Comparison of Advanced Terrestrial and Aerial Remote Sensing Methods for Above-Ground Carbon Stock Estimation—A Comparative Case Study for a Hungarian Temperate Forest

Szász, Botond and Heil, Bálint and Kovács, Gábor and Mészáros, Diána and Czimber, Kornél (2025) Comparison of Advanced Terrestrial and Aerial Remote Sensing Methods for Above-Ground Carbon Stock Estimation—A Comparative Case Study for a Hungarian Temperate Forest. REMOTE SENSING, 17 (13). ISSN 2072-4292

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Official URL: https://doi.org/10.3390/rs17132173

Abstract

The increasing pace of climate-driven changes in forest ecosystems calls for reliable remote sensing techniques for quantifying above-ground carbon storage. In this article, we compare the methodology and results of traditional field surveys, mobile laser scanning, optical drone imaging and photogrammetry, and both drone-based and light aircraft-based aerial laser scanning to determine forest stand parameters, which are suitable to estimate carbon stock. Measurements were conducted at four designated sampling points established during a large-scale project in deciduous and coniferous tree stands of the Dudles Forest, Hungary. The results of the surveys were first compared spatially and quantitatively, followed by a summary of the advantages and disadvantages of each method. The mobile laser scanner proved to be the most accurate, while optical surveying—enhanced with a new diameter measurement methodology based on detecting stem positions from the photogrammetric point cloud and measuring the diameter directly on the orthorectified images—also delivered promising results. Aerial laser scanning was the least accurate but provided coverage over large areas. Based on the results, we recommend adapting our carbon stock estimation methodology primarily to mobile laser scanning surveys combined with aerial laser scanned data.

Tudományterület / tudományág

agricultural sciences > forestry and wildlife management
engineering and technology > agricultural engineering

Faculty

Not relevant

Institution

Soproni Egyetem

Item Type: Article
SWORD Depositor: Teszt Sword
Depositing User: Csaba Horváth
Identification Number: MTMT:36255294
Date Deposited: 27 Aug 2025 07:46
Last Modified: 27 Aug 2025 07:46
URI: http://publicatio.uni-sopron.hu/id/eprint/3717

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