Detection of Heterobasidion Root Rot on Pinus brutia Ten. Using Different Vegetation Indices Generated from Sentinel-2 A Satellite Imagery

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dc.authoridBeram, Refika Ceyda/0000-0002-1203-2910en_US
dc.authoridAKYOL, Sultan/0000-0003-4440-2960en_US
dc.authoridWoodward, Stephen/0000-0002-6627-7702en_US
dc.authoridAYDIN, Abdurrahim/0000-0002-6572-3395en_US
dc.authorscopusid57205743969en_US
dc.authorscopusid57215205903en_US
dc.authorscopusid36460530900en_US
dc.authorscopusid58337765900en_US
dc.authorscopusid59215585500en_US
dc.authorscopusid14036984100en_US
dc.authorscopusid55636980800en_US
dc.contributor.authorCinar, Tunahan
dc.contributor.authorBeram, R. Ceyda
dc.contributor.authorAydin, Abdurrahim
dc.contributor.authorAkyol, Sultan
dc.contributor.authorTashigul, Nurzhan
dc.contributor.authorLehtijarvi, H. Tugba
dc.contributor.authorWoodward, Steve
dc.date.accessioned2024-08-23T16:07:03Z
dc.date.available2024-08-23T16:07:03Z
dc.date.issued2024en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractThe genus Heterobasidion includes some of the most destructive pathogens of conifers in the Northern hemisphere. Heterobasidion root rot leads to loss of root function and visible symptoms in the crowns of most Pinus spp., including Turkish red pine (P. brutia). Infected pines will eventually die. Wind-thrown trees with decayed roots or open gaps in the stand often indicate the presence of Heterobasidion root rot. Satellite imagery has recently been utilized regularly to detect damaged areas in order to apply early management procedures to pests or diseases in forests, reducing spread within an affected site and to other places. In the work described here, Sentinel-2 A satellite imagery was tested for detecting Heterobasidion root rot in P. brutia regeneration in an area in south-western Turkiye, using different vegetation indices. Normalized Difference Red Edge Index (NDRE), Normalized Difference Vegetation Index (NDVI), and Plant Senescence Reflectance Index (PSRI) indices were calculated from Sentinel-2 A satellite images in the Google Earth Engine (GEE) platform to detect disease. Calculated indices as synthetic band were added to the Sentinel-2 A satellite image on the GEE platform. Images with the added bands were classified using Random Forest (RF) before evaluation using the Kappa Coefficient and Overall Accuracy. Based on a statistical analysis, NDRE was the most useful index for detecting the disease with an overall accuracy of 89% and a Kappa Coefficient of 0.84, followed by NDVI and PSRI, respectively. After evaluation of General Accuracy and Kappa Coefficient, disease incidence in the area was determined (affected hectares), based on the indices. NDRE detected 7.21 affected hectares, NDVI 7.9 hectares and PSRI 6.49 hectares in a total of 67.8 hectares. Sentinel-2 A bands, which allow the measurement of various land and vegetation health parameters, the effect of bands on RF classification was determined according to the indices used. The most important band for classification of NDRE and NDVI was the B2 (BLUE) band of Sentinel-2 A, and the most important band with PSRI was the B5 (RED EDGE) band. Based on these bands, the best wavelengths for detecting H. annosum diseased areas were in the range 492.4-740.5 nm in Sentinel-2 A. The system enabled the detection of differences in crown deterioration and also wind-thrown trees with decayed roots or open gaps in the stand. This study is the first to show that Sentinel-2 A satellite imagery can be applied successfully for the detection of Heterobasidion root rot on P. brutia.en_US
dc.identifier.doi10.1007/s12524-024-01914-1
dc.identifier.endpage1817en_US
dc.identifier.issn0255-660X
dc.identifier.issn0974-3006
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-85198392530en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1805en_US
dc.identifier.urihttps://doi.org/10.1007/s12524-024-01914-1
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14457
dc.identifier.volume52en_US
dc.identifier.wosWOS:001252365900002en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofJournal of the Indian Society of Remote Sensingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRemote sensingen_US
dc.subjectSentinel-2Aen_US
dc.subjectHeterobasidion root roten_US
dc.subjectDecay fungien_US
dc.subjectForest stand managementen_US
dc.subjectPowdery Mildewen_US
dc.subjectWinter-Wheaten_US
dc.subjectAnnosumen_US
dc.subjectInfectionen_US
dc.subjectAccuracyen_US
dc.subjectDiseaseen_US
dc.subjectForestsen_US
dc.subjectModelen_US
dc.subjectBanden_US
dc.titleDetection of Heterobasidion Root Rot on Pinus brutia Ten. Using Different Vegetation Indices Generated from Sentinel-2 A Satellite Imageryen_US
dc.typeArticleen_US

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