Understanding Tree Mortality Patterns: A Comprehensive Review of Remote Sensing and Ground-based studies Article Swipe
Filippos Eliades
,
Dimitrios Sarris
,
Felix Bachofer
,
Silas Michaelides
,
Diofantos Hadjimitsis
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202407.0269.v1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202407.0269.v1
Land degradation, desertification and tree mortality related to global climate change are in the spotlight of Remote Sensing research in recent decades, since extreme climat-ic events could affect the composition, structure and biogeography of forests. Howev-er, the complexity of tree mortality processes requires a holistic approach. Herein, we present the first global assessment and a historical perspective of tree mortality by re-viewing both Remote Sensing and ground-based studies. We compiled 254 papers on tree mortality that make use of remotely sensed products, ground-based monitoring and climatic drivers, focusing on their spatial and temporal patterns, in the methods applied, while highlighting research gaps. Forested ecosystems, especially in the Medi-terranean area, appear to have experienced often climatic-induced physiological stress under extreme droughts and warming, raising concern that forests may become in-creasingly vulnerable to tree mortality. Our core results indicated that international publications on tree mortality are on the increase with the main hotspots being North America (39%) and Europe (26%). Wetness indicators appear as the barometer in ex-plaining tree mortality on a local scale, while vegetation indicators derived from mul-tispectral optical sensors are promising for large scale assessment. We observed that almost all of the studies we have reviewed were based on less than 25 years of data and were of local scale. Longer timeframes and regional scale investigations that will include multiple tree species analysis could have a significant impact on future re-search.
Related Topics
Concepts
Climate change
Scale (ratio)
Geography
Vegetation (pathology)
Tree (set theory)
Environmental resource management
Global change
Spatial ecology
Physical geography
Desertification
Global warming
Elevation (ballistics)
Remote sensing
Environmental science
Ecology
Cartography
Biology
Medicine
Mathematical analysis
Geometry
Pathology
Mathematics
Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.20944/preprints202407.0269.v1
- https://www.preprints.org/manuscript/202407.0269/v1/download
- OA Status
- green
- Cited By
- 2
- References
- 100
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400304878
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4400304878Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.20944/preprints202407.0269.v1Digital Object Identifier
- Title
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Understanding Tree Mortality Patterns: A Comprehensive Review of Remote Sensing and Ground-based studiesWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-03Full publication date if available
- Authors
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Filippos Eliades, Dimitrios Sarris, Felix Bachofer, Silas Michaelides, Diofantos HadjimitsisList of authors in order
- Landing page
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https://doi.org/10.20944/preprints202407.0269.v1Publisher landing page
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https://www.preprints.org/manuscript/202407.0269/v1/downloadDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.preprints.org/manuscript/202407.0269/v1/downloadDirect OA link when available
- Concepts
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Climate change, Scale (ratio), Geography, Vegetation (pathology), Tree (set theory), Environmental resource management, Global change, Spatial ecology, Physical geography, Desertification, Global warming, Elevation (ballistics), Remote sensing, Environmental science, Ecology, Cartography, Biology, Medicine, Mathematical analysis, Geometry, Pathology, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2025: 1, 2024: 1Per-year citation counts (last 5 years)
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100Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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