Canopy

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2 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Jul 13Week of Sep 28

Latest papers 18

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Pixel-Level Transformers in Remote Sensing: A Canopy Height Case Study
Sep 29, 2026Sven Ligensa, Jan Pauls, Karsten Schrödter +2Canopy Remote Sensing
University of Münster Münster, Germany · Laboratoire des Sciences du Climat et de l’Environnement Paris, France
Canopy: Exploiting Piecewise Smooth Tree Priors for Multi-Fidelity Bandits
Sep 24, 2026Michael Jerge, Suman JanaTree Search Multi-Fidelity
Amazon · Columbia University
From crown candidates to neighborhood screening: integrating optical GeoAI and spatial modeling for urban-canopy assessment in Davis, California
Aug 14, 2026Mohammadreza Narimani, Shreyan Mitra, Parastoo FarajpoorCanopy Land Surface Temperature
Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA, 95616, USA · California High School, San Ramon, CA, 94583, USA
Deep Evidential Regression for Sparse Forest Height Estimation from Multimodal Satellite Imagery
Aug 3, 2026Laura Bader, Muhammad Ammar Ahmed, Xiao Xiang Zhu +1Canopy Forest Biomass
LMU Munich, 80539 Munich, Germany · Munich Center for Machine Learning (MCML) · TU Munich, 80333 Munich
UAV3DCrop: Benchmarking 3D Reconstruction in Repeated Multi-Angle UAV Crop Surveys
Aug 3, 2026Junxiong Zhou, Xuechen Li, Chonghao Qiu +11Agricultural Monitoring 3D Reconstruction
University of Minnesota, Twin Cities, USA · University of Pittsburgh, USA · Max Planck Institute for Biogeochemistry, Germany +3
Uncertainty Quantification for EO Regression Tasks: Building Height, Tree Canopy Height and Above-ground Biomass Estimation
Jul 13, 2026Ritu Yadav, Andrea Nascetti, Yifang BanCanopy Biomass
Ritu Yadav, Andrea Nascetti and Yifang Ban is with Division of Geoinformatics, KTH Royal Institute of Technology, Sweden.
3D Reconstruction of deciduous Trees using low-cost UAV- and Crane-based Photogrammetry for Monitoring Shoot Elongation across entire Canopies
Jul 8, 2026Stephan Nebiker, Micha Tschanz, Nando Amport +1Forest Biomass Canopy
Institute of Geomatics, FHNW University of Applied Sciences and Arts Northwestern Switzerland, 4132 Muttenz, Switzerland · Physiological Plant Ecology group, University of Basel, 4056 Basel
Canopy: A Heterograph Foundation Model for Metabolic Engineering
Jul 7, 2026Jake Bowden, Laurence Legon, Satnam SuraeMetabolic Biomedical Knowledge Graph
Twig Bio, London, United Kingdom
EcoVision: AI-Powered Drone Imaging for Salt Marsh Vegetation Monitoring and Dominance Mapping
Jul 7, 2026Innocent Onyenonachi, Peter J. Lawerance, Nadia KanwalAerial Imagery Canopy
School of Computer Science and Mathematics, Keele University, ST5 3BG, United Kingdom · School of Life Science, Keele University, ST5 3BG, United Kingdom
Uncertainty-aware tree height change regression
Jul 1, 2026Max Gaber, Dimitri Gominski, Jaime C. Revenga +3Canopy Change
Department of Geosciences and Natural Resource Management, University of Copenhagen · Department of Mathematical Sciences, University of Copenhagen · Department of Computer Science and Electrical Engineering, University of Rostock +1
Integrating national forest inventory, airborne lidar, and satellite imagery for wall-to-wall mapping of forest structure with computer vision
Jun 18, 2026Luke J. Zachmann, David D. Diaz, Vincent A. Landau +8Forest Biomass Biomass
Vibrant Planet Public Benefit Corporation, Truckee, CA, USA
Leaf Spectral Reflectance Prediction Using Multi-Head Attention Neural Networks
May 31, 2026Parastoo Farajpoor, Alireza Pourreza, Mohammadreza Narimani +2Reflectance Canopy
Digital Agriculture Laboratory, Department of Biological and Agricultural Engineering, University of California, Davis, CA, USA · Department of Botany and Plant Sciences, University of California, Riverside, CA, USA · Department of Viticulture and Enology, University of California, Davis, CA, USA
Fine-Tuning Improves Information Conveyance in Language Models
May 29, 2026Yuwei Cheng, Weiyi Tian, Haifeng XuLarge Language Model Fine-Tuning Model Fine-Tuning
Department of Data Science University of Chicago Chicago, IL 60637 · Department of Computer Science University of Chicago Chicago, IL 60637
Rapid Forest Fuel Load Estimation via Virtual Remote Sensing and Metric-Scale Feed-Forward 3D Reconstruction
May 11, 2026Quanyun Wu, Kyle Gao, Wentao Sun +6Forest Biomass Canopy
University of Waterloo · Waterloo, Canada · University of Calgary +1
Developing a foundation model for high-resolution remote sensing data of the Netherlands
May 11, 2026Paul Vermeeren, Heysem KayaRecent Vision Foundation Models Canopy
Department of Information and Computer Sciences, Utrecht Univ., the Netherlands
From Canopy to Collision: A Hybrid Predictive Framework for Identifying Risk Factors in Tree-Involved Traffic Crashes
Apr 25, 2026Abdul Azim, Ahmed Hossain, Soumyadip Maitra +1Crashes Canopy
Department of Civil Engineering Rajshahi University of Engineering & Technology Rajshahi-6204, Bangladesh · Traffic Safety Analysis Engineer, Traffic Safety Group Multimodal Planning Division (MPD) Arizona Department of Transportation (ADOT) 1615 W. Jackson St Phoenix, AZ 85007 · Department of Transportation Studies College of Science, Engineering and Technology Texas Southern University 3100 Cleburne Street, Houston, TX, 77004
From Articles to Canopies: Knowledge-Driven Pseudo-Labelling for Tree Species Classification using LLM Experts
Apr 17, 2026Michał Romaszewski, Dominik Kopeć, Michał Cholewa +6Species Identification Canopy
Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, Gliwice, 44-100, Poland · University of Lodz, Narutowicza 68, 90-136, Lodz, Poland · MGGP Aero, Kaczkowskiego 6, 33-100, Tarnów, Poland +1
SERA-H: Super-Resolution of Sentinel Time Series for Fine-Scale Canopy Height Mapping
Dec 19, 2025Thomas Boudras, Martin Schwartz, Rasmus Fensholt +6Canopy Sentinel-2
Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA, CNRS, UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France · Department of Geography and Geology, University of Copenhagen, Øster Voldgade 10, Copenhagen, DK-1350, Denmark · Kayros SAS, Paris, 75009, France +2

Sep 29, 2026, cs.CVJ/K move · Enter open · S save

Pixel-Level Transformers in Remote Sensing: A Canopy Height Case Study

Sven Ligensa, Jan Pauls, Karsten Schrödter, Ibrahim Fayad+1

University of Münster Münster, Germany · Laboratoire des Sciences du Climat et de l’Environnement Paris, France

Canopy Remote Sensing Pixel-Level Prediction Transformer Architectures Forecast

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Predicting canopy height from medium-resolution satellite imagery is a common and scalable approach for assessing the condition of the world's forests, which play a crucial role in climate change mitigation. While Transformer-based architectures have shown strong performance in many domains, their straightforward application to dense (i.e., pixel-level) regression tasks often yields suboptimal results. In particular, the patch size has a crucial impact on the model performance. In this work, we consider pixel-level attention schemes and show that the resulting models generally outperform those relying on larger patch sizes. However, pixel-level attention can be a prohibitively resource-intensive operation. For this reason, we conduct an extensive experimental study using efficient attention variants to identify favorable trade-offs between prediction quality and resource requirements, facilitating the practical deployment of the proposed models. In addition, we perform a comprehensive comparison with several well-established models in the field and show that, with suitable hyperparameter choices, Transformer-based architectures can outperform competing approaches. Our findings provide practical guidance for designing models for pixel-level regression tasks on medium-resolution satellite imagery, including canopy height and biomass estimation, soil moisture mapping, and yield forecasting.

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