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The potential of tree planting as a natural climate solution is often undermined by inadequate monitoring of tree planting projects. Current monitoring methods involve measuring trees by hand for each species, requiring extensive cost,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Mélisande Teng , Arthur Ouaknine , Etienne Laliberté , Yoshua Bengio , David Rolnick , Hugo Larochelle

This paper presents a non-parametric approach for segmenting trees from airborne LiDAR data in deciduous forests. Based on the LiDAR point cloud, the approach collects crown information such as steepness and height on-the-fly to delineate…

Computer Vision and Pattern Recognition · Computer Science 2017-01-03 Hamid Hamraz , Marco A. Contreras , Jun Zhang

Accurate mapping of individual trees is essential for ecological monitoring and forest management. Orthomosaic imagery from unmanned aerial vehicles (UAVs) is widely used, but stitching artifacts and heavy preprocessing limit its…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Rongkun Zhu , Kangning Cui , Wei Tang , Rui-Feng Wang , Sarra Alqahtani , David Lutz , Fan Yang , Paul Fine , Jordan Karubian , Robert Plemmons , Jean-Michel Morel , Victor Pauca , Miles Silman

Developing a robust algorithm for automatic individual tree crown (ITC) detection from laser scanning datasets is important for tracking the responses of trees to anthropogenic change. Such approaches allow the size, growth and mortality of…

Computer Vision and Pattern Recognition · Computer Science 2019-10-04 Jonathan Williams , Carola-Bibiane Schönlieb , Tom Swinfield , Juheon Lee , Xiaohao Cai , Lan Qie , David A. Coomes

The pattern analysis of tree structure holds significant scientific value for genetic breeding and forestry management. The current trunk and branch extraction technologies are mainly LiDAR-based or UAV-based. The former approaches obtain…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Chenyang Fan , Xujie Zhu , Taige Luo , Sheng Xu , Zhulin Chen , Hongxin Yang

Visual explanation of ``black-box'' models allows researchers in explainable artificial intelligence (XAI) to interpret the model's decisions in a human-understandable manner. In this paper, we propose interpretable class activation mapping…

Computer Vision and Pattern Recognition · Computer Science 2023-04-28 Seyed Mojtaba Marvasti-Zadeh , Devin Goodsman , Nilanjan Ray , Nadir Erbilgin

Unmanned aerial vehicles (UAV) are used successfully in many application areas such as military, security, monitoring, emergency aid, tourism, agriculture, and forestry. This study aims to automatically count trees in designated areas on…

Computer Vision and Pattern Recognition · Computer Science 2022-01-11 Musa Ataş , Ayhan Talay

The purpose of this study was to investigate the use of deep learning for coniferous/deciduous classification of individual trees from airborne LiDAR data. To enable efficient processing by a deep convolutional neural network (CNN), we…

Machine Learning · Computer Science 2018-02-27 Hamid Hamraz , Nathan B. Jacobs , Marco A. Contreras , Chase H. Clark

The accurate semantic segmentation of tree crowns within remotely sensed data is crucial for scientific endeavours such as forest management, biodiversity studies, and carbon sequestration quantification. However, precise segmentation…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Georgios Voulgaris

Olive tree biovolume estimation is a key task in precision agriculture, supporting yield prediction and resource management, especially in Mediterranean regions severely impacted by climate-induced stress. This study presents a comparative…

Image and Video Processing · Electrical Eng. & Systems 2025-10-31 Wondimagegn Abebe Demissie , Stefano Roccella , Rudy Rossetto , Antonio Minnocci , Andrea Vannini , Luca Sebastiani

In this paper, we introduce a framework for segmenting instances of a common object class by multiple active contour evolution over semantic segmentation maps of images obtained through fully convolutional networks. The contour evolution is…

Computer Vision and Pattern Recognition · Computer Science 2021-05-06 Przemyslaw Polewski , Jacquelyn Shelton , Wei Yao , Marco Heurich

The task of counting eucalyptus trees from aerial images collected by unmanned aerial vehicles (UAVs) has been frequently explored by techniques of estimation of the basal area, i.e, by determining the expected number of trees based on…

Computer Vision and Pattern Recognition · Computer Science 2017-03-29 Rodrigo M. Ferreira , Ricardo M. Marcacini

Tree perception is an essential building block toward autonomous forestry operations. Current developments generally consider input data from lidar sensors to solve forest navigation, tree detection and diameter estimation problems. Whereas…

Computer Vision and Pattern Recognition · Computer Science 2022-11-01 Vincent Grondin , Jean-Michel Fortin , François Pomerleau , Philippe Giguère

Tropical forests harbor most of the planet's tree biodiversity and are critical to global ecological balance. Canopy trees in particular play a disproportionate role in carbon storage and functioning of these ecosystems. Studying canopy…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Simon-Olivier Duguay , Hugo Baudchon , Etienne Laliberté , Helene Muller-Landau , Gonzalo Rivas-Torres , Arthur Ouaknine

Early detection of wildfires is essential to prevent large-scale fires resulting in extensive environmental, structural, and societal damage. Uncrewed aerial vehicles (UAVs) can cover large remote areas effectively with quick deployment…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Julius Pesonen , Teemu Hakala , Väinö Karjalainen , Niko Koivumäki , Lauri Markelin , Anna-Maria Raita-Hakola , Juha Suomalainen , Ilkka Pölönen , Eija Honkavaara

Deep-learning-based image classification and object detection has been applied successfully to tree monitoring. However, studies of tree crowns and fallen trees, especially on flood inundated areas, remain largely unexplored. Detection of…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Anne Achieng Osio , Hoàng-Ân Lê , Samson Ayugi , Fred Onyango , Peter Odwe , Sébastien Lefèvre

Accurate detection of individual tree crowns from remote sensing data poses a significant challenge due to the dense nature of forest canopy and the presence of diverse environmental variations, e.g., overlapping canopies, occlusions, and…

Computer Vision and Pattern Recognition · Computer Science 2023-10-26 Rudraksh Kapil , Seyed Mojtaba Marvasti-Zadeh , Nadir Erbilgin , Nilanjan Ray

Trees are key components of the terrestrial biosphere, playing vital roles in ecosystem function, climate regulation, and the bioeconomy. However, large-scale monitoring of individual trees remains limited by inadequate modelling. Available…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Dimitri Gominski , Martin Brandt , Xiaoye Tong , Siyu Liu , Maurice Mugabowindekwe , Sizhuo Li , Florian Reiner , Andrew Davies , Rasmus Fensholt

Airborne LiDAR point cloud representing a forest contains 3D data, from which vertical stand structure even of understory layers can be derived. This paper presents a tree segmentation approach for multi-story stands that stratifies the…

Computer Vision and Pattern Recognition · Computer Science 2017-07-18 Hamid Hamraz , Marco A. Contreras , Jun Zhang

Forest stands are the fundamental units in forest management inventories, silviculture, and financial analysis within operational forestry. Over the past two decades, a common method for mapping stand borders has involved delineation…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Håkon Næss Sandum , Hans Ole Ørka , Oliver Tomic , Erik Næsset , Terje Gobakken