Rodyti trumpą aprašą

dc.contributor.authorZarandian, Ardavan
dc.contributor.authorMohammadyari, Fatemeh
dc.contributor.authorMirsanjari, Mir Mehrdad
dc.contributor.authorSužiedelytė Visockienė, Jūratė
dc.date.accessioned2023-09-18T16:28:05Z
dc.date.available2023-09-18T16:28:05Z
dc.date.issued2023
dc.identifier.issn0167-6369
dc.identifier.other(crossref_id)143969622
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/114234
dc.description.abstractModels for land cover/land use simulation are appropriate and important tools for decision-makers, helping them build future plausible landscape scenarios. Due to the fact that the simulation results of different models may be different, it is sometimes difficult for users to choose a suitable model. Therefore, in this study, an integrated approach is used, combining the data obtained from remote sensing and GIS with Land Change Modeler (LCM) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models to simulate and predict land cover/land use changes for 2028 in Karaj metropolis (Northern Iran as a poor region—in terms of data—which is under intense and rapid urbanization. In this sense, three land cover/land use maps related to the study area were primarily generated using satellite image data for the period 2006, 2011, and 2017. They were used as a basis to define two scenarios: business-as-usual (BAU) scenario and participatory plausible scenario (PPS) for 2028. Afterwards, the necessary input data used in running of both models were prepared and, then, the outputs of the models were interpreted and compared. According to the results, while human-made coverage and low-density grasslands increased by about 74% and 12%, respectively, it was from 2006 to 2017 that agricultural lands, gardens, and high-density grasslands decreased by 42%, 34%, and 7%, respectively. According to the business-as-usual scenario, which was projected using the LCM model, the increase in human-made cover will continue by about 29% by 2028, and the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will experience decrease by about 20%, 3%, 11%, and 9%, respectively. The participatory plausible scenario for 2028, which was defined using the InVEST model, confirmed the same results, but having different quantities. Accordingly, while human-made cover will increase by about 73%, the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will decrease by about 41%, 10%, 16%, and 1%, respectively. The output quantities of InVEST scenario model seem to be closer to reality with less uncertainty, because this model estimates the quantity of demand for land and its suitability for different uses, based on the views of different stakeholders, and considers landscape development future policies and plans. In contrast, the LCM model is based solely on trend extrapolation from the past to current time and changes in the landscape structure.eng
dc.formatPDF
dc.format.extentp. 1-22
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyDimensions
dc.relation.isreferencedbyMEDLINE
dc.relation.isreferencedbyZoological Record
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://link.springer.com/content/pdf/10.1007/s10661-022-10740-2.pdf?pdf=button
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:151550898/datastreams/MAIN/content
dc.titleScenario modeling to predict changes in land use/cover using Land Change Modeler and InVEST model: a case study of Karaj Metropolis, Iran
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references61
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionResearch Center for Environment and Sustainable Development (RCESD)
dc.contributor.institutionMalayer University
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyAplinkos inžinerijos fakultetas / Faculty of Environmental Engineering
dc.subject.researchfieldT 004 - Aplinkos inžinerija / Environmental engineering
dc.subject.researchfieldT 010 - Matavimų inžinerija / Measurement engineering
dc.subject.studydirectionE04 - Matavimų inžinerija / Measurement engineering
dc.subject.studydirectionE03 - Aplinkos inžinerija / Environmental engineering
dc.subject.vgtuprioritizedfieldsSD05 - Geodezinės technologijos / Geodetic technologies
dc.subject.ltspecializationsL104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies
dc.subject.enland use/land cover
dc.subject.enurban expansion
dc.subject.enLCM
dc.subject.enInVEST
dc.subject.enscenario modeling
dc.subject.enKaraj
dcterms.sourcetitleEnvironmental monitoring and assessment
dc.description.issueiss. 2
dc.description.volumevol. 195
dc.publisher.nameSpringer
dc.publisher.cityDordrecht
dc.identifier.doi143969622
dc.identifier.doi000909838700003
dc.identifier.doi10.1007/s10661-022-10740-2
dc.identifier.elaba151550898


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