Article
Environmental Sciences
Zhenyu Zhang, Jian Wang, Zhiyuan Li, Youlong Zhao, Ruisheng Wang, Ayman Habib
Summary: This paper proposes an optimization method for individual tree segmentation (ITS) based on Gaussian mixture model for airborne LiDAR data. It effectively addresses the accuracy issue and under-segmentation of individual trees in high-density multistoried mixed forest areas. Experimental results demonstrate that the proposed method outperforms the traditional mean shift algorithm in terms of accuracy and under-segmentation.
Article
Environmental Sciences
Yihan Pu, Dandan Xu, Haobin Wang, Xin Li, Xia Xu
Summary: Accurate and efficient individual tree detection and segmentation (ITDS) using UAV-LiDAR in broadleaved forests is challenging due to the irregular and overlapped canopies. In this study, we developed an efficient and accurate ITDS framework for broadleaved forests based on UAV-LiDAR point clouds, which includes ITD, initial ITS, and a refining process. The results show that this framework provides accurate results for ITDS and can be applied to single-phase point clouds in the future.
Article
Environmental Sciences
Gang Shao, Songlin Fei, Guofan Shao
Summary: Accurate tree inventory is important for sustainable forest planting and management. In this study, a stepwise tree detection approach was proposed, using horizontal point density and vertical structure profiles. The study demonstrated that horizontal point density provides critical information to locate individual trees, while vertical structure profiles can identify spreading branches and deliquescent crowns.
Article
Forestry
Xiangyu Chen, Kunyong Yu, Shuhan Yu, Zhongyang Hu, Hongru Tan, Yichen Chen, Xiang Huang, Jian Liu
Summary: This study proposes an improved K-means algorithm with local maxima and height weighting methods for segmenting Chinese fir plantations. The research results show that this algorithm has higher accuracy compared to traditional algorithms and can be applied to Chinese fir plantations of different age groups.
Article
Environmental Sciences
Qingda Chen, Tian Gao, Jiaojun Zhu, Fayun Wu, Xiufen Li, Deliang Lu, Fengyuan Yu
Summary: Accurate individual tree segmentation is important for forest management and the study of forest ecosystems. This study introduced a new UAV-LiDAR dataset, FULD, which fused leaf-off and leaf-on point clouds, to assess its benefits for tree segmentation and height estimation in dense deciduous forests. The results showed that the combination of FULD and the layer stacking segmentation algorithm produced the highest accuracies across all forest types and improved tree height estimation.
Article
Environmental Sciences
Romain Neuville, Jordan Steven Bates, Francois Jonard
Summary: The integration of UAVs with LiDAR technology offers new possibilities for efficient and accurate monitoring of forest stand structures. By improving the HDBSCAN clustering algorithm and utilizing PCA, tree stems can be effectively segmented and their diameters estimated. Results suggest that this methodology can accurately detect tree stems and retrieve tree metrics without the need for site-specific parameters, showcasing potential for minimizing errors and improving tree detection and metrics retrieval.
Article
Environmental Sciences
Zhouyang Hua, Sheng Xu, Yingan Liu
Summary: This paper proposes an individual tree segmentation method called Shadow-cut to extract the contours of street tree point clouds. The method includes using support vector machine for tree region separation, calculating the optimal projection, and using image segmentation algorithm to extract edges. Experiments demonstrate that this method achieves high accuracy and completeness on LiDAR data.
Article
Environmental Sciences
Bin Wang, Jianyang Liu, Jianing Li, Mingze Li
Summary: Based on UAV LiDAR and hyperspectral data, this study designed different classification schemes to explore the effects of different data sources, classifiers, and canopy morphological features on the classification of single tree species. The results showed that multisource remote sensing data had higher classification accuracy than single data source. Random forest and support vector machine classifiers had similar classification accuracies, with overall accuracies above 78%. The BP neural network classifier had the lowest classification accuracy of 75.8%. The addition of UAV LiDAR-extracted canopy morphological features slightly improved the classification accuracy of all three classifiers for tree species.
Article
Environmental Sciences
Chong Zhang, Jiawei Zhou, Huiwen Wang, Tianyi Tan, Mengchen Cui, Zilu Huang, Pei Wang, Li Zhang
Summary: High-resolution UAV imagery combined with a convolutional neural network approach is effective in accurately measuring forestry ecosystems. In this study, a new method for individual tree segmentation and identification based on the improved Mask R-CNN is proposed, which shows advantages in broadleaf canopy segmentation and number detection.
Article
Environmental Sciences
Kaisen Ma, Yujiu Xiong, Fugen Jiang, Song Chen, Hua Sun
Summary: This paper proposes a new method for detecting and segmenting individual trees in forest ecosystems using high-density UAV-scanned laser point clouds. The results demonstrate that the proposed VPCDM can provide an innovative data segmentation model for LiDAR-based high-density point clouds and enhance the accuracy of parameter extraction.
Article
Geography, Physical
Sebastian Dersch, Marco Heurich, Nina Krueger, Peter Krzystek
Summary: This paper introduces a novel integrated single tree segmentation method for automatic field inventory using lidar, with stem detection playing a key role. Experimental results show that automatic stem detection successfully locates stems, and the integration of stem detection significantly improves the accuracy of tree segmentation. The overall improvement in terms of F-scores is up to 15% and 6% for reference data from visual inspection and field measurements, respectively.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Plant Sciences
Xiaofeng Wang, Yi Wang, Chaowei Zhou, Lichang Yin, Xiaoming Feng
Summary: Fine monitoring of tree species using UAV data and object-oriented classification at the single tree scale achieved high accuracy in detecting surface fragments, improving classification effects, and avoiding salt and pepper noise compared to traditional methods.
URBAN FORESTRY & URBAN GREENING
(2021)
Article
Environmental Sciences
Kuo Liao, Yunhe Li, Bingzhang Zou, Dengqiu Li, Dengsheng Lu
Summary: This study compared the accuracy of tree height measurements using different methods and the influence of allometric models on tree volume estimation accuracy. The results showed significant impacts of different measurement methods on tree volume calculations, and incorporating UAV Lidar data with DBH field measurements can effectively improve tree volume estimation accuracy.
Article
Environmental Sciences
Robin J. L. Hartley, Sadeepa Jayathunga, Peter D. Massam, Dilshan De Silva, Honey Jane Estarija, Sam J. Davidson, Adedamola Wuraola, Grant D. Pearse
Summary: Phenotyping has been used in horticultural industries for decades, but it was less accessible for tree breeders until recently when affordable and non-destructive technologies like mobile laser scanners became available. In this study, a high-density mobile laser scanner was used to derive phenotypic measurements from mature Pinus radiata, and the results showed strong agreement with field measurements. The findings suggest that MLS technology holds strong potential for advancing forest phenotyping and tree measurement, even in mature forests.
Article
Remote Sensing
Kaisen Ma, Chaokui Li, Fugen Jiang, Liangliang Xu, Jing Yi, Heqin Huang, Hua Sun
Summary: A novel point cloud normalization method was proposed to detect treetops in steep terrain areas. The treetop detection displacement model was improved for quantifying treetop displacements and tree height changes. This study made important contributions to the development of accurate treetop position identification and tree height parameter extraction methods.
Article
Mathematics
I. Mezo, J. -Y. Lu
Summary: This study focuses on estimating the best constants for the ratio of two equivalent but visually different norms in the logarithm space L-p log L.
ANALYSIS MATHEMATICA
(2022)
Article
Astronomy & Astrophysics
J. Y. Lu, Y. T. Xiong, K. Zhao, M. Wang, J. Y. Li, G. S. Peng, M. Sun
Summary: In this paper, a novel bimodal model is proposed to predict a complete sunspot cycle based on comprehensive precursor information. The model combines the implicit and geometric information of the solar cycle with the traditional precursor method and employs a multivariate linear approach, achieving a good performance in the prediction.
ASTROPHYSICAL JOURNAL
(2022)
Article
Multidisciplinary Sciences
Zhifeng Liu, Feng Ding, Jianyong Lu, Yue Zhou, Hetao Chu
Summary: This paper proposes two novel deep learning models, namely BLSTM-ATT and BLSTM-TRA models, for wind speed prediction, which outperform the ECMWF model in terms of prediction accuracy.
COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES
(2022)
Article
Geosciences, Multidisciplinary
Yue Zhou, Jih-Hong Shue, Hiroshi Hasegawa, Jianyong Lu, Ming Wang, Hanxiao Zhang
Summary: Using data from the ARTEMIS spacecraft near the Moon, this study statistically analyzes the properties of Kelvin-Helmholtz (KH) waves and the thickness of initial velocity shear layers on the magnetopause at lunar distance. The results show that at lunar distance, the KH waves have a larger wavelength and thickness compared to those at near-Earth magnetopause. The ratio of wavelength to thickness at lunar distance exceeds the range predicted by the linear theory, indicating that the observed KH waves are not consistent with the fastest growing mode according to linear theory. This study provides insights into the generation and development of KH waves at lunar distance.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Astronomy & Astrophysics
Guangshuai Peng, Jianyong Lu, Hua Zhang, Xiaoxin Zhang, Guanglin Yang, Zhiqiang Wang, Chao Shen, Meng Yi, Yuhang Hao
Summary: This study utilizes machine learning to establish a prediction model based on Gaussian process regression (GPR) for accurate forecast of high-energy electron flux. The GPR model outperforms other typical models and intelligence models in terms of flux forecast and shows relatively better prediction of extreme disturbed events.
ASTROPHYSICS AND SPACE SCIENCE
(2022)
Article
Environmental Sciences
Yufeng Tian, Jingyuan Li, Chaolei Yang, Jingqi Cui, Fuzhen Shen, Jianyong Lu, Shiping Xiong, Guanchun Wei, Zheng Li, Hua Zhang, Guanglin Yang, Yewen Wu, Zong Wei, Shuwen Jiang, Jingrui Yao, Jingye Wang, Zhixin Zhu
Summary: This study investigates the impact of the annual solar eclipse on surface ozone concentration. The results show that during the eclipse, ozone concentration decreases by more than 40% for a period of 20 hours. At the same time, there is a decrease in solar radiation and temperature, while relative humidity increases. Ozone concentration shows a positive correlation with temperature and a negative correlation with relative humidity.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Astronomy & Astrophysics
Guanchun Wei, Jianyong Lu, Wenbin Wang, Yufeng Tian, Jingyuan Li, Shiping Xiong, Meng Sun, Fuzhen Shen, Zheng Li, Hua Zhang, Jingqi Cui, Chaolei Yang, Jingrui Yao, Shuwen Jiang, Zhixin Zhu, Jingye Wang
Summary: Using SABER temperature data, we investigated the response of the mesosphere and lower thermosphere to two medium geomagnetic storms with different durations. The temperature increase in the Southern hemisphere during the longer-duration storm was 40 K, while it was less than 10 K for the shorter-duration event. Simulations showed that longer-duration storms result in more particles and energy input, leading to stronger forces and faster horizontal wind, which then cause greater temperature increases in the MLT region through adiabatic heating/cooling and vertical advection. Therefore, the duration of the storm is important for understanding the temperature response in the MLT region.
Article
Astronomy & Astrophysics
H. Y. Sui, M. Wang, J. Y. Lu, Y. Zhou, J. Wang
Summary: Based on the MAVEN mission, the intensity and orientation of the IMF have been found to affect the location and shape of the Martian bow shock. When the IMF intensity increases, the bow shock moves linearly away from Mars. Under the radial IMF condition, the subsolar and flank regions of the Martian bow shock are closer to Mars. When the Y component of the IMF is dominant, the cross section of the Martian bow shock elongates in the north-south direction.
ASTROPHYSICAL JOURNAL
(2023)
Article
Astronomy & Astrophysics
Shiping Xiong, Jingyuan Li, Guanchun Wei, Jianyong Lu, Yufeng Tian, Xiaoping Zhang, Shuai Fu, Meng Sun, Zheng Li, Hua Zhang, Jingqi Cui, Shuwen Jiang, Chaolei Yang
Summary: Observations from SABER and simulations from WACCM-X were used to analyze the effects of solar proton events (SPEs) on mesospheric ozone at high latitudes. The results showed that high-latitude mesospheric ozone decreased significantly during SPEs, with a larger decrease in the North Hemisphere compared to the South Hemisphere. The simulations also revealed a significant increase in NOx and HOx during SPEs, with the changes exhibiting hemispheric asymmetries.
SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
H. X. Zhang, J. Y. Lu, M. Wang
Summary: A parametric study is conducted to investigate the energy transfer of the solar wind across the magnetopause entering the magnetosphere. The study analyzes the distribution of mechanical and electromagnetic energy under different interplanetary magnetic field (IMF) orientations and compares their characteristics. The results show that the energy transfer and interaction at the magnetopause vary with the IMF orientation, and the energy distribution exhibits different patterns under different IMFs.
SCIENTIFIC REPORTS
(2023)
Article
Meteorology & Atmospheric Sciences
Jingyuan Li, Guanchun Wei, Wenbin Wang, Qinshun Luo, Jianyong Lu, Yufeng Tian, Shiping Xiong, Meng Sun, Fuzhen Shen, Tao Yuan, Xiaoping Zhang, Shuai Fu, Zheng Li, Hua Zhang, Chaolei Yang
Summary: This study reveals the nature and mechanisms of temperature variations in the mesosphere and lower thermosphere (MLT) at high latitudes. The temperature in the MLT region shows increases and decreases at different time intervals during geomagnetic storms. The main drivers of these temperature changes are adiabatic heating/cooling and vertical advection.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2023)
Article
Astronomy & Astrophysics
M. Wang, K. Xu, J. Y. Lu, M. X. Yin, H. Y. Sui, Z. J. Guan, J. Q. Zhang
Summary: In this paper, the effect of interplanetary magnetic field (IMF) intensity and orientation on the Martian magnetic pileup boundary (r(0)) and pressure balance is studied using a three-dimensional multispecies MHD model. The results show that the magnitude of the Y or Z-component of IMF influences r(0), while the radial IMF component has little effect. The ratio of the IMF Y and Z-components to IMF intensity controls the impact of the IMF cone angle on r(0) and compression degree of the magnetic field. The difference in the IMF effect on the size of the Martian magnetic pileup boundary reveals different solar wind interactions with a magnetized and unmagnetized planet.
ASTROPHYSICAL JOURNAL
(2023)
Article
Geosciences, Multidisciplinary
Xi Wang, Jianyong Lu, Ming Wang, Yue Zhou, Yufei Hao
Summary: This paper investigates the influence of high-speed jets (HSJs) on the position of the magnetopause under long-term radial interplanetary magnetic fields (IMFs). The study finds that under quasi-radial IMF conditions, the magnetopause expands and then is locally indented by HSJs.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Astronomy & Astrophysics
Haibing Ruan, Jiuhou Lei, Jianyong Lu, Fen Tang
Summary: An empirical model of total electron content is developed based on the superposition of the tide-like components. The seasonal and interannual behaviors in the amplitudes and phases of tide-like signatures in the ionosphere are reproduced. The developed empirical model has a good performance in reconstructing the variabilities in the global ionosphere.
SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS
(2023)
Article
Geosciences, Multidisciplinary
Hao Zhang, YaBing Wang, JianYong Lu
Summary: In this study, we conducted a statistical analysis of trunk-like structures observed in He+ and O+ in the inner magnetosphere using observations from the HOPE instrument onboard Van Allen Probe A. The study revealed that these trunk structures exhibit an energy decrease towards Earth, specific spatial distribution, and dependence on different geomagnetic indices.
EARTH AND PLANETARY PHYSICS
(2022)