4.7 Article

An Unsupervised Canopy-to-Root Pathing (UCRP) Tree Segmentation Algorithm for Automatic Forest Mapping

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Environmental Sciences

Comparative Analysis of Multi-Platform, Multi-Resolution, Multi-Temporal LiDAR Data for Forest Inventory

Yi-Chun Lin et al.

Summary: LiDAR technology is advancing rapidly, providing valuable data for characterizing forest vertical structure. Comparative analysis of point clouds from different LiDAR systems helps select appropriate systems and tools for various research questions.

REMOTE SENSING (2022)

Article Environmental Sciences

A New Method for UAV Lidar Precision Testing Used for the Evaluation of an Affordable DJI ZENMUSE L1 Scanner

Martin Stroner et al.

Summary: This paper introduces a method using high-reflectivity foil-covered accurately georeferenced targets to verify the accuracy of UAV lidar systems. By comparing the lidar point cloud with a dense SfM point cloud, the systematic shift is successfully removed, revealing that the accuracy of the system is better than the manufacturer-declared values.

REMOTE SENSING (2021)

Article Environmental Sciences

Quality control and crop characterization framework for multi-temporal UAV LiDAR data over mechanized agricultural fields

Yi-Chun Lin et al.

Summary: Recent developments in remote sensing have enabled automatic, high resolution, and non-destructive survey of agriculture fields, particularly using LiDAR technology. This study proposes a targetless framework for multi-temporal LiDAR data quality control and crop characterization, with high performance in vertical and planimetric accuracy evaluation. The results show net discrepancies of -3 cm and -8 cm between multi-temporal point clouds, and successful row and alley detection under different conditions.

REMOTE SENSING OF ENVIRONMENT (2021)

Article Agriculture, Multidisciplinary

Graph-based methods for analyzing orchard tree structure using noisy point cloud data

Fred Westling et al.

Summary: Digitization of fruit trees using LiDAR allows for analysis to improve growing practices and yield. A method is presented for individual tree location, segmentation, and matter classification that can operate on low-quality data captured by handheld or mobile LiDAR. The new methods for tree location and segmentation showed improvement over existing methods, while trunk matter classification, though performing poorly in absolute terms, consistently outperformed existing methods with a significantly shorter runtime.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)

Article Remote Sensing

Leaf-Off and Leaf-On UAV LiDAR Surveys for Single-Tree Inventory in Forest Plantations

Yi-Chun Lin et al.

Summary: LiDAR technology has been proven effective for forest inventory and management, with the use of UAV platforms gaining popularity for providing high-resolution point clouds. The ability to map under canopy features with UAV LiDAR surveys depends on penetration degree, determined by canopy cover. This study investigates the impact of leaf cover scenarios on UAV survey quality and proposes an individual tree detection approach that outperforms existing algorithms.

DRONES (2021)

Article Engineering, Electrical & Electronic

Stratifying Forest Overstory and Understory for 3-D Segmentation Using Terrestrial Laser Scanning Data

Zengxin Yun et al.

Summary: The proposed algorithm showed better performance in low overlapped coniferous and broadleaf forest stands, with F1-scores of 0.96 and 0.91 respectively, but decreased to 0.89 and 0.65 in high overlap rates. Multistation TLS data produced better segmentation results (F1-scores: 0.85-1) than single-station TLS data (F1-scores: 0.67-0.83) in coniferous forest stands. The vertical forest structure profiles were found to have an impact on the final 3-D segmentation accuracy.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2021)

Article Geography, Physical

Unsupervised semantic and instance segmentation of forest point clouds

Di Wang

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2020)

Article Geography, Physical

Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees

Hamid Hamraz et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2019)

Article Ecology

Leaf and wood classification framework for terrestrial LiDAR point clouds

Matheus B. Vicari et al.

METHODS IN ECOLOGY AND EVOLUTION (2019)

Article Remote Sensing

Individual tree segmentation from a leaf-off photogrammetric point cloud

Julia C. Carr et al.

INTERNATIONAL JOURNAL OF REMOTE SENSING (2018)

Article Agriculture, Multidisciplinary

Automatic individual tree detection and canopy segmentation from three-dimensional point cloud images obtained from ground-based lidar

Kenta Itakura et al.

JOURNAL OF AGRICULTURAL METEOROLOGY (2018)

Article Geography, Physical

International benchmarking of terrestrial laser scanning approaches for forest inventories

Xinlian Liang et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2018)

Article Robotics

3DmFV: Three-Dimensional Point Cloud Classification in Real-Time Using Convolutional Neural Networks

Yizhak Ben-Shabat et al.

IEEE ROBOTICS AND AUTOMATION LETTERS (2018)

Article Remote Sensing

Layer Stacking: A Novel Algorithm for Individual Forest Tree Segmentation from LiDAR Point Clouds

Elias Ayrey et al.

CANADIAN JOURNAL OF REMOTE SENSING (2017)

Article Remote Sensing

Layer Stacking: A Novel Algorithm for Individual Forest Tree Segmentation from LiDAR Point Clouds

Elias Ayrey et al.

CANADIAN JOURNAL OF REMOTE SENSING (2017)

Article Geochemistry & Geophysics

Forest Data Collection Using Terrestrial Image-Based Point Clouds From a Handheld Camera Compared to Terrestrial and Personal Laser Scanning

Xinlian Liang et al.

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2015)

Article Remote Sensing

Deep learning-based tree classification using mobile LiDAR data

Haiyan Guan et al.

REMOTE SENSING LETTERS (2015)

Proceedings Paper Geography, Physical

AUTOMATIC CLASSIFICATION OF TREES FROM LASER SCANNING POINT CLOUDS

Beril Sirmacek et al.

ISPRS GEOSPATIAL WEEK 2015 (2015)

Article Environmental Sciences

Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data

Pasi Raumonen et al.

REMOTE SENSING (2013)

Review Remote Sensing

A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing

Yinghai Ke et al.

INTERNATIONAL JOURNAL OF REMOTE SENSING (2011)

Article Environmental Sciences

Lidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers

Kaiguang Zhao et al.

REMOTE SENSING OF ENVIRONMENT (2009)

Article Environmental Sciences

Mapping US forest biomass using nationwide forest inventory data and moderate resolution information

J. A. Blackard et al.

REMOTE SENSING OF ENVIRONMENT (2008)

Article Geography, Physical

The individual tree crown approach applied to Ikonos images of a coniferous plantation area

Francois A. Gougeon et al.

PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING (2006)

Article Geography, Physical

Individual tree-crown delineation and treetop detection high-spatial-resolution aerial imagery

L Wang et al.

PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING (2004)

Article Computer Science, Interdisciplinary Applications

TIDA: an algorithm for the delineation of tree crowns in high spatial resolution remotely sensed imagery

DS Culvenor

COMPUTERS & GEOSCIENCES (2002)