ASSESSING THE IMPACT OF BEET WEBWORM MOTHS ON SUNFLOWER FIELDS USING MULTITEMPORAL SENTINEL-2 SATELLITE IMAGERY AND VEGETATION INDICES

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dc.authoridSaglam, Ozgur/0000-0003-1307-9267
dc.contributor.authorKara, S.
dc.contributor.authorMaden, B.
dc.contributor.authorErcan, B. S.
dc.contributor.authorSunar, F.
dc.contributor.authorAysal, T.
dc.contributor.authorSaglam, O.
dc.date.accessioned2024-10-29T17:58:15Z
dc.date.available2024-10-29T17:58:15Z
dc.date.issued2023
dc.departmentTekirdağ Namık Kemal Üniversitesi
dc.description39th International Symposium on Remote Sensing of Environment (ISRSE) - From Human needs to SDGs -- APR 24-28, 2023 -- Antalya, TURKEY
dc.description.abstractRemote sensing technology plays a crucial role in detecting and monitoring environmental issues, offering the ability to monitor large areas, diagnose problems early, and facilitate accurate interventions. By integrating in-situ data with qualitative measurements obtained from satellite images, comprehensive insights can be obtained, and statistical inferences can be established. This study focuses on analyzing the damages caused by beet webworm moths (Loxostege sticticalis) in sunflower fields located in the Ortaca neighborhood of Tekirdag province in Thrace region, utilizing Sentinel-2 satellite images and in-situ data collected from the sunflower fields in Ortaca. The relationship between different spectral indices, such as the Enhanced Vegetation Index, Chlorophyll Index Green, and spectral transformation techniques like Tasseled Cap Greenness, derived from Sentinel-2 satellite images, and the observed damage rates in various sunflower fields' in-situ data was investigated. The results revealed a negative correlation between the variables, highlighting EVI as the most effective indicator of damage among the plant indices. Leveraging these findings, a damage map was generated using EVI, enabling visual interpretation of the damage status in other sunflower fields within the study area. These findings offer valuable insights into the impact of pests on sunflower crops, despite the accuracy evaluation results falling below the desired level, with an overall accuracy of 75% and a Kappa accuracy of 65%, attributed to the limited availability of in-situ data.
dc.identifier.doi10.5194/isprs-archives-XLVIII-M-1-2023-521-2023
dc.identifier.endpage527
dc.identifier.issn1682-1750
dc.identifier.issn2194-9034
dc.identifier.startpage521
dc.identifier.urihttps://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-521-2023
dc.identifier.urihttps://hdl.handle.net/20.500.11776/14154
dc.identifier.wosWOS:001190737300072
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherCopernicus Gesellschaft Mbh
dc.relation.ispartof39th International Symposium on Remote Sensing of Environment Isrse-39 From Human Needs To Sdgs, Vol. 48-M-1
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectSentinel-2A
dc.subjectSunflower
dc.subjectLoxostege Sticticalis
dc.subjectPest Damage
dc.subjectSpectral Indices
dc.subjectCorrelation Analysis
dc.titleASSESSING THE IMPACT OF BEET WEBWORM MOTHS ON SUNFLOWER FIELDS USING MULTITEMPORAL SENTINEL-2 SATELLITE IMAGERY AND VEGETATION INDICES
dc.typeConference Object

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