Exploring the performance of spatio-temporal assimilation in an urban cellular automata model |
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| Authors: | Xuecao Li Yuyu Zhou Tengyun Hu Lu Liang Xiaoping Liu |
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| Institution: | 1. Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China;2. Department of Geological &3. Atmospheric Sciences, Iowa State University, Ames, IA, USA;4. Department of Geological &5. Beijing Municipal Institute of City Planning and Design, Beijing, China;6. Arkansas Forest Resources Center, University of Arkansas Division of Agriculture, Monticello, AR, USA;7. School of Forestry and Natural Resources, University of Arkansas at Monticello, Monticello, AR, USA;8. School of Geography and Planning, Sun Yat-Sen University, Guangzhou, Guangdong, China |
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| Abstract: | Urban cellular automata (CA) models propagate and accumulate errors during the modeling process due to the model structure or stochastic processes involved. It is feasible to assimilate real-time observations into an urban CA model to reduce model uncertainties. However, the assimilation performance is sensitive to the spatio-temporal units in the assimilation algorithm, that is, spatial block size and window length (temporal interval). In this study, we coupled an assimilation model, an ensemble Kalman filter (EnKF) and a Logistic-CA model to simulate the urban dynamic in Beijing over a period of two decades. Our results indicate that the coupled EnKF-CA model outperforms the CA-alone counterpart by about 10% in terms of the figure of merit, which reflects the agreement of modeled pixels. We also find that the assimilation performance using a finer block (1 km) is better than that using a coarser block (5 km and 10 km) because of the better depiction of spatial heterogeneity using a finer block. Moreover, the improvement of intermediate outputs using the coupled EnKF-CA model is effective for a certain period (e.g. 5 years). This implies that a high-frequency assimilation may not significantly improve the model performance. The sensitivity analyses of spatio-temporal assimilation in the EnKF-CA model provide a better understanding of the assimilation mechanism that couples with land-use change models. |
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| Keywords: | EnKF Logistic-CA block size assimilation window length sensitivity analysis |
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