Exploring the Potential of the Google Earth Engine (GEE) Platform for Analysing Forest Disturbance Patterns with Big Data

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dc.authorscopusid57205743969en_US
dc.authorscopusid36460530900en_US
dc.contributor.authorCinar, Tunahan
dc.contributor.authorAydin, Abdurrahim
dc.date.accessioned2024-08-23T16:03:57Z
dc.date.available2024-08-23T16:03:57Z
dc.date.issued2023en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractClimate change has led to various adverse consequences, with natural disasters being one of the most striking outcomes. Natural disasters negatively impact life, causing significant disruptions to the ecosystem. Prompt identification of affected areas and initiation of the rehabilitation process are imperative to address the disturbances in the ecosystem. Satellite imagery is employed for the rapid and cost-effective detection of damages caused by natural disasters. In this conducted study, the outputs of climate change wildfire, forest change detection, and drought analysis, have been examined, all of which worsens the impacts on the ecosystem. The analysis of drought involved using MODIS data, while Sentinel -2A satellite images were utilized to identify wildfire areas and changes in forested regions caused by windthrow. The research focused on Ganja, Azerbaijan, as the area for drought analysis. The driest June between 2005 and 2018 was assessed using the Vegetation Condition Index (VCI) in conjunction with data from the National Centers for Environmental Information (NOAA). At the Duzce Tatlidere Forest Management Directorate, the Normalized Difference Red Edge Index (NDRE) was utilized between the years 2018 and 2019 to detect the changes occurring in forested areas due to windthrow. The NDRE synthetic band was added to satellite images for the years 2018 and 2019, and a Random Forest (RF) algorithm was employed to classify the data. The classification results were evaluated using Total Accuracy and Kappa statistics. The study includes the detection of the Normalized Burn Ratio (NBR) applied to determine the extent of the wildfire that occurred in the Solquca village of the Qabala region in Azerbaijan in 2021. According to the analysis of the VCI and NOAA, June 2014 was identified as the driest month in Ganja. In the Tatlidere region, the analysis indicated that 4.22 hectares experienced reforestation, while 24 hectares experienced deforestation. The NBR analysis has revealed that similar to 1007 hectares of land were burned in the Solquca village of Qabala. The analyses conducted provide information regarding the use of satellite imagery in relation to changes in forest areas due to drought, wildfire, and windthrow.en_US
dc.identifier.doi10.15446/esrj.v27n4.110128
dc.identifier.endpage448en_US
dc.identifier.issn1794-6190
dc.identifier.issn2339-3459
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85186888276en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage437en_US
dc.identifier.urihttps://doi.org/10.15446/esrj.v27n4.110128
dc.identifier.urihttps://hdl.handle.net/20.500.12684/13993
dc.identifier.volume27en_US
dc.identifier.wosWOS:001178446200004en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherUniv Nacional De Colombiaen_US
dc.relation.ispartofEarth Sciences Research Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectDroughten_US
dc.subjectwildfireen_US
dc.subjectforest change detectionen_US
dc.subjectbig data analysisen_US
dc.subjectGoogle Earth Engineen_US
dc.subjectNoaaen_US
dc.subjectDroughten_US
dc.subjectInformationen_US
dc.subjectAccuracyen_US
dc.subjectImagesen_US
dc.subjectAreasen_US
dc.subjectIndexen_US
dc.subjectNdvien_US
dc.subjectBanden_US
dc.titleExploring the Potential of the Google Earth Engine (GEE) Platform for Analysing Forest Disturbance Patterns with Big Dataen_US
dc.typeArticleen_US

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