the Trentino region, Italy.
References
C. ANCEY (2001). Snow avalanches. In N. BALMFORTH, A. PROVENZALE (eds.), Lecture Notes in Physics, Springer-Verlag, Berlin Heidelberg, Toronto, pp. 319–338.
S. BAGGI, J. SCHWEIZER (2009). Characteristics of wet-snow avalanche activity: 20 years of observations from a high alpine valley (dischma, switzerland). Natural Hazards, 50, pp. 97–108.
D. R. BRILLINGER, H. K. PREISLER, J.W. BENOIT (2006). Probabilistic risk assessment for wildfires. Environmetrics, 17, pp. 623–633.
A. BRIX, P. J. DIGGLE (2001). Spatio-temporal prediction for log-gaussian cox processes. Journal of the Royal Statistical Society: Series B, 63, no. 4, pp. 823–841.
N. CRESSIE (1993). Statistics for Spatial Data. JohnWiley & Sons, New York.
D. DALEY, D. VERE-JONES (1998). An Introduction to the Theory of Point Processes. Springer, New York.
N. ECKERT, E. PARENT, , R. KIES, , H. BAYA (2010). A spatio-temporal modeling framework for assessing the fluctuations of avalanche occurrence resulting from climate change: application to 60 years of data in the northern french alps. Climatic Change, 101, pp. 515–553.
N. ECKERT, E. PARENT, M. NAAIM, D. RICHARD (2008). Bayesian stochastic modeling for avalanche predetermination: froma general systemframework to return period computations. Stoch. Env. Res. Risk. Ass., 22, pp. 185–206.
V. JOMELLI, D.G. C. DELVAL, S. ESCANDED, D. BRUNSTEIN, B.HETU, , L. FILION, P. PECH (2007). Probabilistic analysis of recent snow avalanche activity and climate in the french alps. Cold Regions Science and Technology, 47, pp. 180–192.
V. JOMELLI, P. PECH (2004). Effects of the little ice age on avalanche boulder tongues in the french alps (massif des ecrins). Earth Surface Processes and Landforms, 29, pp. 553–564.
M.MEUNIER, C. ANCEY (2004). Towards a conceptual approach to predetermining longreturn- period avalanche run-out distances. Journal of Glaciology, 50, pp. 268–278.
Y. OGATA (1998). Space-time point-process models for earthquake occurrences. Annals of the Institute for Statistical Mathematics, 50, pp. 379–402.
R. D. PENG, F. P. SCHOENBERG, J. WOODS (2005). A space-time conditional intensity model for evaluating a wildfire hazard index. Journal of the American Statistical Association, 100, no. 469, pp. 25–35.
F. SCHOENBERG, C. CHANG, J. KEELEY, J. POMPA, J. WOODS, H. XU (2007). A critical assessment of the burning index in los angeles county, california. International Journal ofWildland Fire, 16, pp. 473–483.
D. STRAUB, A. GRAY-REGAMEY (2006). A bayesian probabilistic framework for avalanche modelling based on observations. Cold Regions Science and Technology, 46, pp. 192–203.
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