Evidence map›Paper›PMID 41295130›Full record

ArticleJournal of imaging2025

Sentinel-2-Based Forest Health Survey of ICP Forests Level I and II Plots in Hungary.

Tamás Molnár, Bence Bolla, Orsolya Szabó, András Koltay

Abstract read
In one paragraph

Article in Journal of imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Tamás MolnárForest Research Institute, Department of Forest Ecology and Silviculture, University of Sopron, Várkerület 30/A, 9600 Sárvár, Hungary.ORCID 0000-0002-1489-0871
Bence BollaForest Research Institute, Department of Forest Ecology and Silviculture, University of Sopron, Várkerület 30/A, 9600 Sárvár, Hungary.ORCID 0000-0003-2234-0295
Orsolya SzabóForest Research Institute, Department of Plantation Forestry, University of Sopron, Farkassziget 3, 4150 Püspökladány, Hungary.ORCID 0000-0002-4688-0897
András KoltayForest Research Institute, Department of Forest Protection, University of Sopron, Hegyalja út 18, 3232 Mátrafüred, Hungary.ORCID 0000-0001-6865-2601

Funding

Ministry of Culture and Innovation of Hungary TKP2021-NKTA-43
6 · The paper itself

Abstract

Forest damage has been increasingly recorded over the past decade in both Europe and Hungary, primarily due to prolonged droughts, causing a decline in forest health. In the framework of ICP Forests, the forest damage has been monitored for decades; however, it is labour-intensive and time-consuming. Satellite-based remote sensing offers a rapid and efficient method for assessing large-scale damage events, combining the ground-based ICP Forests datasets. This study utilised cloud computing and Sentinel-2 satellite imagery to monitor forest health and detect anomalies. Standardised NDVI (Z NDVI) maps were produced for the period from 2017 to 2023 to identify disturbances in the forest. The research focused on seven active ICP Forests Level II and 78 Level I plots in Hungary. Z NDVI values were divided into five categories based on damage severity, and there was agreement between Level II field data and satellite imagery. In 2017, severe damage was caused by late frost and wind; however, the forest recovered by 2018. Another decline was observed in 2021 due to wind and in 2022 due to drought. Data from the ICP Forests Level I plots, which represent forest condition in Hungary, indicated that 80% of the monitored stands were damaged, with 30% suffering moderate damage and 15% experiencing severe damage. Z NDVI classifications aligned with the field data, showing widespread forest damage across the country.

Indexed as

defoliationforest hydrologyforest monitoringICP Forestssatellite imagery

Identifiers

PMID41295130
PMCPMC12653305

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.