Professors Maria Antónia da Conceição Abrantes Amaral Turkman and
Kamil Feridum Turkman, from the University of Lisbon used the
INLA methodology and specifically SPDE's (using R-INLA), to do the official
risk assessment for forest fire prediction in Portugal for 2018.
New accepted paper: Lombardo, L., Bakka, H., Tanyas, H., van Westen, C., Mai, P. M., and Huser, R. (2019+), Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides, Journal of Geophysical Research-Earth Surface [PDF preprint]
New accepted paper: Castro-Camilo, D., Huser, R., and Rue, H.
Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented us
A tool developed by Håvard Rue has transformed data analysis, interpretation and communication. It has been applied broadly: from modeling the spread of infectious diseases to mapping fish stocks.
Simultaneously modeling of air pollutants and weather under extreme conditions highlights the potential for serious health risks.