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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 |
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| Authors: | Seda Şalap-Ayça Piotr Jankowski Keith C Clarke Phaedon C Kyriakidis Atsushi Nara |
| Institution: | 1. Department of Geography, San Diego State University, San Diego, CA, USA;2. Department of Geography, University of California Santa Barbara, Santa Barbara, CA, USA;3. Institute of Geoecology and Geoinformation, Adam Mickiewicz University, Poznań, Poland;4. Department of Geography, University of California Santa Barbara, Santa Barbara, CA, USA;5. Department of Civil Engineering and Geomatics, Cyprus University of Technology, Lemesos, Cyprus |
| Abstract: | The paper presents a computationally efficient meta-modeling approach to spatially explicit uncertainty and sensitivity analysis in a cellular automata (CA) urban growth and land-use simulation model. The uncertainty and sensitivity of the model parameters are approximated using a meta-modeling method called polynomial chaos expansion (PCE). The parameter uncertainty and sensitivity measures obtained with PCE are compared with traditional Monte Carlo simulation results. The meta-modeling approach was found to reduce the number of model simulations necessary to arrive at stable sensitivity estimates. The quality of the results is comparable to the full-order modeling approach, which is computationally costly. The study shows that the meta-modeling approach can significantly reduce the computational effort of carrying out spatially explicit uncertainty and sensitivity analysis in the application of spatio-temporal models. |
| Keywords: | Land-use change urban growth sensitivity analysis meta-modeling polynomial chaos expansion |