Article
Multidisciplinary Sciences
Renato Juliano Martins, Emil Marinov, M. Aziz Ben Youssef, Christina Kyrou, Mathilde Joubert, Constance Colmagro, Valentin Gate, Colette Turbil, Pierre-Marie Coulon, Daniel Turover, Samira Khadir, Massimo Giudici, Charalambos Klitis, Marc Sorel, Patrice Genevet
Summary: The article introduces an advanced LiDAR technology that achieves a large field of view and high frame rate by using ultrafast low FoV deflectors and large area metasurfaces, enabling simultaneous peripheral and central imaging zones. The use of this technology with advanced learning algorithms offers potential improvements in perception and decision-making processes of ADAS and robotic systems.
NATURE COMMUNICATIONS
(2022)
Article
Environmental Sciences
Melissa Latella, Fabio Sola, Carlo Camporeale
Summary: This study introduces a novel LiDAR algorithm for accurate individual tree detection in deciduous forests, with low sensitivity to parameter setup and applicability in low-density point cloud analysis. Additionally, the algorithm demonstrates potential for more complex tools in forest modeling and management.
Article
Multidisciplinary Sciences
Fanglin Bao, Xueji Wang, Shree Hari Sureshbabu, Gautam Sreekumar, Liping Yang, Vaneet Aggarwal, Vishnu N. N. Boddeti, Zubin Jacob
Summary: Machine perception uses advanced sensors to collect information for situational awareness. State-of-the-art machine perception faces difficulties with increasing number of intelligent agents. Exploiting omnipresent heat signal could be a new frontier for scalable perception. The proposed heat-assisted detection and ranging (HADAR) overcomes the challenge of ghosting and shows promising results compared to AI-enhanced thermal sensing.
Review
Nanoscience & Nanotechnology
Inki Kim, Renato Juliano Martins, Jaehyuck Jang, Trevon Badloe, Samira Khadir, Ho-Youl Jung, Hyeongdo Kim, Jongun Kim, Patrice Genevet, Junsuk Rho
Summary: This review discusses the technological challenges of applying nanophotonics in LiDAR, the basic principles of LiDAR and overcoming hardware limitations, the characteristics of nanophotonic platforms, and the future trends in integrating nanophotonic technologies into commercially viable, fast, ultrathin, and lightweight LiDAR systems.
NATURE NANOTECHNOLOGY
(2021)
Article
Environmental Sciences
Aaron M. Sparks, Mark Corrao, Alistair M. S. Smith
Summary: This study evaluated the accuracy of seven individual tree detection methods in coniferous forest stands, showing that higher ALS pulse density data resulted in higher ITD accuracy. Omission errors were mainly related to stand density, and the use of simple canopy height model methods could reduce omission errors.
Article
Multidisciplinary Sciences
Wai Yi Chau, Cheng Ning Loong, Yu-Hsing Wang, Siu-Wai Chiu, Tun Jian Tan, Jimmy Wu, Mei Ling Leung, Pin Siang Tan, Ghee Leng Ooi
Summary: This study explores the use of a novel multi-beam flash LiDAR sensor to measure the three-dimensional motion of trees and proposes a framework to construct the motions of tree skeletons and derive their dynamic properties. The feasibility of the framework is justified through experiments on different trees under pull-and-release tests and typhoon conditions.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2022)
Article
Environmental Sciences
Jeremy Arkin, Nicholas C. Coops, Lori D. Daniels, Andrew Plowright
Summary: Accurate estimation of forest canopy fuels is crucial for wildfire prediction and mitigation. This study examines the ability of LiDAR point clouds from RPAS to characterize the vertical arrangement and volume of crown fuels, showing good match between extracted and manually measured clusters but a tendency for overprediction of lower boundaries in the automated method.
Article
Forestry
Aaron M. Sparks, Alistair M. S. Smith
Summary: In this study, the ability of the ForestView(R) algorithm to detect individual trees, classify tree species, live/dead status, canopy position, and estimate height and DBH in a complex forest was assessed. The algorithm showed high accuracy in stands with lower canopy cover but lower accuracy in stands with higher canopy cover.
Article
Remote Sensing
Guoqing Zhou, Xiang Zhou, Youjian Song, Donghui Xie, Long Wang, Guangjian Yan, Minglie Hu, Bowen Liu, Weidong Shang, Chenghu Gong, Cheng Wang, Huaguo Huang, Yiqiang Zhao, Zhigang Liu, Guangyun Zhang, Xing Wang, Sheng Nie, Mao Ye, Songlin Liu, Qiaofeng Tan, Ke Li, Fengyuan Wei, Wei Su, Jinshou Tian, Qingkang Ai, Lvyun Yang, Bo Song, Jiasheng Xu, Lieping Zhang, Wei Li, Ruirui Wang, Hao Xue, Hao Dong, Ying Yu, Hongtao Wang
Summary: This paper presents an innovative study on the design of airborne-oriented supercontinuum laser hyperspectral (SCLaHS) LiDAR, which is capable of collecting rich spectral data and three-dimensional point cloud data with high spectral and spatial resolution.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Chemistry, Analytical
Jean-Francois Prieur, Benoit St-Onge, Richard A. Fournier, Murray E. Woods, Parvez Rana, Daniel Kneeshaw
Summary: This paper compares the applicability of different types of airborne laser scanning systems for species identification at the individual tree level and finds that the overall accuracies of the methods are similar across all sensor types.
Article
Plant Sciences
Jens van der Zee, Alvaro Lau, Alexander Shenkin
Summary: This study quantified the characteristic of crown surface complementarity in trees displaying crown shyness using LiDAR-derived tree point clouds. The research found that trees with overlapping crowns scored lower in surface complementarity values compared to non-overlapping pairs, and the average slenderness of tree pairs correlated positively with their surface complementarity score. The 3-D metric developed in this study revealed how trees adapt the shape of their crowns to those of adjacent trees and how this is linked to the slenderness of the trees.
Article
Geochemistry & Geophysics
Yuanshuo Hao, Faris Rafi Almay Widagdo, Xin Liu, Yongshuai Liu, Lihu Dong, Fengri Li
Summary: In this study, a novel hierarchical region-merging algorithm was developed for individual tree segmentation from aerial point clouds. The proposed method achieved good performance, especially for high-density forests.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Forestry
Zhenyang Hui, Zhaochen Cai, Peng Xu, Yuanping Xia, Penggen Cheng
Summary: This paper developed two new kinds of feature vectors, fractal geometry-based feature vectors and QSM-based feature vectors, to improve the performance of tree species classification. By conducting feature vector dimension reduction using the CART method, the developed feature vectors outperformed traditional learning methods and showed better performance compared to a relevant method. The results indicate the effectiveness of the fractal geometry-based and QSM-based feature vectors.
Article
Physics, Applied
Ryo Tetsuya, Takemasa Tamanuki, Hiroyuki Ito, Hiroshi Abe, Ryo Kurahashi, Miyoshi Seki, Minoru Ohtsuka, Nobuyuki Yokoyama, Makoto Okano, Toshihiko Baba
Summary: Photonic crystal waveguide slow-light grating can emit and steer optical beams, and is used as a beam scanner for light detection and ranging (LiDAR). Dividing the waveguide into multiple antennas in a serial array configuration improves reception performance.
APPLIED PHYSICS LETTERS
(2021)
Article
Green & Sustainable Science & Technology
Zahra Azizi, Mojdeh Miraki
Summary: The study found that the accuracy of tree detection is influenced by tree height and species, being most accurate in urban forests with homogenous even-aged structures and less accurate in uneven-aged stands.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2022)
Article
Environmental Sciences
Lei Xu, Jian Gong, Jiaming Na, Yuanwei Yang, Zhao Tan, Norbert Pfeifer, Shunyi Zheng
Summary: This study proposes a convergence diameter and radial dislocation detection method based on block-level fitting, which solves the accuracy degradation caused by the model error and point cloud incompletion. The experimental results showed that the method has good detection accuracy and is suitable for practical engineering applications.
Article
Environmental Sciences
Valeria-Ersilia Oniga, Ana-Ioana Breaban, Norbert Pfeifer, Maximilian Diac
Summary: The paper discusses a method for 3D building modeling based on oblique UAS images, using a low-cost drone to collect data over an urban area. The process includes various steps such as filtering ground points, classification, segmentation, plane creation, and 3D model reconstruction. The results show that the proposed pipeline is reliable, with a global accuracy of around 0.15 m for each modeled building.
Article
Environmental Sciences
Ana-Maria Loghin, Johannes Otepka-Schremmer, Camillo Ressl, Norbert Pfeifer
Summary: This paper proposes an approach to detect and estimate the periodic distortions of Pleiades tri-stereo imagery caused by satellite attitude oscillations. By re-projecting ground points onto satellite images using RPCs, the systematic height errors of satellite-based elevation models are computed and corrected. Experimental results show that the proposed method successfully removes the systematic elevation discrepancies and improves the overall accuracy of the elevation models.
Article
Environmental Sciences
Fariborz Ghorbani, Hamid Ebadi, Norbert Pfeifer, Amin Sedaghat
Summary: This research presents an automated approach for 3D keypoint detection to control the quality, spatial distribution, and the number of keypoints. The proposed method combines different features and utilizes an Octree structure, showing proper performance in point cloud registration.
Article
Ecology
Jesper Erenskjold Moeslund, Kevin Kuhlmann Clausen, Lars Dalby, Camilla Flojgaard, Meelis Partel, Norbert Pfeifer, Markus Hollaus, Ane Kirstine Brunbjerg, Mat Disney, Jian Zhang
Summary: This study used a large plant dataset and lidar data to analyze the impact of habitat characteristics on plant dark diversity, and identified factors that should be considered by managers and policymakers in conservation and restoration projects.
REMOTE SENSING IN ECOLOGY AND CONSERVATION
(2023)
Article
Environmental Sciences
Ana-Ioana Breaban, Valeria-Ersilia Oniga, Constantin Chirila, Ana-Maria Loghin, Norbert Pfeifer, Mihaela Macovei, Alina-Mihaela Nicuta Precul
Summary: This paper presents a new methodology for improving the accuracy of point clouds using high-resolution satellite images. The method pays attention to the processing of local geoid and digital terrain model, and achieves accurate model results through field measurements and various correction methods.
Article
Biodiversity Conservation
Langning Huo, Joachim Strengbom, Tomas Lundmark, Per Westerfelt, Eva Lindberg
Summary: In sustainable forest resource management, establishing forest conservation areas is crucial for maintaining forest biodiversity. However, assessing the conservation value of forests can be challenging due to their large and remote nature. This study explores the use of dense airborne laser scanning (ALS) data to estimate conservation values, specifically focusing on identifying different types of indicator trees.
ECOLOGICAL INDICATORS
(2023)
Article
Environmental Sciences
Langning Huo, Eva Lindberg, Jonas Bohlin, Henrik Jan Persson
Summary: Detecting disease- or insect-infested forests early on is crucial, especially under conditions of climate change. This study aimed to determine when infested trees start to show an abnormal spectral response and to quantify the detectability of infested trees. Through a controlled experiment and field assessments, the study found that multispectral drone images were more effective in detecting infestations compared to field observations. The proposed Multiple Ratio Disease-Water Stress Indices (MR-DSWIs) also showed higher detection rates. The study concluded that 5-10 weeks after an attack is a suitable period for early stage infestation mapping.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Khrystyna Burshtynska, Svitlana Kokhan, Norbert Pfeifer, Maksym Halochkin, Iryna Zayats
Summary: In recent decades, floods in the Pre-Carpathian region of Ukraine have become more frequent, causing significant economic and environmental damage. This study aims to propose a methodology for hydrological modeling of riverbed sections with complex morphometric and hydrological characteristics. Using UAV imagery, a digital elevation model (DEM) is constructed, and factors such as cross-section distance and Manning coefficients are determined for accurate modeling. The research findings suggest that imaging during the leafless period is essential for achieving the required accuracy of the DEM.
Article
Environmental Sciences
Kenneth Olofsson, Johan Holmgren
Summary: A new algorithm for detecting branch attachments on stems based on a voxel approach and line object detection by a voting procedure is introduced. This algorithm can be used to evaluate the quality of stems by giving the branch density of each standing tree. The detected branches were evaluated using field-sampled trees. The algorithm detected 63% of the total amount of branch whorls and 90% of the branch whorls attached in the height interval from 0 to 10 m above ground. The suggested method could be used to create maps of forest stand stem quality data.
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
Forestry
S. Karvemo, L. Huo, P. Ohrn, E. Lindberg, H. J. Persson
Summary: In recent decades, Norway spruce forests in Europe have suffered from large-scale tree mortality caused by the spruce bark beetle, which is influenced by storm-felling events and periods of drought due to climate change. This study compared the infestation patterns and configuration of the bark beetles after a storm and a drought in southern Sweden, finding differences in infestation occurrence and size related to forest structures and climate. The study highlights the importance of understanding the drivers behind bark beetle infestations triggered by different factors to develop more accurate outbreak predictions.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Remote Sensing
Christoffer R. Axelsson, Eva Lindberg, Henrik J. Persson, Johan Holmgren
Summary: This study used airborne laser scanning with two wavelengths (green and near infrared) to scan a boreal forest. A two-step methodology was employed to classify species and estimate species-specific stem volumes at the level of individual tree crowns. The results showed that the use of the green channel improved the accuracy of species classification and stem volume estimation. Additionally, tree height was found to influence the classification results, with shorter trees being more difficult to classify correctly.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
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.