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Article: Exploring the performance of spatio-temporal assimilation in an urban cellular automata model

TitleExploring the performance of spatio-temporal assimilation in an urban cellular automata model
Authors
Keywordsassimilation window length
block size
EnKF
Logistic-CA
sensitivity analysis
Issue Date2017
Citation
International Journal of Geographical Information Science, 2017, v. 31, n. 11, p. 2195-2215 How to Cite?
AbstractUrban 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.
Persistent Identifierhttp://hdl.handle.net/10722/329454
ISSN
2023 Impact Factor: 4.3
2023 SCImago Journal Rankings: 1.436
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Xuecao-
dc.contributor.authorLu, Hui-
dc.contributor.authorZhou, Yuyu-
dc.contributor.authorHu, Tengyun-
dc.contributor.authorLiang, Lu-
dc.contributor.authorLiu, Xiaoping-
dc.contributor.authorHu, Guohua-
dc.contributor.authorYu, Le-
dc.date.accessioned2023-08-09T03:32:54Z-
dc.date.available2023-08-09T03:32:54Z-
dc.date.issued2017-
dc.identifier.citationInternational Journal of Geographical Information Science, 2017, v. 31, n. 11, p. 2195-2215-
dc.identifier.issn1365-8816-
dc.identifier.urihttp://hdl.handle.net/10722/329454-
dc.description.abstractUrban 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.-
dc.languageeng-
dc.relation.ispartofInternational Journal of Geographical Information Science-
dc.subjectassimilation window length-
dc.subjectblock size-
dc.subjectEnKF-
dc.subjectLogistic-CA-
dc.subjectsensitivity analysis-
dc.titleExploring the performance of spatio-temporal assimilation in an urban cellular automata model-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/13658816.2017.1357821-
dc.identifier.scopuseid_2-s2.0-85026273652-
dc.identifier.volume31-
dc.identifier.issue11-
dc.identifier.spage2195-
dc.identifier.epage2215-
dc.identifier.eissn1362-3087-
dc.identifier.isiWOS:000408205100004-

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