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Synthetic RapidEye data used for the detection of area-based spruce tree mortality induced by bark beetles

Latifi, Hooman und Dahms, Thorsten und Beudert, Burkhard und Heurich, Marco und Kübert, Carina und Dech, Stefan (2018) Synthetic RapidEye data used for the detection of area-based spruce tree mortality induced by bark beetles. Giscience & Remote Sensing, 55 (6), Seiten 839-859. Taylor & Francis. doi: 10.1080/15481603.2018.1458463. ISSN 1548-1603.

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Offizielle URL: https://www.tandfonline.com/doi/full/10.1080/15481603.2018.1458463

Kurzfassung

Tree mortality caused by outbreaks of the bark beetle Ips typographus (L.) plays an important role in the natural dynamics of Norway spruce (Picea abies L.) stands, which could cause far-reaching changes in the occurrence and duration of vegetation phenology. Field-based early detection of tree disturbances is hampered by logistic, terrain, and technical shortcomings, and by the inability to continuously monitor disturbances over large areas. Despite achievements in remote mapping of bark-beetle-induced tree mortalities, early warning has been mostly unsuccessful mainly because of the lack of spectral sensitivity and discrepancies in definitions of field- and image-based disturbance classes. Here we applied a method based on inter-annual phenology of Norway spruce stands derived from synthetic multispectral data to part of the Bavarian Forest National Park in Germany. We fused temporally continuous Moderate Resolution Imaging Spectroradiometer and discrete RapidEye data using a flexible spatiotemporal data fusion method to achieve validated 8-day RapidEye-like composites of normalized difference vegetation index for 2011. We assumed that the dead trees delineated on 2012 aerial photographs were those in which bark beetle infestations were initiated in 2011. Samples were drawn with variable-sized buffering to represent the areas prone to infestations and their surroundings. We applied a conditional inference random forest to select the best image date among the entire 46 synthetic datasets to best discriminate between the core infestation patches and their surroundings from the subsequent year. Of the discrete time points identified, day 281 of the year represented the highest discrepancy between aerial image-based dead trees and their surroundings. Classification results were significantly correlated with beetle count data obtained using pheromone traps. Our method provided valuable information for management purposes and enabled wall-to-wall mapping of stands prone to infestation and its uncertainty. The results offer potential implications for rapid and cost-effective monitoring of bark beetle outbreaks using satellite data, which would be of great benefit for both management and research tasks

elib-URL des Eintrags:https://elib.dlr.de/122829/
Dokumentart:Zeitschriftenbeitrag
Titel:Synthetic RapidEye data used for the detection of area-based spruce tree mortality induced by bark beetles
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Latifi, Hoomanhooman.latifi (at) uni-wuerzburg.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Dahms, Thorstenthorsten.dahms (at) uni-wuerzburg.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Beudert, BurkhardNICHT SPEZIFIZIERTNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Heurich, MarcoMarco.Heurich (at) npv-bw.bayern.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Kübert, Carinacarina.kuebert (at) uni-wuerzburg.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Dech, StefanStefan.Dech (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:2018
Erschienen in:Giscience & Remote Sensing
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:55
DOI:10.1080/15481603.2018.1458463
Seitenbereich:Seiten 839-859
Verlag:Taylor & Francis
ISSN:1548-1603
Status:veröffentlicht
Stichwörter:conditional inference trees, forest disturbance, FSDAF, MODIS, RapidEye
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Geowissenschaftl. Fernerkundungs- und GIS-Verfahren
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum
Deutsches Fernerkundungsdatenzentrum > Leitungsbereich DFD
Hinterlegt von: Wöhrl, Monika
Hinterlegt am:12 Nov 2018 10:36
Letzte Änderung:22 Jun 2023 10:19

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