A meta-modeling approach for spatio-temporal uncertainty and sensitivity analysis: an application for a cellular automata-based Urban growth and land-use change model

作者: Seda Şalap-Ayça , Piotr Jankowski , Keith C Clarke , Phaedon C Kyriakidis , Atsushi Nara

DOI: 10.1080/13658816.2017.1406944

关键词:

摘要: The paper presents a computationally efficient meta-modeling approach to spatially explicit uncertainty and sensitivity analysis in cellular automata (CA) urban growth land-use simulation model. of the model parameters are approximated using method called polynomial chaos expansion (PCE). parameter measures obtained with PCE compared traditional Monte Carlo results. was found reduce number simulations necessary arrive at stable estimates. quality results is comparable full-order modeling approach, which costly. study shows that can significantly computational effort carrying out application spatio-temporal models.

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