Skladan, MichalSingh, ArunimaChudá, JuliánaLieskovský, MartinMasný, MatejVýbošťok, Jozef2026-03-202026-03-2020252673-6187https://doi.org/10.3389/frsen.2025.1669081https://repo.umb.sk/handle/123456789/1351In: Frontiers in remote sensing. Lausanne : Frontiers Media S.A., 2025. ISSN 2673-6187. Vol. 6 (2025), pp. [1-14].Short-rotation plantations of fast-growing trees (FGT) offer a sustainable biomass source to mitigate climate change and boost rural energy self-sufficiency. Accurate estimation of woody above-ground biomass (AGB) is critical for efficient management and utilization of these plantations. This study evaluates modern mobile laser scanning (MLS) techniques for dry-weight AGB estimation, comparing a commercial MLS system with a low-cost prototype built on the Livox Mid-360 sensor. Research was carried out in a dense, second-rotation poplar clone plantation. Thirty-one research plots were scanned using both MLS setups, then harvested and oven-dried to obtain reference dry weights. Point clouds were processed via a voxel-based approach at four resolutions (5, 10, 15 and 20 cm) to develop regression models correlating total voxel volume with dry biomass. The low-cost prototype delivered its best performance at 5 cm voxel size (R2 = 0.84; rRMSE = 12.2%), markedly outperforming the commercial system at the same resolution (R2 = 0.68; rRMSE = 17.5%). The commercial MLS achieved its optimum at 20 cm voxels (R2 = 0.82; rRMSE = 12.9%). Predictive models were validated using 16 plots for training and 15 for testing. The prototype yielded the highest precision for dry weight prediction (R2 = 0.89; rRMSE = 12.9%) at 5 cm resolution, while the commercial MLS excelled in fresh-weight estimation at 15 cm resolution (R2 = 0.92; rRMSE = 12.0%). These results demonstrate that affordable MLS solutions can provide biomass estimates comparable to those of higher-cost systems for dry AGB assessment in high-density poplar stands. Implementing low-cost laser scanning improves monitoring frequency, reduces operational expenses, and enables large-scale application in short-rotation forestry. This approach supports evidence-based decision-making for sustainable bioenergy production. Future work will explore integrating multispectral data and automated processing pipelines to further enhance biomass estimation accuracy and scalability across diverse forest conditions.enCC BY Creative Commons Attribution 4.0. Internationalinfo:eu-repo/semantics/openAccesslaserové skenovaniestromytreesbiomasabiomassArticle