Modeling windthrow through remote sensing and analysis of environmental factors: Case of Bolu, Türkiye

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dc.contributor.authorCinar, Tunahan
dc.contributor.authorAydin, Abdurrahim
dc.date.accessioned2025-10-11T20:48:45Z
dc.date.available2025-10-11T20:48:45Z
dc.date.issued2025
dc.departmentDüzce Üniversitesien_US
dc.description.abstractClimate change may lead to increased or decreased future forest productivity. However, more frequent storms are expected in Europe and are increasingly considered an important abiotic damage factor for forests, leading to windthrows that result in both economic and ecological losses. Remote sensing data helps in detecting past windthrow and assessing both ecological and economic losses. In this study, carried out in Bolu Regional Forest Directorate (RFD), the windthrow areas between 2017 and 2019 were detected by using the Normalized Difference Fraction Index (NDFI) from the Sentinel-2A satellite image of Google Earth Engine Platform (GEE). The MaxEnt method was used to ascertain the relationship between windthrow damage and environmental variables. Wind speed, stand type (pure/mixed), precipitation, texture, distance to road, elevation, root types, slope (degree), and site index were used as environmental variables in the modeling. The value of the area under the curve (AUC) of the model was determined to be 0.821. According to the modeling results, the environmental variables that have the greatest impact on windthrow damage are site index and wind speed. In areas with a site index of '1' and wind speeds between 35-42 km/h and 53-65 km/h, it has been determined that there is an increased risk of windthrow. This study will enable forest managers to make ecological assessments to reduce the occurrence of windthrow. As a result of ecological assessments, it is anticipated that improvements in forest management planning will lead to a reduction in disturbances caused by windthrow.en_US
dc.description.sponsorshipDuzce University Scientific Research Projects [2022.02.02.1352]en_US
dc.description.sponsorshipThis study has been supported by Duzce University Scientific Research Projects with Project Number 2022.02.02.1352.en_US
dc.identifier.doi10.1007/s10661-025-14529-x
dc.identifier.issn0167-6369
dc.identifier.issn1573-2959
dc.identifier.issue9en_US
dc.identifier.pmid40888951en_US
dc.identifier.scopus2-s2.0-105015022451en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1007/s10661-025-14529-x
dc.identifier.urihttps://hdl.handle.net/20.500.12684/22083
dc.identifier.volume197en_US
dc.identifier.wosWOS:001564588900001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofEnvironmental Monitoringand Assessmenten_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKA_WOS_20250911
dc.subjectMaxEnten_US
dc.subjectModelingen_US
dc.subjectRemote Sensingen_US
dc.subjectWindthrowen_US
dc.subjectGoogle Earth Engineen_US
dc.titleModeling windthrow through remote sensing and analysis of environmental factors: Case of Bolu, Türkiyeen_US
dc.typeArticleen_US

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