Virtual laser scanning with HELIOS++: A novel take on ray tracing-based simulation of topographic full-waveform 3D laser scanning

Winiwarter, Lukas; Pena, Alberto Manuel Esmorís; Weiser, Hannah; Anders, Katharina; Sánchez, Jorge Martínez; Searle, Mark; Höfle, Bernhard

doi:10.1016/j.rse.2021.112772

Cited by 64 publications

(39 citation statements)

References 39 publications

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“…DART also allows lidar to be simulated. Furthermore, there are specialized lidar simulators such as HELIOS++ (Winiwarter et al, 2022(Winiwarter et al, , 2021. The point clouds presented here can be used as scene parts for HELIOS++ after converting LAZ files to ASCII files, e.g., using LAStools: las2txt -i <pointcloud.laz> -o <pointcloud.xyz> -oparse xyz and using the xyzloader of HELIOS++ (https: //github.com/3dgeo-heidelberg/helios/wiki/Scene# xyz-point-cloud-loader, last access: 24 June 2022).…”

Section: Usage Notesmentioning

confidence: 99%

“…One key element for creating synthetic forest stands, enabling laser scanning simulations, is detailed and realistic 3D tree models, which can be reconstructed from 3D point clouds obtained with terrestrial, UAV-borne or airborne laser scanning. Virtual forest scenes can be built from such 3D tree models and used as input to complex radiative transfer models (e.g., DART; Gastellu-Etchegorry et al, 2015) or light detection and ranging (lidar) simulators (e.g., HE-LIOS++; Winiwarter et al, 2022). Such simulations enable an improved understanding of the relation between forests' structural elements and electromagnetic radiation (Disney et al, 2010;Weiser et al, 2021;Widlowski et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests

Weiser

Schäfer²,

Winiwarter³

et al. 2022

Earth Syst. Sci. Data

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Abstract. Laser scanning from different acquisition platforms enables the collection of 3D point clouds from different perspectives and with varying resolutions. These point clouds allow us to retrieve detailed information on the individual tree and forest structure. We conducted airborne laser scanning (ALS), uncrewed aerial vehicle (UAV)-borne laser scanning (ULS) and terrestrial laser scanning (TLS) in two German mixed forests with species typical of central Europe. We provide the spatially overlapping, georeferenced point clouds for 12 forest plots. As a result of individual tree extraction, we furthermore present a comprehensive database of tree point clouds and corresponding tree metrics. Tree metrics were derived from the point clouds and, for half of the plots, also measured in the field. Our dataset may be used for the creation of 3D tree models for radiative transfer modeling or lidar simulation studies or to fit allometric equations between point cloud metrics and forest inventory variables. It can further serve as a benchmark dataset for different algorithms and machine learning tasks, in particular automated individual tree segmentation, tree species classification or forest inventory metric prediction. The dataset and supplementary metadata are available for download, hosted by the PANGAEA data publisher at https://doi.org/10.1594/PANGAEA.942856 (Weiser et al., 2022a).

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Section: Usage Notesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests

Weiser

Schäfer²,

Winiwarter³

et al. 2022

Earth Syst. Sci. Data

Self Cite

View full text Add to dashboard Cite

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“…Complex point cloud simulation tools, such as the HELIOS++ [54] or Gazebo together with the Robotics Operation System [55], have reached a high level of development. These tools can be used to create point clouds from surface and CAD models that contain the characteristics of specific sensors and system configurations.…”

Section: D Point Cloud Datasetsmentioning

confidence: 99%

Evaluating the Quality of Semantic Segmented 3D Point Clouds

Barnefske

Sternberg

2022

Remote Sensing

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Recently, 3D point clouds have become a quasi-standard for digitization. Point cloud processing remains a challenge due to the complex and unstructured nature of point clouds. Currently, most automatic point cloud segmentation methods are data-based and gain knowledge from manually segmented ground truth (GT) point clouds. The creation of GT point clouds by capturing data with an optical sensor and then performing a manual or semi-automatic segmentation is a less studied research field. Usually, GT point clouds are semantically segmented only once and considered to be free of semantic errors. In this work, it is shown that this assumption has no overall validity if the reality is to be represented by a semantic point cloud. Our quality model has been developed to describe and evaluate semantic GT point clouds and their manual creation processes. It is applied on our dataset and publicly available point cloud datasets. Furthermore, we believe that this quality model contributes to the objective evaluation and comparability of data-based segmentation algorithms.

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“…DART also allows to simulate LiDAR. Furthermore, there are specialized LiDAR simulators such as HELIOS++ (Winiwarter et al, 2022(Winiwarter et al, , 2021. The point clouds presented here can be used as scene parts for HELIOS++ after converting LAZ files to ASCII files, e.g.…”

Section: Ulsmentioning

confidence: 99%

“…For example, 3D tree models derived from laser scans of real trees have been used to develop structural tree allometries to, e.g., non-destructively estimate the aboveground-biomass of tree individuals (Calders et al, 2015). Further, virtual forest scenes can be built from 3D tree models and used as input to radiative transfer models (e.g., DART, Gastellu-Etchegorry et al 2015) or Light Detection and Ranging (LiDAR) simulators (e.g., HELIOS++, Winiwarter et al 2022). Such simulations enable an improved understanding of the relation between forests' structural elements and electromagnetic radiation (Disney et al, 2010;Weiser et al, 2021;Widlowski et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests

Weiser

Schäfer

Winiwarter

et al. 2022

Preprint

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Abstract. Laser scanning from different acquisition platforms enables collecting 3D point clouds from different perspectives and with varying resolutions. Such point clouds allow us to e.g., retrieve information about the forest structure and individual tree properties, or to model individual trees in 3D. We conducted airborne laser scanning (ALS), UAV-borne laser scanning (ULS) and terrestrial laser scanning (TLS) in German mixed forests with species typical for Central Europe. We provide the spatially overlapping, georeferenced point clouds of the different acquisitions. As a result of individual tree extraction, we furthermore present a comprehensive database of tree point clouds and corresponding tree metrics, both measured in the field and derived from the point clouds. Our dataset may be used for the creation of 3D tree models for radiative transfer modeling or LiDAR simulation studies or to fit allometric equations between point cloud metrics and forest inventory variables. It can further serve as a benchmark dataset for different algorithms and machine learning tasks, in particular automated individual tree segmentation, tree species classification or forest inventory metric prediction. The dataset and supplementary metadata are available for download on the PANGAEA data publisher at https://doi.org/10.1594/PANGAEA.933426 (Weiser et al., 2021b).

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Virtual laser scanning with HELIOS++: A novel take on ray tracing-based simulation of topographic full-waveform 3D laser scanning

Cited by 64 publications

References 39 publications

Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests

Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests

Evaluating the Quality of Semantic Segmented 3D Point Clouds

Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests

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