Hidden forest loss: challenges in detecting wind- and insect-driven forest disturbances with global forest change landsat-based products in mixed southern boreal forests

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985939%3A_____%2F25%3A00642918" target="_blank" >RIV/67985939:_____/25:00642918 - isvavai.cz</a>

Alternative codes found

RIV/60460709:41320/25:106287 RIV/60076658:12310/25:43910512

Result on the web

<a href="https://doi.org/10.1016/j.rsase.2025.101798" target="_blank" >https://doi.org/10.1016/j.rsase.2025.101798</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.rsase.2025.101798" target="_blank" >10.1016/j.rsase.2025.101798</a>

Result language

angličtina

Original language name

Hidden forest loss: challenges in detecting wind- and insect-driven forest disturbances with global forest change landsat-based products in mixed southern boreal forests

Original language description

Wind- and insect-induced forest disturbances are becoming increasingly frequent and severe due to climate change, resulting in significant forest loss worldwide. Accurate detection of these disturbances is essential for understanding carbon storage, forest dynamics, ecosystem resilience, and for developing effective climate adaptation strategies. The Landsat-based Global Forest Change (GFC) product and the related Global Forest Watch web service are widely used for largescale forest monitoring. However, its capacity to detect disturbances caused by wind and insect outbreaks remains uncertain. In this study, we assessed the accuracy of GFC forest loss detection by comparing it with U-Net neural network forest loss masks derived from very high-resolution satellite imagery. We analyzed several study areas in natural mixed-species southern boreal forests affected by windthrows and bark beetle outbreaks, evaluating true positive (TP), false negative (FN), and false positive (FP) detection rates. Our results show that GFC substantially underestimates forest loss, with TP detection rates ranging from 1.56 % to 62.18 % and FN errors reaching 37.82 %-98.44 %. In some cases, overestimation occurred due to high FP rates up to 65.55 %. The FPs happen when a small patch of forest loss within a 30 x 30 m Landsat pixel triggers the entire pixel to be classified as forest loss, even though most of the pixel remains undisturbed. The limitation stems from the small-scale nature of windthrows and insect-induced diebacks, which cannot be reliably captured by Landsat's spatial resolution. Our findings suggest that integrating higher-resolution satellite data is crucial for accurate area estimation and improved assessments of forest loss in the face of climate-driven disturbances such as windthrows and diebacks in natural mixed-species forests. Although GFC can be unsuitable for precisely mapping forest losses, it remains a valuable, globally consistent early warning tool due to its annual updates and broad coverage. Practitioners should treat GFC detections as indicative and conduct rapid visual or automated checks with higher-resolution imagery when assessing windthrow or insect-driven mortality, especially when disturbance patches are less than 450 m2.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

40102 - Forestry

Project

<a href="/en/project/GA25-15727S" target="_blank" >GA25-15727S: Can poleward migration of tropical cyclones boost temperate forest expansion to compensate for the warming-induced decline of southern boreal forests?</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Remote Sensing Applications

ISSN

2352-9385

e-ISSN

2352-9385

Volume of the periodical

40

Issue of the periodical within the volume

Nov 2025

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

11

Pages from-to

101798

UT code for WoS article

001626171700001

EID of the result in the Scopus database

2-s2.0-105022448645