Estimating the Threshold of Detection on Tree Crown Defoliation Using Vegetation Indices from UAS Multispectral Imagery

dc.contributor.authorOtsu, Kaori
dc.contributor.authorPla, Magda
dc.contributor.authorDuane, Andrea
dc.contributor.authorCardil Forradellas, Adrián
dc.contributor.authorBrotons, Lluís
dc.date.accessioned2022-11-27T17:06:00Z
dc.date.available2022-11-27T17:06:00Z
dc.date.issued2019
dc.description.abstractPeriodical outbreaks of Thaumetopoea pityocampa feeding on pine needles may pose a threat to Mediterranean coniferous forests by causing severe tree defoliation, growth reduction, and eventually mortality. To cost–effectively monitor the temporal and spatial damages in pine–oak mixed stands using unmanned aerial systems (UASs) for multispectral imagery, we aimed at developing a simple thresholding classification tool for forest practitioners as an alternative method to complex classifiers such as Random Forest. The UAS flights were performed during winter 2017–2018 over four study areas in Catalonia, northeastern Spain. To detect defoliation and further distinguish pine species, we conducted nested histogram thresholding analyses with four UAS-derived vegetation indices (VIs) and evaluated classification accuracy. The normalized difference vegetation index (NDVI) and NDVI red edge performed the best for detecting defoliation with an overall accuracy of 95% in the total study area. For discriminating pine species, accuracy results of 93–96% were only achievable with green NDVI in the partial study area, where the Random Forest classification combined for defoliation and tree species resulted in 91–93%. Finally, we achieved to estimate the average thresholds of VIs for detecting defoliation over the total area, which may be applicable across similar Mediterranean pine stands for monitoring regional forest health on a large scale.ca_ES
dc.identifier.doihttps://doi.org/10.3390/drones3040080
dc.identifier.idgrec032709
dc.identifier.issn2504-446X
dc.identifier.urihttp://hdl.handle.net/10459.1/84378
dc.language.isoengca_ES
dc.publisherMDPIca_ES
dc.relation.isformatofReproducció del document publicat a https://doi.org/10.3390/drones3040080ca_ES
dc.relation.ispartofDrones, 2019, vol. 3, núm. 4, art. 80ca_ES
dc.rightscc-by (c) Kaori Otsu et. al., 2019ca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectUnmanned aerial systems (UAS)ca_ES
dc.subjectMultispectral imageryca_ES
dc.subjectForest defoliationca_ES
dc.subjectThaumetopoea pityocampaca_ES
dc.subjectVegetation indexca_ES
dc.subjectThresholding analysisca_ES
dc.titleEstimating the Threshold of Detection on Tree Crown Defoliation Using Vegetation Indices from UAS Multispectral Imageryca_ES
dc.typeinfo:eu-repo/semantics/articleca_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_ES
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