Spatio-temporal change analysis and prediction of land use and land cover changes using CA-ANN model

dc.authoridDegermenci, Ahmet Salih/0000-0002-3866-0878en_US
dc.authorscopusid36496583300en_US
dc.contributor.authorDegermenci, Ahmet Salih
dc.date.accessioned2024-08-23T16:07:09Z
dc.date.available2024-08-23T16:07:09Z
dc.date.issued2023en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractThe spatial and temporal representation of land use and land cover (LULC) changes helps to understand the interactions between natural habitats and other areas and to plan for sustainability. Research on the models used to determine the spatio-temporal change of LULC and simulation of possible future scenarios provides a perspective for future planning and development strategies. Landsat 5 TM for 1990, Landsat 7 ETM + for 2006, and Landsat 8 OLI for 2022 satellite imageries were used to estimate spatial and temporal variations of transition potentials and future LULC simulation. Independent variables (DEM, slope, and distances to roads and buildings) and the cellular automata-artificial neural network (CA-ANN) model integrated in the MOLUSCE plugin of QGIS were used. The CA-ANN model was used to predict the LULC maps for 2038 and 2054, and the results suggest that artificial surfaces will continue to increase. The Duzce City center's artificial surfaces grew by 100% between 1990 and 2022, from 16.04 to 33.10 km2, and are projected to be 41.13 km2 and 50.32 km2 in 2038 and 2054, respectively. Artificial surfaces, which covered 20% of the study area in 1990, are estimated to cover 64.07% in 2054. If this trend continues, most of the 1st-class agricultural lands may be lost. The study's results can assist local governments in their land management strategies and aid them in planning for the future. The results suggest that policies are necessary to control the expansion of artificial surfaces, ensuring a balanced distribution of land use.en_US
dc.identifier.doi10.1007/s10661-023-11848-9
dc.identifier.issn0167-6369
dc.identifier.issn1573-2959
dc.identifier.issue10en_US
dc.identifier.pmid37725186en_US
dc.identifier.scopus2-s2.0-85171625035en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1007/s10661-023-11848-9
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14523
dc.identifier.volume195en_US
dc.identifier.wosWOS:001071557500003en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.institutionauthorDegermenci, Ahmet Salihen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofEnvironmental Monitoring and Assessmenten_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial surfacesen_US
dc.subjectCA-ANN modelen_US
dc.subjectMOLUSCEen_US
dc.subjectPredicted LULCen_US
dc.subjectDuzceen_US
dc.subjectUrban-Growthen_US
dc.subjectCellular-Automatonen_US
dc.subjectLandscape Patternen_US
dc.subjectMarkov Modelen_US
dc.subjectDynamicsen_US
dc.subjectSimulationen_US
dc.subjectExpansionen_US
dc.subjectRegionen_US
dc.subjectGisen_US
dc.titleSpatio-temporal change analysis and prediction of land use and land cover changes using CA-ANN modelen_US
dc.typeArticleen_US

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