Review
Environmental Sciences
Nosheen Munir, Mohammad Awrangjeb, Bela Stantic
Summary: Electricity is now indispensable, and power lines are crucial in modern societies. Remote sensing platforms, including satellite and aerial images, thermal images, and LiDAR points, are used for the inspection of power lines. Among these technologies, LiDAR surveying has become popular due to its active and weather-independent nature. This article examines different methods for power line extraction and reconstruction using LiDAR scanning systems, providing guidelines for future research.
Article
Environmental Sciences
Peng Wang, Ruqin Zhou, Chenguang Dai, Hanyun Wang, Wanshou Jiang, Yongsheng Zhang
Summary: LiDAR odometry is crucial for autonomous driving, but existing methods suffer from efficiency and accuracy issues due to the characteristics of point clouds in urban road scenes and interference from dynamic objects. To address these issues, a simulation-based self-supervised line extraction method is proposed, which reduces the input and improves the accuracy and efficiency of odometry.
Article
Environmental Sciences
Leyang Zhao, Li Yan, Xiaolin Meng
Summary: This study introduces an algorithm for extracting street curbs from mobile LiDAR data to address complex scenarios and improve the accuracy and reliability of the extraction results.
Article
Chemistry, Analytical
Filippo Accomando, Andrea Vitale, Antonello Bonfante, Maurizio Buonanno, Giovanni Florio
Summary: Compensating for magnetic and electromagnetic interference in drone-borne magnetometry surveys is a main challenge. Research has shown that suspending the magnetometer at a certain distance from the drone or below the drone can be effective solutions. By filtering drone-generated noise through CWT analysis, high quality data can be obtained, and the optimal flight solution can be chosen based on survey target and flight conditions.
Article
Environmental Sciences
Zhenyang Hui, Zhuoxuan Li, Dajun Li, Yanan Xu, Yuqian Wang
Summary: This paper proposes a self-adaptive filtering method based on object primitive global energy minimization for processing large-scale and complicated urban environments in airborne LiDAR datasets. By generating a mode graph and defining an energy function based on it, the filtering process is transformed into iterative global energy minimization. Experimental results show that the developed filter outperforms three classical filtering methods in terms of total error and Kappa coefficient.
Article
Environmental Sciences
Hangkai You, Shihua Li, Yifan Xu, Ze He, Di Wang
Summary: Tree information in urban areas is vital in various fields, and ALS is efficient in acquiring spatial information. This paper proposes a new point-based method for tree extraction, based on 3D morphological features, which has been proven effective in complex urban scenes. The method showed high accuracy in extracting trees from ALS data, making it suitable for urban area studies with only one adjustable parameter.
Article
Environmental Sciences
Yulin Gong, Xuejian Li, Huaqiang Du, Guomo Zhou, Fangjie Mao, Lv Zhou, Bo Zhang, Jie Xuan, Dien Zhu
Summary: The accurate classification of tree species is crucial for sustainable forest management and biodiversity monitoring. This study proposes a new intensity frequency feature for fine classification of eight tree species using UAV LiDAR. The results demonstrate that this new feature can serve as a comprehensive and effective intensity feature for tree species classification.
Article
Environmental Sciences
Nikolas Angelou, Mikael Sjoholm
Summary: Wind lidars are used in wind turbines to monitor inflow and enhance data reliability and monitoring efficiency. A new method based on modeling the radial speed contribution generated by the turbine blades is proposed to distinguish between wind and blade signals.
Article
Environmental Sciences
Marek Siranec, Marek Hoeger, Alena Otcenasova
Summary: This study systematically analyzes the accuracy of sag recalculation affected by input parameter inaccuracies, emphasizing the importance of considering sag deviation during safety assessment processes.
Article
Computer Science, Interdisciplinary Applications
Alberto M. Esmoris, David L. Vilarino, David F. Arango, Francisco-Alberto Varela-Garcia, Jose C. Cabaleiro, Francisco F. Rivera
Summary: This paper proposes two complementary LiDAR-based algorithms for accurately characterizing different elements in urban environments. The first algorithm is a novel profiling method robust to noise and obstacles, accurately characterizing the curvature, slope, and height of sidewalks, obstacles, and defects. The second algorithm provides a detailed quantitative summary of the state of zebra crossings, including location, geometry, and road marking information. The results can assist in the maintenance and improvement of urban roads, particularly in enhancing the quality and safety of pedestrian routes.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Geography, Physical
Ying Quan, Mingze Li, Yuanshuo Hao, Jianyang Liu, Bin Wang
Summary: This study used a combination of UAV-borne LiDAR and hyperspectral data to classify 11 common tree species in a natural secondary forest in Northeast China. The most valuable feature sets were selected using a hybrid approach and the random forest algorithm was used for classification. The results showed that combining LiDAR and hyperspectral data produced the highest classification accuracy (75.7%). The mean intensity of single returns and the visible atmospherically resistant index for red-edge band were found to be the most influential features. The selected features were robust under certain conditions. This study demonstrates the capabilities of UAV-borne LiDAR and hyperspectral data for tree species discrimination in natural secondary forests.
GISCIENCE & REMOTE SENSING
(2023)
Article
Environmental Sciences
Zexin Lv, Xiaolan Qiu, Yao Cheng, Songtao Shangguan, Fangfang Li, Chibiao Ding
Summary: Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) has many useful applications, especially in forest areas. However, there are fewer studies on the application of PolInSAR in urban areas compared with that in forest areas. In this paper, a processing method for a Ku-band multi-rotor-UAV-borne PolInSAR is proposed, and height inversion results in an urban area are analyzed using data from the Fudan campus in Shanghai. The preliminary results show that this method has potential for height inversion of urban targets.
Article
Environmental Sciences
Haiming Qin, Weiqi Zhou, Wenhui Zhao
Summary: This study examined the efficacy of small-footprint full-waveform LiDAR data in urban land cover classification. By decomposing the waveform data and extracting features, a random forest classifier was used to achieve high classification accuracy. The results indicate that full-waveform LiDAR data and the proposed features play important roles in urban land cover classification.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Francisco Rodriguez-Gomez, Jose del Campo-Avila, Marta Ferrer-Cuesta, Llanos Mora-Lopez
Summary: Urban sustainability is crucial in addressing climate change, and replacing polluting energy with renewable energy is fundamental for achieving this goal. This paper presents an open-source software that helps identify optimal locations for photovoltaic panel installations in cities and demonstrates its potential applications.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Geochemistry & Geophysics
Yantian Wang, Xiaohuan Xi, Cheng Wang, Xuebo Yang, Pu Wang, Sheng Nie, Meng Du
Summary: A robust method for directly estimating crown base height (CBH) from UAV LiDAR data was proposed in this study. The method, which included two significant skills of understory vegetation removal and kernel densification, could better deal with the problem of understory, trunk, and noise points caused by high-density UAV data. The results showed that the method performed slightly better than a previous simple model, demonstrating high precision for measuring CBH of low trees.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
