Article
Environmental Sciences
Dimitrios Panagiotidis, Azadeh Abdollahnejad
Summary: This study focuses on using TLS data and the RANSAC method to accurately generate log length and diameter for estimating merchantable volume at the tree level. The results demonstrate low bias and high accuracy for deciduous and coniferous trees, as well as a high correlation with log length, which is crucial for analyzing stem curvature changes at different heights. The study also highlights the potential of TLS data collection for forest inventories, reducing the reliance on field reference data.
Article
Environmental Sciences
Wenxia Dai, Qingfeng Guan, Shangshu Cai, Rundong Liu, Ruibo Chen, Qing Liu, Chao Chen, Zhen Dong
Summary: This study investigates the performance of estimating plot canopy cover using Unmanned-Aerial-Vehicle (UAV)-Borne Laser Scanning (ULS) and Terrestrial Laser Scanning (TLS). The results show that ULS has better accuracy compared to TLS, and the difference increases with forest complexity. The study provides useful information for the selection of data sources and estimation methods in plot canopy cover mapping.
Article
Remote Sensing
Daniel Kuekenbrink, Mauro Marty, Ruedi Boesch, Christian Ginzler
Summary: This study evaluates the performance of different close-range remote sensing devices for tree detection and diameter at breast height (DBH) extraction in forests. The results show that terrestrial laser scanning systems (TLS) have the highest tree detection rate, while drone-based laser scanning systems (UAVLS) have the lowest tree detection rate. The novel GoPro approach performs moderately well in tree detection and is comparable to LiDAR devices in DBH extraction.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Geochemistry & Geophysics
Yuanzhi Cai, Lei Fan, Peter M. Atkinson, Cheng Zhang
Summary: This research proposes a novel image enhancement method to reveal the local geometric characteristics of point cloud data in images. The method explores various feature channel combinations and achieves improved semantic segmentation accuracy. Experimental results on the Semantic3D benchmark demonstrate the superiority of this image-based approach.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Plant Sciences
Peter B. Boucher, Ian Paynter, David A. Orwig, Ilan Valencius, Crystal Schaaf
Summary: The research evaluated the impact of occlusion on TLS scans and compared different stem sets, finding that occlusion from non-stem sources was the major influence on TLS line of sight. It was also discovered that transect and point TLS samples demonstrated better representativeness of some stem properties. Deriving sampled area from TLS scans improved estimates of stem density.
Article
Environmental Sciences
Lidu Zhao, Xiaping Ma, Zhongfu Xiang, Shuangcheng Zhang, Chuan Hu, Yin Zhou, Guicheng Chen
Summary: The extraction of landslide deformation using terrestrial laser scanning has many important applications. This study proposes a method to extract landslide deformations from TLS data by eliminating edge drift and using weighted least squares regularization solution. Experimental results show that the proposed method outperforms existing methods in landslide deformation extraction.
Review
Environmental Sciences
Tasiyiwa Priscilla Muumbe, Jussi Baade, Jenia Singh, Christiane Schmullius, Christian Thau
Summary: Savannas are diverse ecosystems with complex vegetation, conventional methods may underestimate carbon storage potential. TLS technology shows promise in accurate vegetation parameter extraction, future research should focus on algorithm development and improvement.
Review
Chemistry, Analytical
Chao Wu, Yongbo Yuan, Yang Tang, Boquan Tian
Summary: Terrestrial laser scanning (TLS) is a revolutionary technology gaining increasing interest in the fields of architecture, engineering, and construction (AEC) due to its automated, non-contact operation, and efficient large-scale sampling capability. This paper presents a systematic review of the progress and current status of TLS, categorizing major applications and identifying essential problems impacting its working effects. Future research directions are suggested to improve cost control, data processing capability, automatic scan planning, digital technology integration, and adoption of artificial intelligence in TLS.
Article
Environmental Sciences
Gabor Brolly, Geza Kiraly, Matti Lehtomaki, Xinlian Liang
Summary: This paper presents a fully automatic method for tree mapping and parameter extraction from terrestrial laser scans, achieving tree height estimates without constraints on crown shape. The algorithm demonstrates robustness across diverse forest structures, but tends to be conservative in tree height estimates.
Article
Forestry
Timo P. Pitkanen, Tuula Piri, Aleksi Lehtonen, Mikko Peltoniemi
Summary: The study demonstrated the applicability of TLS point cloud data in detecting structural differences between healthy and diseased trees infected by Heterobasidion annosum. Diseased trees were found to have a more swollen butt and point accumulations at greater heights, but there was no statistically significant difference in crown occupancy compared to healthy trees. Up to 85% classification accuracy of the infection status was achieved based on the calculated features.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Chemistry, Analytical
Michael Bekele Maru, Donghwan Lee, Kassahun Demissie Tola, Seunghee Park
Summary: This study compared the performance of optical sensors (depth camera and terrestrial laser scanner) in estimating structural deflection. Bilateral filtering techniques were used to enhance the accuracy of point cloud data and increase the prospects of sensor application in structural health monitoring. Results showed that data obtained from TLS were better than those obtained from DC.
Article
Environmental Sciences
Guotao Hu, Yin Zhou, Zhongfu Xiang, Lidu Zhao, Guicheng Chen, Tao Li, Jinyu Zhu, Kaixin Hu
Summary: This research presents a method for generating high-precision and fast RC bridges with chambers for geometric digital twin (gDT) using terrestrial laser scanning. The proposed method includes a fast point cloud data collection technique, Euclidean clustering and grid segmentation algorithms, and a framework based on the Dynamo-Revit reverse modelling method. The feasibility and accuracy of the method are validated through a comparison between the generated gDT model and the point cloud model.
Article
Environmental Sciences
Sukant Chaudhry, David Salido-Monzu, Andreas Wieser
Summary: The study presents a simple model for predicting the resolution capability in a laser scanning point cloud, specifically focusing on the angular direction. It utilizes an elliptical Gaussian beam for quantification and verifies the approximation of RC while considering scanning resolution. The model is accessible and supports assessing the suitability of specific scanners or scanning parameters for different applications.
Article
Biodiversity Conservation
Shun Li, Tianming Wang, Zhengyang Hou, Yinan Gong, Limin Feng, Jianping Ge
Summary: Forest understory vegetation is crucial for providing food, nutrition, and habitat for wildlife. Terrestrial Laser Scanning (TLS) has the potential to improve the accuracy of predicting understory biomass and monitoring biomass changes under the influence of wildlife.
ECOLOGICAL INDICATORS
(2021)
Article
Geography, Physical
Xufei Wang, Zexin Yang, Xiaojun Cheng, Jantien Stoter, Wenbing Xu, Zhenlun Wu, Liangliang Nan
Summary: In this research, an automatic, robust, and efficient method for registering forest point clouds is proposed. The approach locates tree stems and matches them based on their relative spatial relationship to determine the registration transformation. The algorithm requires no extra tree attributes and can align point clouds of large forest environments. Additionally, a new benchmark dataset is introduced for the development and evaluation of forest point cloud registration methods.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Construction & Building Technology
Xiaorui Li, Bisheng Yang, Fuxun Liang, Hongsheng Zhang, Yong Xu, Zhen Dong
Summary: This study develops a canopy air temperature predicting model at the city-block scale using urban 3D morphology parameters. The model accuracy is validated and used to investigate the effects of vertical landscape on the canopy air temperature in urban areas.
BUILDING AND ENVIRONMENT
(2023)
Article
Environmental Sciences
Xiao Ma, Guang Zheng, Xu Chi, Long Yang, Qiang Geng, Jiarui Li, Yifan Qiao
Summary: A generalizable approach to mapping large-scale distributions of building heights using GEDI-derived relative height metrics, optical data, and radar data is proposed. The approach was applied to the Yangtze River Delta region in China, revealing spatial distribution patterns of building heights and the effect of urbanization on mean building heights.
REMOTE SENSING OF ENVIRONMENT
(2023)
Editorial Material
Geography, Physical
Fan Zhang, Jan Dirk Wegner, Bisheng Yang, Yu Liu
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Geography, Physical
Weitong Wu, Jianping Li, Chi Chen, Bisheng Yang, Xianghong Zou, Yandi Yang, Yuhang Xu, Ruofei Zhong, Ruibo Chen
Summary: This paper proposes an adaptive frame length LiDAR odometry method (AFLI-Calib) for the external self-calibration of LiDAR-inertial measurement unit (IMU). The method dynamically adjusts the LiDAR frame length based on the motion state of sensors and the matching stability of scenes, and uses a linear-based continuous-time model for point cloud registration. Further optimization of trajectory and extrinsic parameters is achieved through multi-constraint optimization. The experiments demonstrate that the method achieves high accuracy and robustness.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Yifan Qiao, Guang Zheng, Zihan Du, Xiao Ma, Jiarui Li, L. Monika Moskal
Summary: Accurate classification of tree species is crucial for monitoring, managing, and conserving forest resources. This study utilized ALS data and hyperspectral data to extract four categories of indicators and applied them to the random forest algorithm for tree species classification, achieving an overall accuracy of 84.4%. By introducing individual-tree structure parameters into the constant allometric ratio (CAR) biomass model, biomass models for three tree species were established, and the model-fitting effects were improved after incorporating crown parameters.
Article
Geosciences, Multidisciplinary
Moritz Altmann, Katharina Ramskogler, Sebastian Mikolka-Floery, Madlene Pfeiffer, Florian Haas, Tobias Heckmann, Jakob Rom, Fabian Fleischer, Toni Himmelstoss, Norbert Pfeifer, Camillo Ressl, Erich Tasser, Michael Becht
Summary: Using digital monoplotting and historical terrestrial photographs, this study quantitatively analyzes surface changes of a Little Ice Age lateral moraine section over a 130-year period (1890-2020). The results show continuous expansion of the gully system and initial expansion of vegetation-covered areas until 1953, followed by a decrease due to large-scale erosion within the gully system. The study also concludes that land-cover development was influenced by temperature and precipitation changes.
Article
Environmental Sciences
Akbar Hossain Kanan, Francesco Pirotti, Mauro Masiero, Md Masudur Rahman
Summary: This study aims to analyze the potential impacts of sea level rise on dry land inundation in the Sundarbans area. The results show that under different scenarios of sea level rise, a significant amount of land in the Sundarbans could be flooded by 2100. While the direct impact of sea level rise on inundation is limited, indirect threats and human disturbances are expected to be major drivers of degradation in the Sundarbans by the end of the twenty-first century.
Article
Biodiversity Conservation
Michele Dalponte, Ruggero Cetto, Daniele Marinelli, Davide Andreatta, Cristina Salvadori, Francesco Pirotti, Lorenzo Frizzera, Damiano Gianelle
Summary: This study explores the spectral separability of different stages of spruce bark beetle infestation using Planet imagery at individual tree level. The results show that there are significant differences in spectral bands and indexes between healthy trees and those in the red-stage of infestation, as well as between healthy trees and those in the green-attack stage at the end of the summer.
ECOLOGICAL INDICATORS
(2023)
Article
Forestry
Federica Romagnoli, Alberto Cadei, Maximiliano Costa, Davide Marangon, Giacomo Pellegrini, Davide Nardi, Mauro Masiero, Laura Secco, Stefano Grigolato, Emanuele Lingua, Lorenzo Picco, Francesco Pirotti, Andrea Battisti, Tommaso Locatelli, Kristina Blennow, Barry Gardiner, Raffaele Cavalli
Summary: Windstorms have significant impacts on European forests, influencing various dimensions such as ecology, operations, geomorphology, economy, and socio-cultural aspects. However, current literature mainly focuses on specific aspects and lacks a comprehensive understanding. An interdisciplinary and systemic approach is needed to analyze and address the cascade effects and interconnections among these dimensions in post-windstorm dynamics.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Zhigang Tu, Zhisheng Huang, Yujin Chen, Di Kang, Linchao Bao, Bisheng Yang, Junsong Yuan
Summary: In this paper, a method for reconstructing accurate and consistent 3D hands from a monocular video is presented. By utilizing the information from the detected 2D hand keypoints and the image texture, the requirement on 3D hand annotation is reduced or eliminated. A self-supervised 3D hand reconstruction model, S(2)HAND, is proposed to estimate pose, shape, texture, and the camera viewpoint. Additionally, S(2)HAND(V) uses motion, texture, and shape consistency to further improve the accuracy and consistency of hand poses, shapes, and textures in video training data.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Haiping Wang, Yuan Liu, Qingyong Hu, Bing Wang, Jianguo Chen, Zhen Dong, Yulan Guo, Wenping Wang, Bisheng Yang
Summary: We propose RoReg, a novel point cloud registration framework that takes advantage of orientation descriptors and estimated local rotations in the registration process. Previous methods overlook the importance of descriptor orientations, focusing only on rotation-invariant descriptors. In this study, we demonstrate the usefulness of oriented descriptors and estimated local rotations in feature description, detection, matching, and transformation estimation. Through the development of a novel oriented descriptor RoReg-Desc and the use of estimated local rotations, we improve registration performance with a rotation-guided detector, rotation coherence matcher, and one-shot-estimation RANSAC. Extensive experiments show that RoReg achieves state-of-the-art results on popular datasets and generalizes well to the outdoor ETH dataset. Furthermore, we provide in-depth analysis on each component of RoReg to validate the benefits of oriented descriptors and estimated local rotations.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Geography, Physical
Yuhao Li, Xianghong Zou, Tian Li, Sihan Sun, Yuan Wang, Fuxun Liang, Jiangping Li, Bisheng Yang, Zhen Dong
Summary: In this paper, a method called MuCoGraph is proposed to correct the position inconsistency of mobile laser scanning (MLS) point clouds. This method introduces multi-scale constraints and formulates an enhanced pose graph to establish correct correspondences and correct the position inconsistency in revisited areas. The experiments demonstrate that the proposed method shows good robustness and effectiveness on three datasets.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Shirong Cai, Kunlong Niu, Xiaolin Mu, Xiankun Yang, Francesco Pirotti
Summary: This study analyzed the spatiotemporal changes in extreme precipitation in the Pearl River Basin using the long-term APHRODITE dataset. The results showed an increasing trend in annual and seasonal precipitation, with different indices exhibiting different changes in different seasons and regions. The findings are important for flood mitigation, natural hazard control, and water resources management in the Pearl River Basin.
Article
Environmental Sciences
Philipp Glira, Christoph Weidinger, Johannes Otepka-Schremmer, Camillo Ressl, Norbert Pfeifer, Michaela Haberler-Weber
Summary: Nonrigid registration is a significant challenge in point cloud processing with diverse applications. This paper presents a new method using piecewise tricubic polynomials to model nonrigid deformations, offering several advantages over existing methods.
Article
Remote Sensing
Zengxin Yun, Guang Zheng, Monika Moskal, Jiarui Li, Peng Gong
Summary: This study successfully extracted the waveforms of overstory and understory in multi-layer forests using GEDI data and investigated the effects of canopy cover, overstory height, terrain slope, and geolocation on forest stratification. The results showed significant impacts of these factors on forest structure.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)