Noora Tienaho, Ninni Saarinen, Tuomas Yrttimaa, Ville Kankare, Mikko Vastaranta. (2024). Quantifying fire-induced changes in ground vegetation using bitemporal terrestrial laser scanning. Silva Fennica vol. 58 no. 3 article id 23061. https://doi.org/10.14214/sf.23061

Keywords: forest fires; biomass; boreal forest; LIDAR; controlled burning; surface differencing; surface fires

Highlights: Bitemporal terrestrial laser scanning provided a means for identifying surface areas exposed to fire by utilizing a surface differencing method developed in this study; The developed method allowed for the quantification of fire-induced volumetric changes in ground vegetation at high resolution, facilitating the assessment of the impact of surface fires on forest ecosystems.

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Forest fires pose a significant threat to forest carbon storage and sinks, yet they also play a crucial role in the natural dynamics of boreal forests. Accurate quantification of biomass changes resulting from forest fires is essential for damage assessment and controlled burning evaluation. This study utilized terrestrial laser scanning (TLS) to quantify changes in ground vegetation resulting from low-intensity surface fires. TLS data were collected before and after controlled burnings at eight one-hectare test sites in Scots pine (Pinus sylvestris L.) dominated boreal forests in Finland. A surface differencing-based method was developed to identify areas exposed to fire. Validation, based on visual interpretation of 1 × 1 m surface patches (n = 320), showed a recall, precision, and F1-score of 0.9 for the accuracy of identifying burned surfaces. The developed method allowed the assessment of the magnitude of fire-induced vegetation changes within the test sites. The proportions of burned 1 × 1 m areas within the test sites varied between 51–96%. Total volumetric change in ground vegetation was on average –1200 m³ ha^-1, with burning reducing the vegetation volume by 1700 m³ ha^-1 and vegetation growth increasing it by 500 m³ ha^-1. Substantial variations in the volumetric changes within and between the test sites were detected, highlighting the complex dynamics of surface fires, and emphasizing the importance of having observations from multiple sites. This study demonstrates that bitemporal TLS measurements provide a robust means for characterizing fire-induced changes, facilitating the assessment of the impact of surface fires on forest ecosystems.

Tienaho, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland https://orcid.org/0000-0002-6574-5797 E-mail: noora.tienaho@uef.fi
Saarinen, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland https://orcid.org/0000-0003-2730-8892 E-mail: ninni.saarinen@uef.fi
Yrttimaa, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland https://orcid.org/0000-0003-2648-523X E-mail: tuomas.yrttimaa@uef.fi
Kankare, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland https://orcid.org/0000-0001-6038-1579 E-mail: ville.kankare@uef.fi
Vastaranta, School of Forest Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland https://orcid.org/0000-0001-6552-9122 E-mail: mikko.vastaranta@uef.fi

Category : Data Note

article id 24066, category Data Note

Tuomas Yrttimaa, Lauri Liikonen, Aapo Erkkilä, Mikko Vastaranta. (2025). Terrestrial laser scanning point clouds and tree attributes from 55 sample plots at the Evo test site (spring 2024). Silva Fennica vol. 59 no. 1 article id 24066. https://doi.org/10.14214/sf.24066

Keywords: boreal forest; ground-based LiDAR; LIS TreeAnalyzer; point cloud processing; Riegl VZ-400i; tree characterization; tree reconstruction

Highlights: Terrestrial laser scanning dataset from 55 sample plots (32 × 32 m) representing boreal forests of Southern Finland; Data was acquired in April–May 2024 using a Riegl VZ-400i scanner, providing multiple returns per pulse; Each point is annotated with reflectance, return properties, and tree linkage; Crown and stem diameters were derived for further analysis, advancing tree and forest research applications.

Abstract | Full text in HTML | Full text in PDF | Author Info

Terrestrial laser scanning (TLS) is an active remote sensing technique that digitizes trees and forest stands by capturing range measurements, resulting in detailed point clouds. To support the development of computational methods for tree and forest stand characterization, as well as to facilitate the exploration of tree structures, we collected TLS data from 55 sample plots (32 m × 32 m) and 6320 trees in Evo, Southern Finland. Data acquisition was conducted during April–May 2024 using a Riegl VZ-400i terrestrial laser scanner (Riegl Laser Measurement Systems GmbH, Austria), capable of recording up to eight returns per laser pulse. This dataset includes TLS point clouds in the projected coordinate reference system commonly used in Finland (ETRS-TM35FIN). Each point is annotated with reflectance, return number, return count, and height above ground. Additionally, information linking each return to its originating tree is provided. For individual trees, the point clouds were further processed to derive key attributes such as crown projection area, crown diameter, and stem diameter. In addition, tree species was derived by linking the TLS-based tree measurements with field inventory data. Here, we describe and share these curated TLS data files and related tree measurements, which offer a valuable resource for advancing tree- and forest-related research and applications.

Yrttimaa, School of Forest Sciences, University of Eastern Finland, FI-80101 Joensuu, Finland https://orcid.org/0000-0003-2648-523X E-mail: tuomas.yrttimaa@uef.fi
Liikonen, School of Forest Sciences, University of Eastern Finland, FI-80101 Joensuu, Finland E-mail: lauriliik@uef.fi
Erkkilä, School of Forest Sciences, University of Eastern Finland, FI-80101 Joensuu, Finland E-mail: aapo.erkkila@uef.fi
Vastaranta, School of Forest Sciences, University of Eastern Finland, FI-80101 Joensuu, Finland https://orcid.org/0000-0001-6552-9122 E-mail: mikko.vastaranta@uef.fi

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