Earth Observation-Based Living Biomass Carbon Estimates Within European Beech Distribution Footprints in Greece

Reliable spatial evidence can support quality assurance and quality control for land use, land-use change and forestry (LULUCF), but land-cover and species-distribution layers do not by themselves identify IPCC Forest Land or species-pure stands. We estimated 2010 and 2020 above- and below-ground living biomass carbon within tree-covered European beech (Fagus sylvatica L.) distribution and occurrence footprints in Greece. Our operational hypothesis was that increasingly restrictive species masks would materially alter the mapped extent and carbon estimates. ESA Climate Change Initiative Biomass v6, ESA WorldCover 2021, European Forest Genetic Resources Programme (EUFORGEN) polygons, and Forest Information System for Europe (FISE) relative probability of presence layers were processed in Google Earth Engine. Biomass was converted with IPCC default carbon fractions and root:shoot ratios, and the results were summarized nationally and for GAUL Level-2 units. The broad EUFORGEN footprint covered 22,133 km2, whereas the Combined overlap of EUFORGEN, FISE relative probability of presence ≥ 0.50, and tree cover covered 2742 km2. Within the Combined footprint, the pixel mean living biomass carbon density was 60.33 Mg C ha−1 in 2010 and 62.50 Mg C ha−1 in 2020, and the area-integrated change was +0.58 Tg C; the area-normalized regional change was positive in 13 of 17 units and negative in 4. Across masks, the mean decadal change ranged from −0.50 to +3.37 Mg C ha−1 and the approximate area-integrated totals from −1.10 to +0.58 Tg C. These scenario-conditioned estimates are neither official national greenhouse gas inventory estimates nor tests of statistical significance; instead, they provide reproducible spatial screening while making mask sensitivity and unpropagated uncertainty explicit.

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Publication Details

Journal
Earth
Published
2026-08-24
DOI
https://doi.org/10.3390/earth7050142
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
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article

Earth Observation-Based Living Biomass Carbon Estimates Within European Beech Distribution Footprints in Greece

Elias Milios, K. Radoglou, Athanasios Stampoulidis, Nikolaos Arampatzis
Earth
Remote Sensing and LiDAR Applications
article

Earth Observation-Based Living Biomass Carbon Estimates Within European Beech Distribution Footprints in Greece

Elias Milios, K. Radoglou, Athanasios Stampoulidis, Nikolaos Arampatzis
article en

Abstract

Reliable spatial evidence can support quality assurance and quality control for land use, land-use change and forestry (LULUCF), but land-cover and species-distribution layers do not by themselves identify IPCC Forest Land or species-pure stands. We estimated 2010 and 2020 above- and below-ground living biomass carbon within tree-covered European beech (Fagus sylvatica L.) distribution and occurrence footprints in Greece. Our operational hypothesis was that increasingly restrictive species masks would materially alter the mapped extent and carbon estimates. ESA Climate Change Initiative Biomass v6, ESA WorldCover 2021, European Forest Genetic Resources Programme (EUFORGEN) polygons, and Forest Information System for Europe (FISE) relative probability of presence layers were processed in Google Earth Engine. Biomass was converted with IPCC default carbon fractions and root:shoot ratios, and the results were summarized nationally and for GAUL Level-2 units. The broad EUFORGEN footprint covered 22,133 km2, whereas the Combined overlap of EUFORGEN, FISE relative probability of presence ≥ 0.50, and tree cover covered 2742 km2. Within the Combined footprint, the pixel mean living biomass carbon density was 60.33 Mg C ha−1 in 2010 and 62.50 Mg C ha−1 in 2020, and the area-integrated change was +0.58 Tg C; the area-normalized regional change was positive in 13 of 17 units and negative in 4. Across masks, the mean decadal change ranged from −0.50 to +3.37 Mg C ha−1 and the approximate area-integrated totals from −1.10 to +0.58 Tg C. These scenario-conditioned estimates are neither official national greenhouse gas inventory estimates nor tests of statistical significance; instead, they provide reproducible spatial screening while making mask sensitivity and unpropagated uncertainty explicit.

EarthVol. 7(5)
Agricultural University of Athens (GR), Democritus University of Thrace (GR)
Life in Land
Openalex Percentile: Top 16%
Remote Sensing and LiDAR Applications
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