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Pregled bibliografske jedinice broj: 1148644

Detecting the oak lace bug infestation in oak forests using MODIS and meteorological data


Kern, Anikó; Marjanović, Hrvoje; Csóka, György; Móricz, Norbert; Pernek, Milan; Hirka, Anikó; Matošević, Dinka; Paulin, Márton; Kovač, Goran
Detecting the oak lace bug infestation in oak forests using MODIS and meteorological data // Agricultural and Forest Meteorology, 306 (2021), 108436, 23 doi:10.1016/j.agrformet.2021.108436 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1148644 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Detecting the oak lace bug infestation in oak forests using MODIS and meteorological data

Autori
Kern, Anikó ; Marjanović, Hrvoje ; Csóka, György ; Móricz, Norbert ; Pernek, Milan ; Hirka, Anikó ; Matošević, Dinka ; Paulin, Márton ; Kovač, Goran

Izvornik
Agricultural and Forest Meteorology (0168-1923) 306 (2021); 108436, 23

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Space-borne remote sensing ; MODIS NDVI ; Invasive species ; Pest detection ; Infestation spread ; Statistical modelling

Sažetak
The oak lace bug (Corythucha arcuata, Say 1832) is a new invasive sap-sucking species in the European oak forests that was first recorded in Central Europe in 2013. It invaded the region from Southeastern Europe, spreads rapidly, and shows no signs of receding after establishment. In this study, focusing on the oak forests in the transboundary area of Hungary and Croatia, we applied two novel methods for detecting and assessing the impact of the oak lace bug (OLB) during the period 2000–2019 based on MODIS NDVI measured at 250 m spatial and 8-day temporal resolution. The first detection method is based purely on NDVI and has the potential to be used in near real-time detection. The second one, based on the residual Z-score of the NDVI models using daily meteorological and soil water content data as independent variables, aims at improved OLB damage assessment by decoupling the effects of the OLB from those caused by the environmental drivers. The presented detection methods had 61.1% to 93.8% agreement with the in situ data, with a better agreement in forests with high oak share. The overall share of the false-positive OLB detections for the strictest method of model residuals was 1.8%. The results confirmed a strong and year-to-year persistent NDVI decrease (down to -14.5% in pure oak forests) during the late summer which can be attributed to the OLB. The origin of the infestation in the study area was identified to be near a resting station on the major highway from Southeastern to Western Europe, corroborating the assumptions that the OLB spread was primarily facilitated by the transport system. The detected speed of the OLB radial spread in the first 3 years of infestation was under 6 km y-1, but since then it increased to above 50 km y-1.

Izvorni jezik
Engleski

Znanstvena područja
Geofizika, Šumarstvo



POVEZANOST RADA


Projekti:
IP-2019-04-6325 - Modeliranje šumskih zaliha i tokova ugljika te rizika prema budućim klimatskim scenarijima (MODFLUX) (Marjanović, Hrvoje, HRZZ - 2019-04) ( CroRIS)

Ustanove:
Hrvatski šumarski institut, Jastrebarsko

Profili:

Avatar Url Dinka Matošević (autor)

Avatar Url Milan Pernek (autor)

Avatar Url Hrvoje Marjanović (autor)

Poveznice na cjeloviti tekst rada:

doi www.sciencedirect.com

Citiraj ovu publikaciju:

Kern, Anikó; Marjanović, Hrvoje; Csóka, György; Móricz, Norbert; Pernek, Milan; Hirka, Anikó; Matošević, Dinka; Paulin, Márton; Kovač, Goran
Detecting the oak lace bug infestation in oak forests using MODIS and meteorological data // Agricultural and Forest Meteorology, 306 (2021), 108436, 23 doi:10.1016/j.agrformet.2021.108436 (međunarodna recenzija, članak, znanstveni)
Kern, A., Marjanović, H., Csóka, G., Móricz, N., Pernek, M., Hirka, A., Matošević, D., Paulin, M. & Kovač, G. (2021) Detecting the oak lace bug infestation in oak forests using MODIS and meteorological data. Agricultural and Forest Meteorology, 306, 108436, 23 doi:10.1016/j.agrformet.2021.108436.
@article{article, author = {Kern, Anik\'{o} and Marjanovi\'{c}, Hrvoje and Cs\'{o}ka, Gy\"{o}rgy and M\'{o}ricz, Norbert and Pernek, Milan and Hirka, Anik\'{o} and Mato\v{s}evi\'{c}, Dinka and Paulin, M\'{a}rton and Kova\v{c}, Goran}, year = {2021}, pages = {23}, DOI = {10.1016/j.agrformet.2021.108436}, chapter = {108436}, keywords = {Space-borne remote sensing, MODIS NDVI, Invasive species, Pest detection, Infestation spread, Statistical modelling}, journal = {Agricultural and Forest Meteorology}, doi = {10.1016/j.agrformet.2021.108436}, volume = {306}, issn = {0168-1923}, title = {Detecting the oak lace bug infestation in oak forests using MODIS and meteorological data}, keyword = {Space-borne remote sensing, MODIS NDVI, Invasive species, Pest detection, Infestation spread, Statistical modelling}, chapternumber = {108436} }
@article{article, author = {Kern, Anik\'{o} and Marjanovi\'{c}, Hrvoje and Cs\'{o}ka, Gy\"{o}rgy and M\'{o}ricz, Norbert and Pernek, Milan and Hirka, Anik\'{o} and Mato\v{s}evi\'{c}, Dinka and Paulin, M\'{a}rton and Kova\v{c}, Goran}, year = {2021}, pages = {23}, DOI = {10.1016/j.agrformet.2021.108436}, chapter = {108436}, keywords = {Space-borne remote sensing, MODIS NDVI, Invasive species, Pest detection, Infestation spread, Statistical modelling}, journal = {Agricultural and Forest Meteorology}, doi = {10.1016/j.agrformet.2021.108436}, volume = {306}, issn = {0168-1923}, title = {Detecting the oak lace bug infestation in oak forests using MODIS and meteorological data}, keyword = {Space-borne remote sensing, MODIS NDVI, Invasive species, Pest detection, Infestation spread, Statistical modelling}, chapternumber = {108436} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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