Real-world tree attribute input data for 3D fuel modelling in FastFuels from Oregon, USA, 2019

This dataset consists of high-resolution individual tree attributes specifically formatted for 3D fuel modeling and physics-based fire simulation. The primary data resource is a structured inventory of forest vegetation, where each entry represents an individual tree. Key variables include precise spatial coordinates (X, Y, Z), Diameter at Breast Height (DBH), and Total Height (TH). These parameters serve as the foundational inputs required to synthesize complex 3D fuel beds within the FastFuels modeling environment that can be later be used as inputs for wildfire simulation softwares FIRETEC and QUIC-Fire. The data was extracted from terrestrial 3D LiDAR point clouds of a Pinus ponderosa plot scanned with a Riegl-VZ400i TLS scanner in Sycan Marsh, Oregon, USA during the summer of 2019. This resource was developed to provide "ground truth" fuel data for the validation and calibration of next-generation wildfire models, enabling researchers to simulate fire behaviour-such as crown fire initiation and heat flux-with higher physical fidelity. Full details about this dataset can be found at https://doi.org/10.5285/bc67144d-91c4-446d-8691-248a793bf4f4