scholarly journals Transient Reactivation of a Deep-Seated Landslide by Undrained Loading Captured With Repeat Airborne and Terrestrial Lidar

2018 ◽  
Vol 45 (10) ◽  
pp. 4841-4850 ◽  
Author(s):  
Adam M. Booth ◽  
Justin McCarley ◽  
Jason Hinkle ◽  
Susan Shaw ◽  
Jean-Paul Ampuero ◽  
...  
Keyword(s):  
Terrestrial Lidar ◽  
Undrained Loading

scholarly journals Individual Tree Extraction from Terrestrial LiDAR Point Clouds Based on Transfer Learning and Gaussian Mixture Model Separation

2021 ◽  
Vol 13 (2) ◽  
pp. 223
Author(s):  
Zhenyang Hui ◽  
Shuanggen Jin ◽  
Dajun Li ◽  
Yao Yevenyo Ziggah ◽  
Bo Liu
Keyword(s):  
Transfer Learning ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Principal Component ◽  
Point Clouds ◽  
Gaussian Mixture ◽  
Individual Tree ◽  
Terrestrial Lidar ◽  
Initial Segmentation ◽  
Tree Extraction

Individual tree extraction is an important process for forest resource surveying and monitoring. To obtain more accurate individual tree extraction results, this paper proposed an individual tree extraction method based on transfer learning and Gaussian mixture model separation. In this study, transfer learning is first adopted in classifying trunk points, which can be used as clustering centers for tree initial segmentation. Subsequently, principal component analysis (PCA) transformation and kernel density estimation are proposed to determine the number of mixed components in the initial segmentation. Based on the number of mixed components, the Gaussian mixture model separation is proposed to separate canopies for each individual tree. Finally, the trunk stems corresponding to each canopy are extracted based on the vertical continuity principle. Six tree plots with different forest environments were used to test the performance of the proposed method. Experimental results show that the proposed method can achieve 87.68% average correctness, which is much higher than that of other two classical methods. In terms of completeness and mean accuracy, the proposed method also outperforms the other two methods.

scholarly journals Remote Sensing for Land Administration

2020 ◽  
Vol 12 (15) ◽  
pp. 2497
Author(s):  
Rohan Bennett ◽  
Peter van Oosterom ◽  
Christiaan Lemmen ◽  
Mila Koeva
Keyword(s):  
Remote Sensing ◽  
Land Tenure ◽  
Laser Scanning ◽  
Poverty Reduction ◽  
Spatial Information ◽  
Cost Effective ◽  
Terrestrial Lidar ◽  
Land Administration ◽  
Tools And Techniques ◽  
Vertical Development

Land administration constitutes the socio-technical systems that govern land tenure, use, value and development within a jurisdiction. The land parcel is the fundamental unit of analysis. Each parcel has identifiable boundaries, associated rights, and linked parties. Spatial information is fundamental. It represents the boundaries between land parcels and is embedded in cadastral sketches, plans, maps and databases. The boundaries are expressed in these records using mathematical or graphical descriptions. They are also expressed physically with monuments or natural features. Ideally, the recorded and physical expressions should align, however, in practice, this may not occur. This means some boundaries may be physically invisible, lacking accurate documentation, or potentially both. Emerging remote sensing tools and techniques offers great potential. Historically, the measurements used to produce recorded boundary representations were generated from ground-based surveying techniques. The approach was, and remains, entirely appropriate in many circumstances, although it can be timely, costly, and may only capture very limited contextual boundary information. Meanwhile, advances in remote sensing and photogrammetry offer improved measurement speeds, reduced costs, higher image resolutions, and enhanced sampling granularity. Applications of unmanned aerial vehicles (UAV), laser scanning, both airborne and terrestrial (LiDAR), radar interferometry, machine learning, and artificial intelligence techniques, all provide examples. Coupled with emergent societal challenges relating to poverty reduction, rapid urbanisation, vertical development, and complex infrastructure management, the contemporary motivation to use these new techniques is high. Fundamentally, they enable more rapid, cost-effective, and tailored approaches to 2D and 3D land data creation, analysis, and maintenance. This Special Issue hosts papers focusing on this intersection of emergent remote sensing tools and techniques, applied to domain of land administration.

Terrestrial lidar and hyperspectral data fusion products for geological outcrop analysis

2013 ◽  
Vol 54 ◽  
pp. 249-258 ◽  
Author(s):  
Simon J. Buckley ◽  
Tobias H. Kurz ◽  
John A. Howell ◽  
Danilo Schneider
Keyword(s):  
Data Fusion ◽  
Hyperspectral Data ◽  
Terrestrial Lidar ◽  
Fusion Products

scholarly journals Traditional field metrics and terrestrial LiDAR predict plant richness in southern pine forests

2021 ◽  
Vol 491 ◽  
pp. 119118
Author(s):  
C.T. Anderson ◽  
S.L. Dietz ◽  
S.M. Pokswinski ◽  
A.M. Jenkins ◽  
M.J. Kaeser ◽  
...  
Keyword(s):  
Pine Forests ◽  
Southern Pine ◽  
Terrestrial Lidar ◽  
Plant Richness

Full-Waveform Terrestrial Lidar Data Classification Using Raw Samples of Digitized Waveform

2021 ◽  
Author(s):  
Mohammad Pashaei ◽  
Michael J. Starek ◽  
Philippe Tissot ◽  
Jacob Berryhill
Keyword(s):  
Data Classification ◽  
Lidar Data ◽  
Terrestrial Lidar ◽  
Full Waveform

Terrestrial hyperspectral image shadow restoration through fusion with terrestrial lidar

2017 ◽  
Author(s):  
Preston J. Hartzell ◽  
Craig L. Glennie ◽  
David C. Finnegan ◽  
Darren L. Hauser
Keyword(s):  
Hyperspectral Image ◽  
Terrestrial Lidar

Error Analysis of a Mobile Terrestrial LiDAR System

GEOMATICA ◽  
2014 ◽  
Vol 68 (3) ◽  
pp. 183-194 ◽  
Author(s):  
M. Leslar ◽  
B. Hu ◽  
J.G. Wang
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Sensitivity Study ◽  
Error Sources ◽  
Terrestrial Lidar ◽  
Lever Arm ◽  
Ideal Situation ◽  
Individual Variables ◽  
The Individual ◽  
Source Of Error

The understanding of the effects of error on Mobile Terrestrial LiDAR (MTL) point clouds has not increased with their popularity. In this study, comprehensive error analyses based on error propagation theory and global sensitivity study were carried out to quantitatively describe the effects of various error sources in a MTL system on the point cloud. Two scenarios were envisioned; the first using the uncertainties for measurement and calibration variables that are normally expected for MTL systems as they exist today, and the second using an ideal situation where measurement and calibration values have been well adjusted. It was found that the highest proportion of error in the point cloud can be attributed to the boresight and lever arm parameters for MTL systems calibrated using non-rigours methods. In particular, under a loosely controlled error condition, the LiDAR to INS Z lever arm and the LiDAR to INS roll angle contributed more error in the output point cloud than any other parameter, including the INS position. Under tightly controlled error conditions, the INS position became the dominant source of error in the point cloud. In addition, conditional variance analysis has shown that the majority of the error in a point cloud can be attributed to the individual variables. Errors caused by the interactions between the diverse variables are minimal and can be regarded as insignificant.

Using terrestrial LiDAR data to analyse morphodynamics on steep unvegetated slopes driven by different geomorphic processes

CATENA ◽  
2016 ◽  
Vol 142 ◽  
pp. 269-280 ◽  
Author(s):  
F. Neugirg ◽  
A. Kaiser ◽  
A. Huber ◽  
T. Heckmann ◽  
M. Schindewolf ◽  
...  
Keyword(s):  
Lidar Data ◽  
Terrestrial Lidar ◽  
Geomorphic Processes
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