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1. SLAM integrated mobile mapping system in complex urban environments

Author:
Li, Shuaixin; Li, Guangyun; Wang, Li; Qin, Yuchu
Source:
ISPRS journal of photogrammetry and remote sensing 2020 v.166 pp. 316-332
ISSN:
0924-2716
Subject:
lidar,   etc   ; algorithms; urban areas;     Show all 3 Subjects
Abstract:
... In this paper, a SLAM-integrated MMS with the capability of efficient, consistent and robust mapping in complex environments where GNSS signal is intermittently lost is presented. The system is developed to take the feedback from mapping module to the localization module into account, which significantly improves the smoothness of the 6 DOF trajectory estimation. In particular, the complex mapping ...
DOI:
10.1016/j.isprsjprs.2020.05.012

2. A novel skyline context descriptor for rapid localization of terrestrial laser scans to airborne laser scanning point clouds

Author:
Liang, Fuxun; Yang, Bisheng; Dong, Zhen; Huang, Ronggang; Zang, Yufu; Pan, Yue
Source:
ISPRS journal of photogrammetry and remote sensing 2020 v.165 pp. 120-132
ISSN:
0924-2716
Subject:
lidar,   etc   ; algorithms; data collection;     Show all 3 Subjects
Abstract:
... By utilizing the airborne laser scanning (ALS) and terrestrial laser scanning (TLS), the land surface information from both top view and side view can be captured rapidly. However, due to the different perspective views, resolutions, and ranges, the automatic localization of multiple TLS scans to ALS is challenging. To address this issue, this paper proposes a novel skyline context-based method. F ...
DOI:
10.1016/j.isprsjprs.2020.04.018

3. KDA3D: Key-Point Densification and Multi-Attention Guidance for 3D Object Detection

Author:
Wang, Jiarong; Zhu, Ming; Wang, Bo; Sun, Deyao; Wei, Hua; Liu, Changji; Nie, Haitao
Source:
Remote Sensing 2020 v.12 no.11
ISSN:
2072-4292
Subject:
lidar,   etc   ; data collection; remote sensing;     Show all 3 Subjects
Abstract:
... In this paper, we propose a novel 3D object detector KDA3D, which achieves high-precision and robust classification, segmentation, and localization with the help of key-point densification and multi-attention guidance. The proposed end-to-end neural network architecture takes LIDAR point clouds as the main inputs that can be optionally complemented by RGB images. It consists of three parts: part-1 ...
DOI:
10.3390/rs12111895

4. A comparative assessment of the vertical distribution of forest components using full-waveform airborne, discrete airborne and discrete terrestrial laser scanning data

Author:
Crespo-Peremarch, Pablo; Fournier, Richard A.; Nguyen, Van-Tho; van Lier, Olivier R.; Ruiz, Luis Ángel
Source:
Forest ecology and management 2020 v.473 pp. 118268
ISSN:
0378-1127
Subject:
lidar,   etc   ; canopy; conifers; forests; spatial distribution; understory;     Show all 6 Subjects
Abstract:
... Laser scanning has the potential to accurately detect the vertical distribution of forest vegetative components. However, limitations are present and vary according to the system’s platform (i.e., terrestrial or airborne) and recording method (i.e., discrete return or full-waveform). Terrestrial configurations detect close objects (i.e., lower vegetation strata) in more detail while airborne confi ...
DOI:
10.1016/j.foreco.2020.118268

5. A multiclass TrAdaBoost transfer learning algorithm for the classification of mobile lidar data

Author:
He, Hanxian; Khoshelham, Kourosh; Fraser, Clive
Source:
ISPRS journal of photogrammetry and remote sensing 2020 v.166 pp. 118-127
ISSN:
0924-2716
Subject:
lidar,   etc   ; algorithms; data collection; learning; models;     Show all 5 Subjects
Abstract:
... A major challenge in the application of state-of-the-art deep learning methods to the classification of mobile lidar data is the lack of sufficient training samples for different object categories. The transfer learning technique based on pre-trained networks, which is widely used in deep learning for image classification, is not directly applicable to point clouds, because pre-trained networks tr ...
DOI:
10.1016/j.isprsjprs.2020.05.010

6. CoMask: Corresponding Mask-Based End-to-End Extrinsic Calibration of the Camera and LiDAR

Author:
Yin, Lu; Luo, Bin; Wang, Wei; Yu, Huan; Wang, Chenjie; Li, Chengyuan
Source:
Remote Sensing 2020 v.12 no.12
ISSN:
2072-4292
Subject:
lidar,   etc   ; algorithms; cameras; remote sensing; system optimization;     Show all 5 Subjects
Abstract:
... The integration of the camera and LiDAR has played an important role in the field of autonomous driving, for example in visual–LiDAR SLAM and 3D environment fusion perception, which rely on precise geometrical extrinsic calibration. In this paper, we proposed a fully automatic end-to-end method based on the 3D–2D corresponding mask (CoMask) to directly estimate the extrinsic parameters with high p ...
DOI:
10.3390/rs12121925

7. Roof Plane Segmentation from Airborne LiDAR Data Using Hierarchical Clustering and Boundary Relabeling

Author:
Li, Li; Yao, Jian; Tu, Jingmin; Liu, Xinyi; Li, Yinxuan; Guo, Lianbo
Source:
Remote Sensing 2020 v.12 no.9
ISSN:
2072-4292
Subject:
lidar,   etc   ; data collection; models; remote sensing;     Show all 4 Subjects
Abstract:
... The roof plane segmentation is one of the key issues for constructing accurate three-dimensional building models from airborne light detection and ranging (LiDAR) data. Region growing is one of the most widely used methods to detect roof planes. It first selects one point or region as a seed, and then iteratively expands to neighboring points. However, region growing has two problems. The first pr ...
DOI:
10.3390/rs12091363

8. Experimental Calibration of the Overlap Factor for the Pulsed Atmospheric Lidar by Employing a Collocated Scheimpflug Lidar

Author:
Mei, Liang; Ma, Teng; Zhang, Zhen; Fei, Ruonan; Liu, Kun; Gong, Zhenfeng; Li, Hui
Source:
Remote Sensing 2020 v.12 no.7
ISSN:
2072-4292
Subject:
lidar,   etc   ; aerosols; calibration; environmental monitoring; remote sensing;     Show all 5 Subjects
Abstract:
... Lidar techniques have been widely employed for atmospheric remote sensing during past decades. However, an important drawback of the traditional atmospheric pulsed lidar technique is the large blind range, typically hundreds of meters, due to incomplete overlap between the transmitter and the receiver, etc. The large blind range prevents the successful retrieval of the near-ground aerosol profile, ...
DOI:
10.3390/rs12071227

9. Urban air pollution monitoring using scanning Lidar

Author:
Xian, Jinhong; Sun, Dongsong; Xu, Wenjing; Han, Yuli; Zheng, Jun; Peng, Jiancao; Yang, Shaochen
Source:
Environmental pollution 2020 v.258 pp. 113696
ISSN:
0269-7491
Subject:
lidar,   etc   ; absorbance; air pollution; algorithms; monitoring;     Show all 5 Subjects
Abstract:
... We have developed a scanning Lidar system in this work to detect urban air pollution changes in real time and locate the sources of urban air pollution. We first proposed an algorithm to retrieve atmospheric extinction coefficients, which we used to create Lidar maps. Using Lidar map of the average extinction coefficients, we identified the locations of the local maximum values, and hence, the pos ...
DOI:
10.1016/j.envpol.2019.113696

10. Ideal Angular Orientation of Selected 64-Channel Multi Beam Lidars for Mobile Mapping Systems

Author:
Alsadik, Bashar
Source:
Remote Sensing 2020 v.12 no.3
ISSN:
2072-4292
Subject:
lidar,   etc   ; industry; radiometry; remote sensing; spinning;     Show all 5 Subjects
Abstract:
... Lidar technology is thriving nowadays for different applications mainly for autonomous navigation, mapping, and smart city technology. Lidars vary in different aspects and can be: multi beam, single beam, spinning, solid state, full 360 field of view FOV, single or multi pulse returns, and many other geometric and radiometric aspects. Users and developers in the mapping industry are continuously l ...
DOI:
10.3390/rs12030510

11. PGA-SiamNet: Pyramid Feature-Based Attention-Guided Siamese Network for Remote Sensing Orthoimagery Building Change Detection

Author:
Jiang, Huiwei; Hu, Xiangyun; Li, Kun; Zhang, Jinming; Gong, Jinqi; Zhang, Mi
Source:
Remote Sensing 2020 v.12 no.3
ISSN:
2072-4292
Subject:
lidar,   etc   ; data collection; orthophotography; remote sensing;     Show all 4 Subjects
Abstract:
... In recent years, building change detection has made remarkable progress through using deep learning. The core problems of this technique are the need for additional data (e.g., Lidar or semantic labels) and the difficulty in extracting sufficient features. In this paper, we propose an end-to-end network, called the pyramid feature-based attention-guided Siamese network (PGA-SiamNet), to solve thes ...
DOI:
10.3390/rs12030484

12. Fully Automated Profile-based Calibration Strategy for Airborne and Terrestrial Mobile LiDAR Systems with Spinning Multi-beam Laser Units

Author:
Ravi, Radhika; Habib, Ayman
Source:
Remote Sensing 2020 v.12 no.3
ISSN:
2072-4292
Subject:
lidar,   etc   ; automation; data collection; remote sensing; spinning;     Show all 5 Subjects
Abstract:
... LiDAR-based mobile mapping systems (MMS) are rapidly gaining popularity for a multitude of applications due to their ability to provide complete and accurate 3D point clouds for any and every scene of interest. However, an accurate calibration technique for such systems is needed in order to unleash their full potential. In this paper, we propose a fully automated profile-based strategy for the ca ...
DOI:
10.3390/rs12030401

13. A Frustum-based probabilistic framework for 3D object detection by fusion of LiDAR and camera data

Author:
Gong, Zheng; Lin, Haojia; Zhang, Dedong; Luo, Zhipeng; Zelek, John; Chen, Yiping; Nurunnabi, Abdul; Wang, Cheng; Li, Jonathan
Source:
ISPRS journal of photogrammetry and remote sensing 2020 v.159 pp. 90-100
ISSN:
0924-2716
Subject:
lidar,   etc   ; cameras; data collection; neural networks; probability;     Show all 5 Subjects
Abstract:
... This paper presents a real-time 3D object detector based on LiDAR based Simultaneous Localization and Mapping (LiDAR-SLAM). The 3D point clouds acquired by mobile LiDAR systems, within the environment of buildings, are usually highly sparse, irregularly distributed, and often contain occlusion and structural ambiguity. Existing 3D object detection methods based on Convolutional Neural Networks (CN ...
DOI:
10.1016/j.isprsjprs.2019.10.015

14. Fusing diameter distributions predicted by an area-based approach and individual-tree detection in coniferous-dominated forests

Author:
Räty, Janne; Packalen, Petteri; Kotivuori, Eetu; Maltamo, Matti
Source:
Canadian journal of forest research 2020 v.50 no.2 pp. 113-125
ISSN:
1208-6037
Subject:
lidar,   etc   ; boreal forests; forest inventory; prediction;     Show all 4 Subjects
Abstract:
... An area-based approach (ABA) is the most common method used to predict forest attributes with airborne laser scanning (ALS) data. Individual-tree detection (ITD) offers an alternative to ABA; however, few studies have examined the selection of these two alternatives for the prediction of diameter distributions. We predicted diameter distributions by applying ABA and ITD in coniferous-dominated bor ...
DOI:
10.1139/cjfr-2019-0102

15. The modern evolution of geomorphology — Binghamton and personal perspectives, 1970–2019 and beyond

Author:
Baker, Victor R.
Source:
Geomorphology 2020 v.366 pp. 106684
ISSN:
0169-555X
Subject:
lidar,   etc   ; artificial intelligence; computer simulation; geomorphology; philosophy; New York;     Show all 6 Subjects
Abstract:
... The annual Binghamton Geomorphology Symposia (BGS) began in 1970, initiated by Professors Donald R. Coates and Marie Morisawa of the State University of New York at Binghamton. The 50 BGS meeting topics through 2019 can be organized into five general themes, as follows: (1) Applications; (2) Methods; (3) Process and Form; (4) History, Philosophy, and Theory; (5) Systems. My own geomorphological re ...
DOI:
10.1016/j.geomorph.2019.02.028

16. Cloud dimensions from Jack Rabbit II field trial data

Author:
Mazzola, Thomas
Source:
Atmospheric environment 2020 v.237 pp. 117614
ISSN:
1352-2310
Subject:
lidar,   etc   ; atmospheric chemistry; chlorine; field experimentation; hares; meteorology; models;     Show all 7 Subjects
Abstract:
... Jack Rabbit II field trials recorded a large amount of point sensor data regarding meteorology and chlorine concentrations and included many video and specialized standoff measurements. Cloud dimensions must be inferred or analyzed from such data. The test data were used to identify cloud dimensions (widths and heights to the 20 and 200 ppm contours) for use in the model inter-comparison exercise. ...
DOI:
10.1016/j.atmosenv.2020.117614

17. DANCE-NET: Density-aware convolution networks with context encoding for airborne LiDAR point cloud classification

Author:
Li, Xiang; Wang, Lingjing; Wang, Mingyang; Wen, Congcong; Fang, Yi
Source:
ISPRS journal of photogrammetry and remote sensing 2020 v.166 pp. 128-139
ISSN:
0924-2716
Subject:
lidar,   etc   ; data collection; neural networks; photogrammetry; remote sensing;     Show all 5 Subjects
Abstract:
... Airborne LiDAR point cloud classification has been a long-standing problem in photogrammetry and remote sensing. Early efforts either combine hand-crafted feature engineering with machine learning-based classification models or leverage the power of conventional convolutional neural networks (CNNs) on projected feature images. Recent proposed deep learning-based methods tend to develop new convolu ...
DOI:
10.1016/j.isprsjprs.2020.05.023

18. Land-cover classification of multispectral LiDAR data using CNN with optimized hyper-parameters

Author:
Pan, Suoyan; Guan, Haiyan; Chen, Yating; Yu, Yongtao; Nunes Gonçalves, Wesley; Marcato Junior, José; Li, Jonathan
Source:
ISPRS journal of photogrammetry and remote sensing 2020 v.166 pp. 241-254
ISSN:
0924-2716
Subject:
lidar,   etc   ; artificial intelligence; geometry; image analysis; land cover; models; wavelengths;     Show all 7 Subjects
Abstract:
... Multispectral LiDAR (Light Detection And Ranging) is characterized of the completeness and consistency of its spectrum and spatial geometric data, which provides a new data source for land-cover classification. In recent years, the convolutional neural network (CNN), compared with traditional machine learning methods, has made a series of breakthroughs in image classification, object detection, an ...
DOI:
10.1016/j.isprsjprs.2020.05.022

19. A Ridgeline-Based Terrain Co-registration for Satellite LiDAR Point Clouds in Rough Areas

Author:
Zhou, Ruqin; Jiang, Wanshou
Source:
Remote Sensing 2020 v.12 no.13
ISSN:
2072-4292
Subject:
lidar,   etc   ; covariance; data collection; landscapes; remote sensing; satellites;     Show all 6 Subjects
Abstract:
... It is still a completely new and challenging task to register extensive, enormous and sparse satellite light detection and ranging (LiDAR) point clouds. Aimed at this problem, this study provides a ridgeline-based terrain co-registration method in preparation for satellite LiDAR point clouds in rough areas. This method has several merits: (1) only ridgelines are extracted as neighbor information f ...
DOI:
10.3390/rs12132163

20. Advances in horse morphometric measurements using LiDAR

Author:
Pérez-Ruiz, M.; Tarrat-Martín, D.; Sánchez-Guerrero, M.J.; Valera, M.
Source:
Computers and electronics in agriculture 2020 v.174 pp. 105510
ISSN:
0168-1699
Subject:
lidar,   etc   ; body measurements; longevity; mares; models; morphometry; reproductive performance; stallions;     Show all 8 Subjects
Abstract:
... Zoometric measurements have a potential value in differentialing between individuals and within populations. The measurement of body size in horses and livestock plays a significant role in functional longevity, production, and reproductive performance and health. In this context, the measurements obtained without contact by detection systems and visualized by computers could represent a great adv ...
DOI:
10.1016/j.compag.2020.105510