Airborne Laser Scanning

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Overview

Airborne laser scanning (ALS) measures distances with aircraft-mounted lasers to produce 3D point clouds used in mapping, forestry, infrastructure, and environmental monitoring. Common approaches classify points or segments with deep neural networks, filter ground returns using geometric and elevation cues, and derive forest attributes from point-cloud structure; calibration and point-cloud enhancement can improve data quality. Research also develops datasets and benchmarks, alongside methods for compressing large point clouds and extracting features such as building footprints and tree species. A central challenge is making models reliable across different sensors, seasons, terrain, and point densities, especially where classes are imbalanced or reference labels are uncertain.

Latest papers

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12 papers0 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

  1. Gaussian Linear Functional Manifold Method for Massive Point Cloud Data

    Sep 4, 2026Hong Zhao, Tonglin Zhang, Baijian Yang +2Point Cloud Surface Reconstruction3D Reconstruction

    School of Applied and Creative Computing, Purdue University, West Lafayette, IN, USA · Department of Statistics, Purdue University, West Lafayette, IN, USA · Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, USA

  2. FLORA: A deep learning approach to predict forest attributes from heterogeneous LiDAR data

    Jun 30, 2026Emilie Vautier, Clément Mallet, Cédric VegaPoint Cloud LearningRemote Sensing

    Univ Gustave Eiffel, Géodata Paris, IGN, LASTIG, F-77454 Marne-la-Vallée, France · Univ Gustave Eiffel, Géodata Paris, IGN, LIF, F-54000, Nancy, France · Université de Lorraine, Géodata Paris, IGN, LIF, F-54000 Nancy, France

  3. Scene-agnostic ALS boresight self-calibration

    Jun 22, 2026Aurélien Brun, Jan SkaloudAirborne Laser Scanning

    aEPFL ENAC ESO, Bâtiment GC - Station 18, 1015 Lausanne, Switzerland

  4. PCFootprint: A Large-Scale Dataset and Benchmark for Vectorized Building Footprint Extraction from Aerial LiDAR Point Clouds

    Jun 18, 2026Haoyuan Shen, Kuihao Wang, Ruisheng Wang +1Remote Sensing Image SegmentationBuilding Footprint Extraction

    School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China

  5. Mirage: a Clean-Label Backdoor against LiDAR 3D Object Detection

    Jun 18, 2026Ziba Parsons, Ang LiLidar-Based 3D Object DetectionBackdoor Attacks

    Computer and Information Science University of Michigan - Dearborn Dearborn, MI 48170

  6. Inter-LPCM: Learning-based Inter-Frame Predictive Coding for LiDAR Point Cloud Compression

    May 18, 2026Chang Sun, Hui Yuan, Shiqi Jiang +3Point Cloud CompressionPredictive Coding

    School of Control Science and Engineering, Shandong University, Jinan 250061, China · Key Laboratory of Machine Intelligence and System Control, Ministry of Education, Jinan 250061, China · School of Computer Science and Technology, Shandong University, Qingdao, 266237, China +1

  7. Super-Resolution of Airborne Laser Scanning Point Clouds for Forest Inventory

    May 4, 2026Jinyuan Shao, Sangyoong Park, Chunxi Zhao +2Point Cloud DenoisingPoint Cloud Learning

    Department of Forestry and Natural Resources, Purdue University, USA · Lyles School of Civil and Construction Engineering, Purdue University, USA

  8. PACE: Post-Causal Entropy Modeling for Learned LiDAR Point Cloud Compression

    May 2, 2026Jiahao Zhu, Kang You, Dandan Ding +1Point Cloud CompressionAirborne Laser Scanning

    School of Information Science and Technology, Hangzhou Normal University, Hangzhou, China. · School of Electronic Science and Engineering, Nanjing University, Nanjing, China.

  9. Multispectral airborne laser scanning dataset for tree species classification: MS-ALS-SPECIES

    Apr 27, 2026Matti Hyyppä, Klaara Salolahti, Eric Hyyppä +9Point Cloud ClassificationTree Species Classification

    Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, The National Land Survey of Finland, Vuorimiehentie 5, Espoo, FI-02150, Finland

  10. SparseGF: A Height-Aware Sparse Segmentation Framework with Context Compression for Robust Ground Filtering Across Urban to Natural Scenes

    Apr 23, 2026Nannan Qin, Pengjie Tao, Haiyan Guan +43D Point Cloud SegmentationSpatial Generalization

    School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, JiangSu, China · Tiandu-Nuist Deep Space Exploration Laboratory, Nanjing, 210044, JiangSu, China · School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, 430079, Hubei, China +4

  11. Benchmarking Deep Learning Models for Aerial LiDAR Point Cloud Semantic Segmentation under Real Acquisition Conditions: A Case Study in Navarre

    Mar 23, 2026Alex Salvatierra, José Antonio Sanz, Christian Gutiérrez +13D Point Cloud Segmentation3D Semantic Segmentation

    Department of Statistics, Computer Science and Mathematics and Institute of Smart Cities (ISC), Public University of Navarre (UPNA), Campus de Arrosadía s/n, Pamplona, 31006, Navarre, Spain · Tracasa Instrumental, Cabárceno, 6, Sarriguren, 31621, Navarre, Spain

  12. Assessing airborne laser scanning and aerial photogrammetry for deep learning-based stand delineation

    Feb 25, 2026Håkon Næss Sandum, Hans Ole Ørka, Oliver Tomic +1Remote SensingRemote Sensing Image Segmentation

    Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway. · Faculty of Science and Technology, Norwegian University of Life Sciences, NMBU, P.O. Box 5003, NO-1432 Ås, Norway.