Using the T-EFA method in a cellular automata-based urban growth simulation's calibration step

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dc.authorid0000-0003-0782-5366
dc.authorid0000-0001-7198-8421
dc.authorid0000-0002-1789-4448
dc.contributor.authorAyazli, Ismail Ercument
dc.contributor.authorYakup, Ahmet Emir
dc.contributor.authorBilen, Omer
dc.date.accessioned2026-02-12T21:05:19Z
dc.date.available2026-02-12T21:05:19Z
dc.date.issued2022
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractChanges in land cover driven by urban sprawl increase the threat of urbanization of forests and agricultural lands. Therefore, monitoring urban sprawl by creating simulation models is frequently carried out to understand sustainable city management. Cellular automata-based models are mostly preferred to reduce the damage led by urban sprawl, and the SLEUTH model is the most well known. Several methods have been developed for the SLEUTH model calibration step, such as optimum SLEUTH metrics and total exploratory factor analysis (T-EFA), to improve the model accuracy. This study aims to create a high-accuracy urban growth simulation model using low-resolution data, investigate the T-EFA method's success in the calibration step, and find the urban sprawl effects on land cover change. Istanbul was selected as our study area due to witnessing its tremendous urban sprawl since the 1950s. According to our results, the urban growth that occurred between 2000 and 2018 could be defined more closely to reality using the T-EFA method, and Istanbul will continue to grow until 2040, with approximately 428.7 km(2) of agricultural lands, 553.4 km(2) of forests, and 0.1 km(2) of wetlands being transformed to urban. In addition, the geologically risky areas under threat of urbanization will increase by 60% between 2018 and 2040.
dc.identifier.doi10.1111/tgis.12928
dc.identifier.endpage1484
dc.identifier.issn1361-1682
dc.identifier.issn1467-9671
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85127708873
dc.identifier.scopusqualityQ1
dc.identifier.startpage1465
dc.identifier.urihttps://doi.org/10.1111/tgis.12928
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6907
dc.identifier.volume26
dc.identifier.wosWOS:000779584200001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherWiley
dc.relation.ispartofTransactions in Gis
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260212
dc.subjectExploratory Factor-Analysis
dc.subjectSan-Francisco
dc.subjectSleuth Model
dc.subjectSprawl
dc.subjectPrediction
dc.subjectNetworks
dc.titleUsing the T-EFA method in a cellular automata-based urban growth simulation's calibration step
dc.typeArticle

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