activity
20202025
most citedSegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data

119 citations · 243 across the 9 of their papers we have counts for

collaborators

12 papers

cs.CV2025

Enhancing Tree Species Classification: Insights from YOLOv8 and Explainable AI Applied to TLS Point Cloud Projections

Adrian Straker, Paul Magdon, Marco Zullich +5

Aiming to advance research in the field of interpretability of deep learning models for tree species classification using TLS 3D point clouds we present insights in the classificat…

cs.CV2025★ 1 cited

ForestFormer3D: A Unified Framework for End-to-End Segmentation of Forest LiDAR 3D Point Clouds

Binbin Xiang, Maciej Wielgosz, Stefano Puliti +4

The segmentation of forest LiDAR 3D point clouds, including both individual tree and semantic segmentation, is fundamental for advancing forest management and ecological research.…

cs.CV2025★ 7 cited

Multispectral airborne laser scanning for tree species classification: a benchmark of machine learning and deep learning algorithms

Josef Taher, Eric Hyyppä, Matti Hyyppä +46

Climate-smart and biodiversity-preserving forestry demands precise information on forest resources, extending to the individual tree level. Multispectral airborne laser scanning (A…

cs.CV2024★ 1 cited

BranchPoseNet: Characterizing tree branching with a deep learning-based pose estimation approach

Stefano Puliti, Carolin Fischer, Rasmus Astrup

This paper presents an automated pipeline for detecting tree whorls in proximally laser scanning data using a pose-estimation deep learning model. Accurate whorl detection provides…

cs.CV2024★ 5 cited

Benchmarking tree species classification from proximally-sensed laser scanning data: introducing the FOR-species20K dataset

Stefano Puliti, Emily R. Lines, Jana Müllerová +30

Proximally-sensed laser scanning offers significant potential for automated forest data capture, but challenges remain in automatically identifying tree species without additional…

cs.CV2024★ 119 cited

SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data

Maciej Wielgosz, Stefano Puliti, Binbin Xiang +2

This research advances individual tree crown (ITC) segmentation in lidar data, using a deep learning model applicable to various laser scanning types: airborne (ULS), terrestrial (…

cs.CV2023

Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning

Binbin Xiang, Maciej Wielgosz, Theodora Kontogianni +4

Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver…

cs.CV2023★ 28 cited

FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees

Stefano Puliti, Grant Pearse, Peter Surový +4

The FOR-instance dataset (available at https://doi.org/10.5281/zenodo.8287792) addresses the challenge of accurate individual tree segmentation from laser scanning data, crucial fo…

cs.CV2023

Towards accurate instance segmentation in large-scale LiDAR point clouds

Binbin Xiang, Torben Peters, Theodora Kontogianni +4

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…

cs.CV2023

Point2Tree(P2T) -- framework for parameter tuning of semantic and instance segmentation used with mobile laser scanning data in coniferous forest

Maciej Wielgosz, Stefano Puliti, Phil Wilkes +1

This article introduces Point2Tree, a novel framework that incorporates a three-stage process involving semantic segmentation, instance segmentation, optimization analysis of hyper…

stat.AP2020

Above-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat 8

Stefano Puliti, Johannes Breidenbach, Johannes Schumacher +3

This study aimed at estimating total forest above-ground net change (Delta AGB, Mt) over five years (2014-2019) based on model-assisted estimation utilizing freely available satell…

stat.AP2020★ 82 cited

National mapping and estimation of forest area by dominant tree species using Sentinel-2 data

Johannes Breidenbach, Lars T. Waser, Misganu Debella-Gilo +5

Nation-wide Sentinel-2 mosaics were used with National Forest Inventory (NFI) data for modelling and subsequent mapping of spruce, pine and deciduous forest in Norway in 16 m $\tim…