Estimation of the Total Carbon Stock of Dudles Forest Based on Satellite Imagery, Airborne Laser Scanning, and Field Surveys

We present our carbon stock estimation method developed for mixed coniferous and deciduous forests in the Hungarian hilly region, covering diverse site conditions. The method consists of four complex steps, integrating traditional field surveys with modern remote sensing and GIS. The first step involves comprehensive field data collection at systematically distributed sampling points. The second step is tree species mapping based on satellite image time series. The third step uses Airborne Laser Scanning to estimate aboveground biomass and derive the carbon stock of roots. The final step involves evaluating and spatially extending field and laboratory data on litter and humus from sampling points using geostatistical methods, followed by aggregating the results for the forest block and individual forest sub-compartments. New elements were developed and implemented into the complex methodology, such as aboveground biomass calculation with voxel aggregation and underground carbon stock spatial extension with EBK regression prediction. Additionally, we examined how the accuracy of our method, designed for a 200 m sampling grid, decreases as the distance between sampling points increases.

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Publication Details

Journal
Forests
Published
2025-03-14
DOI
https://doi.org/10.3390/f16030512
Citations
4
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
3.20
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article

Estimation of the Total Carbon Stock of Dudles Forest Based on Satellite Imagery, Airborne Laser Scanning, and Field Surveys

Dávid Heilig, Kornél Czimber, Bálint Heil, Gábor Veperdi et al.
4 citations
Forests
Remote Sensing and LiDAR Applications
3.20
article

Estimation of the Total Carbon Stock of Dudles Forest Based on Satellite Imagery, Airborne Laser Scanning, and Field Surveys

Dávid Heilig, Kornél Czimber, Bálint Heil, Gábor Veperdi, Diána Mészáros, Gábor Illés, Gábor Kovács, Botond Szász, Norbert Ács
article en
4 citations

Abstract

We present our carbon stock estimation method developed for mixed coniferous and deciduous forests in the Hungarian hilly region, covering diverse site conditions. The method consists of four complex steps, integrating traditional field surveys with modern remote sensing and GIS. The first step involves comprehensive field data collection at systematically distributed sampling points. The second step is tree species mapping based on satellite image time series. The third step uses Airborne Laser Scanning to estimate aboveground biomass and derive the carbon stock of roots. The final step involves evaluating and spatially extending field and laboratory data on litter and humus from sampling points using geostatistical methods, followed by aggregating the results for the forest block and individual forest sub-compartments. New elements were developed and implemented into the complex methodology, such as aboveground biomass calculation with voxel aggregation and underground carbon stock spatial extension with EBK regression prediction. Additionally, we examined how the accuracy of our method, designed for a 200 m sampling grid, decreases as the distance between sampling points increases.

ForestsVol. 16(3)
Forest Research Institute (HU), University of Sopron (HU)
Openalex Percentile: Top 10%
Remote Sensing and LiDAR Applications
3.20
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Estimation of the Total Carbon Stock of Dudles Forest Based on Satellite Imagery, Airborne Laser Scanning, and Field Surveys — Dávid Heilig, Kornél Czimber, et al. · Forests (2025) | TGRS Research Map | TGRS