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dc.contributor.authorFernandez-Carrillo, Angel
dc.contributor.authorPatočka, Zdeněk
dc.contributor.authorDobrovolný, Lumír
dc.contributor.authorFranco-Nieto, Antonio
dc.contributor.authorRevilla-Romero, Beatriz
dc.date.accessioned2022-03-16T01:02:28Z
dc.date.available2022-03-16T01:02:28Z
dc.date.issued2020
dc.identifier.issn2072-4292 Sherpa/RoMEO, JCR
dc.identifier.urihttps://repozitar.mendelu.cz/xmlui/handle/20.500.12698/1512
dc.description.abstractOver the last decades, climate change has triggered an increase in the frequency of sprucebark beetle (Ips typographusL.) in Central Europe. More than 50% of forests in the Czech Republic areseriously threatened by this pest, leading to high ecological and economic losses. The exponentialincrease of bark beetle infestation hinders the implementation of costly field campaigns to prevent andmitigate its effects. Remote sensing may help to overcome such limitations as it provides frequent andspatially continuous data on vegetation condition. Using Sentinel-2 images as main input, two modelshave been developed to test the ability of this data source to map bark beetle damage and severity.All models were based on a change detection approach, and required the generation of previous forestmask and dominant species maps. The first damage mapping model was developed for 2019 and2020, and it was based on bi-temporal regressions in spruce areas to estimate forest vitality and barkbeetle damage. A second model was developed for 2020 considering all forest area, but excludingclear-cuts and completely dead areas, in order to map only changes in stands dominated by alivetrees. The three products were validated with in situ data. All the maps showed high accuracies (acc>0.80). Accuracy was higher than 0.95 and F1-score was higher than 0.88 for areas with high severity,with omission errors under 0.09 in all cases. This confirmed the ability of all the models to detectbark beetle attack at the last phases. Areas with no damage or low severity showed more complexresults. The no damage category yielded greater commission errors and relative bias (CEs=0.30-0.42,relB=0.42-0.51). The similar results obtained for 2020 leaving out clear-cuts and dead trees provedthat the proposed methods could be used to help forest managers fight bark beetle pests. These bioticdamage products based on Sentinel-2 can be set up for any location to derive regular forest vitalitymaps and inform of early damage.en
dc.format3634
dc.publisherMDPI AG (Multidisciplinary Digital Publishing Institute-MDPI)
dc.relationEC/H2020/776045/Operational sustainable forestry with satellite-based remote sensing
dc.relation.ispartofRemote Sensing
dc.relation.urihttps://doi.org/10.3390/rs12213634
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectbark beetleen
dc.subjectIps typographus L.en
dc.subjectpesten
dc.subjectremote sensingen
dc.subjectchange detectionen
dc.subjectforest damageen
dc.subjectspruceen
dc.subjectSentinel-2en
dc.subjectdamage mappingen
dc.subjectmulti-temporal regressionen
dc.titleMonitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Dataen
dc.typeJ_ČLÁNEK
dc.date.updated2022-03-16T01:02:28Z
dc.description.versionOA
local.identifier.doi10.3390/rs12213634
local.identifier.scopus2-s2.0-85095764761
local.identifier.wos000593535700001
local.number21
local.volume12
local.identifier.obd43919913
local.identifier.e-issn2072-4292
dc.project.ID776045
dc.project.IDOperational sustainable forestry with satellite-based remote sensing
dc.identifier.orcidPatočka, Zdeněk 0000-0002-0950-7700
local.contributor.affiliationLDF
local.contributor.affiliationŠLP
local.horizonH_2020


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Zobrazit minimální záznam

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