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dc.contributor.author
Zweifel, Roman
dc.contributor.author
Pappas, Christoforos
dc.contributor.author
Peters, Richard L.
dc.contributor.author
Babst, Flurin
dc.contributor.author
Balanzategui, Daniel
dc.contributor.author
Basler, David
dc.contributor.author
Bastos, Ana
dc.contributor.author
Beloiu Schwenke, Mirela
dc.contributor.author
Buchmann, Nina
dc.contributor.author
Bose, Arun K.
dc.contributor.author
Braun, Sabine
dc.contributor.author
Damm, Alexander
dc.contributor.author
D'Odorico, Petra
dc.contributor.author
Eitel, Jan U.H.
dc.contributor.author
Etzold, Sophia
dc.contributor.author
Fonti, Patrick
dc.contributor.author
Rouholahnejad Freund, Elham
dc.contributor.author
Gessler, Arthur
dc.contributor.author
Haeni, Matthias
dc.contributor.author
Hoch, Günter
dc.contributor.author
Rohner, Brigitte
dc.contributor.author
von Arx, Georg
dc.contributor.author
et al.
dc.date.accessioned
2023-07-26T05:41:04Z
dc.date.available
2023-03-25T04:35:15Z
dc.date.available
2023-03-29T09:50:10Z
dc.date.available
2023-07-25T13:52:08Z
dc.date.available
2023-07-26T05:41:04Z
dc.date.issued
2023-05-10
dc.identifier.issn
0048-9697
dc.identifier.issn
1879-1026
dc.identifier.other
10.1016/j.scitotenv.2023.162167
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/604949
dc.identifier.doi
10.3929/ethz-b-000604949
dc.description.abstract
Forests account for nearly 90 % of the world's terrestrial biomass in the form of carbon and they support 80 % of the global biodiversity. To understand the underlying forest dynamics, we need a long-term but also relatively high-frequency, networked monitoring system, as traditionally used in meteorology or hydrology. While there are numerous existing forest monitoring sites, particularly in temperate regions, the resulting data streams are rarely connected and do not provide information promptly, which hampers real-time assessments of forest responses to extreme climate events. The technology to build a better global forest monitoring network now exists. This white paper addresses the key structural components needed to achieve a novel meta-network. We propose to complement - rather than replace or unify - the existing heterogeneous infrastructure with standardized, quality-assured linking methods and interacting data processing centers to create an integrated forest monitoring network. These automated (research topic-dependent) linking methods in atmosphere, biosphere, and pedosphere play a key role in scaling site-specific results and processing them in a timely manner. To ensure broad participation from existing monitoring sites and to establish new sites, these linking methods must be as informative, reliable, affordable, and maintainable as possible, and should be supplemented by near real-time remote sensing data. The proposed novel meta-network will enable the detection of emergent patterns that would not be visible from isolated analyses of individual sites. In addition, the near real-time availability of data will facilitate predictions of current forest conditions (nowcasts), which are urgently needed for research and decision making in the face of rapid climate change. We call for international and interdisciplinary efforts in this direction.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Elsevier
en_US
dc.subject
Forest monitoring and observation infrastructure
en_US
dc.subject
Remote sensing
en_US
dc.subject
Ecophysiology
en_US
dc.subject
Meta-network
en_US
dc.subject
Automated, standardized linking methods
en_US
dc.subject
Nowcasting and predictions in near real-time
en_US
dc.title
Networking the forest infrastructure towards near real-time monitoring - A white paper
en_US
dc.type
Journal Article
dc.date.published
2023-02-11
ethz.journal.title
Science of The Total Environment
ethz.journal.volume
872
en_US
ethz.journal.abbreviated
Sci. Total Environ.
ethz.pages.start
162167
en_US
ethz.size
11 p.
en_US
ethz.version.deposit
acceptedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Amsterdam
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03648 - Buchmann, Nina / Buchmann, Nina
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02722 - Institut für Terrestrische Oekosysteme / Institute of Terrestrial Ecosystems::09723 - Griess, Verena C. / Griess, Verena C.
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02703 - Institut für Agrarwissenschaften / Institute of Agricultural Sciences::03648 - Buchmann, Nina / Buchmann, Nina
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science::02722 - Institut für Terrestrische Oekosysteme / Institute of Terrestrial Ecosystems::09723 - Griess, Verena C. / Griess, Verena C.
en_US
ethz.date.deposited
2023-03-25T04:35:17Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Embargoed
en_US
ethz.date.embargoend
2025-02-17
ethz.rosetta.installDate
2023-03-29T09:50:11Z
ethz.rosetta.lastUpdated
2024-02-03T02:05:32Z
ethz.rosetta.versionExported
true
ethz.COinS
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