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For the task of subdecimeter aerial imagery segmentation, fine-grained semantic segmentation results are usually difficult to obtain because of complex remote sensing content and optical conditions. Recently, convolutional neural networks…

Computer Vision and Pattern Recognition · Computer Science 2018-08-28 Kai Yue , Lei Yang , Ruirui Li , Wei Hu , Fan Zhang , Wei Li

Forest biomass is a key influence for future climate, and the world urgently needs highly scalable financing schemes, such as carbon offsetting certifications, to protect and restore forests. Current manual forest carbon stock inventory…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Gyri Reiersen , David Dao , Björn Lütjens , Konstantin Klemmer , Kenza Amara , Attila Steinegger , Ce Zhang , Xiaoxiang Zhu

Airborne light detection and ranging (LiDAR) plays an increasingly significant role in urban planning, topographic mapping, environmental monitoring, power line detection and other fields thanks to its capability to quickly acquire…

Computer Vision and Pattern Recognition · Computer Science 2020-04-21 Congcong Wen , Xiang Li , Xiaojing Yao , Ling Peng , Tianhe Chi

Making sense of the physical world has always been at the core of mapping. Up until recently, this has always dependent on using the human eye. Using airborne lasers, it has become possible to quickly "see" more of the world in many more…

Computational Engineering, Finance, and Science · Computer Science 2015-04-14 Christoph Waldhauser , Ronald Hochreiter , Johannes Otepka , Norbert Pfeifer , Sajid Ghuffar , Karolina Korzeniowska , Gerald Wagner

Accurately estimating forest biomass is crucial for global carbon cycle modelling and climate change mitigation. Tree height, a key factor in biomass calculations, can be measured using Synthetic Aperture Radar (SAR) technology. This study…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Grace Colverd , Jumpei Takami , Laura Schade , Karol Bot , Joseph A. Gallego-Mejia

Monitoring forest dynamics at an individual tree scale is essential for accurately assessing ecosystem responses to climate change, yet traditional methods relying on field-based forest inventories are labor-intensive and limited in spatial…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Matthew J. Allen , Harry J. F. Owen , Stuart W. D. Grieve , Emily R. Lines

Earth's forests play an important role in the fight against climate change, and are in turn negatively affected by it. Effective monitoring of different tree species is essential to understanding and improving the health and biodiversity of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-30 Venkatesh Ramesh , Arthur Ouaknine , David Rolnick

The analysis of the multi-layer structure of wild forests is an important challenge of automated large-scale forestry. While modern aerial LiDARs offer geometric information across all vegetation layers, most datasets and methods focus only…

Computer Vision and Pattern Recognition · Computer Science 2022-04-26 Ekaterina Kalinicheva , Loic Landrieu , Clément Mallet , Nesrine Chehata

Mapping standing dead trees is critical for assessing forest health, monitoring biodiversity, and mitigating wildfire risks, for which aerial imagery has proven useful. However, dense canopy structures, spectral overlaps between living and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-06 Anis Ur Rahman , Einari Heinaro , Mete Ahishali , Samuli Junttila

Urban forests play a key role in enhancing environmental quality and supporting biodiversity in cities. Mapping and monitoring these green spaces are crucial for urban planning and conservation, yet accurately detecting trees is challenging…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Alessandro dos Santos Ferreira , Ana Paula Marques Ramos , José Marcato Junior , Wesley Nunes Gonçalves

Identifying species of trees in aerial images is essential for land-use classification, plantation monitoring, and impact assessment of natural disasters. The manual identification of trees in aerial images is tedious, costly, and…

Computer Vision and Pattern Recognition · Computer Science 2020-08-31 Italos Estilon de Souza , Alexandre Xavier Falcão

We propose a new deep learning-based method for estimating the occupancy of vegetation strata from airborne 3D LiDAR point clouds. Our model predicts rasterized occupancy maps for three vegetation strata corresponding to lower, medium, and…

Computer Vision and Pattern Recognition · Computer Science 2022-01-21 Ekaterina Kalinicheva , Loic Landrieu , Clément Mallet , Nesrine Chehata

Tree height estimation serves as an important proxy for biomass estimation in ecological and forestry applications. While traditional methods such as photogrammetry and Light Detection and Ranging (LiDAR) offer accurate height measurements,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Grace Colverd , Jumpei Takami , Laura Schade , Karol Bot , Joseph A. Gallego-Mejia

Trees inside cities are important for the urban microclimate, contributing positively to the physical and mental health of the urban dwellers. Despite their importance, often only limited information about city trees is available. Therefore…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Hui Zhang , Ankit Kariryaa , Venkanna Babu Guthula , Christian Igel , Stefan Oehmcke

One of the impacts of climate change is the difficulty of tree regrowth after wildfires over areas that traditionally were covered by certain tree species. Here a deep learning model is customized to classify land covers from four-band…

Computer Vision and Pattern Recognition · Computer Science 2020-11-13 Wang Zhou , Levente Klein

Mapping standing dead trees is crucial for acquiring information on the effects of climate change on forests and forest biodiversity. However, leveraging high-quality aerial imagery for dead tree segmentation poses challenges due to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Mete Ahishali , Anis Ur Rahman , Einari Heinaro , Aysen Degerli , Samuli Junttila

We investigate the use of additional 3D and phylogenetic non-3D tree balance indices for analyzing and monitoring forests using an exemplary "virtual forest" dataset from the Wytham Woods, Oxford, UK. This study assesses 3D model quality,…

Quantitative Methods · Quantitative Biology 2026-03-23 Sophie J. Kersting , Mareike Fischer

Point-cloud data acquired using a terrestrial laser scanner (TLS) play an important role in digital forestry research. Multiple scans are generally used to overcome occlusion effects and obtain complete tree structural information. However,…

Computer Vision and Pattern Recognition · Computer Science 2020-01-31 Xiuxian Xu , Pei Wang , Xiaozheng Gan , Yaxin Li , Li Zhang , Qing Zhang , Mei Zhou , Yinghui Zhao , Xinwei Li

The stability and ability of an ecosystem to withstand climate change is directly linked to its biodiversity. Dead trees are a key indicator of overall forest health, housing one-third of forest ecosystem biodiversity, and constitute 8%of…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Jacquelyn A. Shelton , Przemyslaw Polewski , Wei Yao , Marco Heurich

Laser scanning has proven to be an invaluable tool in assessing the decomposition of forest environments. Mobile laser scanning (MLS) has shown to be highly promising for extremely accurate, tree level inventory. In this study, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Juho Korkeala , Jesse Muhojoki , Josef Taher , Klaara Salolahti , Matti Hyyppä , Antero Kukko , Juha Hyyppä