no code implementations • 28 Jan 2024 • Maciej Wielgosz, Stefano Puliti, Binbin Xiang, Konrad Schindler, Rasmus Astrup
In conclusion, this study shows the feasibility of a sensor-agnostic model for diverse lidar data, surpassing sensor-specific approaches and setting new standards in tree segmentation, particularly in complex forests.
1 code implementation • 22 Dec 2023 • Binbin Xiang, Maciej Wielgosz, Theodora Kontogianni, Torben Peters, Stefano Puliti, Rasmus Astrup, Konrad Schindler
Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services.
no code implementations • 3 Sep 2023 • Stefano Puliti, Grant Pearse, Peter Surový, Luke Wallace, Markus Hollaus, Maciej Wielgosz, Rasmus Astrup
In conclusion, the FOR-instance dataset contributes to filling a gap in the 3D forest research, enhancing the development and benchmarking of segmentation algorithms for dense airborne laser scanning data.
1 code implementation • 6 Jul 2023 • Binbin Xiang, Torben Peters, Theodora Kontogianni, Frawa Vetterli, Stefano Puliti, Rasmus Astrup, Konrad Schindler
Panoptic segmentation is the combination of semantic and instance segmentation: assign the points in a 3D point cloud to semantic categories and partition them into distinct object instances.
no code implementations • 4 May 2023 • Maciej Wielgosz, Stefano Puliti, Phil Wilkes, Rasmus Astrup
We trained a model based on Pointnet++ architecture which achieves 0. 92 F1-score in semantic segmentation.
no code implementations • 9 Jul 2021 • Janne Räty, Johannes Breidenbach, Marius Hauglin, Rasmus Astrup
We found that forest attributes characterizing the maturity of forest, such as remote sensing-based height, harvested timber volume and quadratic mean diameter at breast height, were among the most important predictor variables.
no code implementations • 16 Apr 2020 • Johannes Breidenbach, Lars T. Waser, Misganu Debella-Gilo, Johannes Schumacher, Johannes Rahlf, Marius Hauglin, Stefano Puliti, Rasmus Astrup
However, even for municipalities with a decent number of NFI plots, direct NFI estimates were sometimes more precise than MA estimates.
Applications