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Integrating process-based vegetation modelling with high-resolution imagery to assess bark beetle infestation and land surface temperature effects on forest net primary productivity

Abdullah, Haidi ; Neinavaz, Elnaz; Darvishzadeh, Roshanak; Huesca, Margarita; Skidmore, Andrew K.; Lindeskog, Mats; Smith, Benjamin; Heurich, Marco; Steinbrecher, Rainer 1; Paganini, Marc
1 Institut für Meteorologie und Klimaforschung (IMK), Karlsruher Institut für Technologie (KIT)

Abstract:

The European spruce bark beetle (Ips typographus) is an insect species that causes significant damage to Norway spruce (Picea abies) forests across Europe. Infestation by bark beetles can profoundly impact forest ecosystems, affecting their structure and composition and affecting the carbon cycle and biodiversity, including a decrease in net primary productivity (NPP), a key indicator of forest health. The primary objective of this study is to enhance our understanding of the interplay among NPP, bark beetle infestation, land surface temperature (LST), and soil moisture content as key components influencing the effects of climate change-related events (e.g., drought) during and after a drought event in the Bavarian Forest National Park in southeastern Germany. Earth observation data, specifically Landsat-8 TIR and Sentinel-2, were used to retrieve LST and leaf area index (LAI), respectively. Furthermore, for the first time, we incorporated a time series of high-resolution (20 m) LAI as a remote sensing biodiversity product into a process-based ecological model (LPJ-GUESS) to accurately generate high-resolution (20 m) NPP products. The study found a gradual decline in NPP values over time due to drought, increased LST, low precipitation, and a high rate of bark beetle infestation. ... mehr

Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 31.01.2025
Sprache Englisch
Identifikator ISSN: 2352-9385
KITopen-ID: 1000180349
Erschienen in Remote Sensing Applications: Society and Environment
Verlag Elsevier
Band 37
Seiten Art.-Nr.: 101499
Nachgewiesen in Scopus
OpenAlex
Dimensions

Verlagsausgabe §
DOI: 10.5445/IR/1000180349
Veröffentlicht am 24.03.2025
Seitenaufrufe: 7
seit 25.03.2025
Downloads: 6
seit 02.04.2025
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