- 1. Introduction
- Use of LIDAR in landslide investigations: a review
- Synthetic aperture lidar as a future tool for earth observation
- A remote forest monitoring system
- Headwall integrates hyperspectral and lidar instruments aboard UAV platforms
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Request a Quote Request a Demo Contact. Focus S The ultra-portable Focus S enables fast, straightforward and ultra-high accurate measurements of objects and buildings. Focus S 70 The ultra-portable Focus S 70 enables fast, straightforward and ultra-high accurate measurements of objects and buildings.
It will facilitate the prediction and management of urban sprawl [ 75 — 77 ] and push forward sustainable urban planning in not just the developed world, but also the developing countries as they catch on with the technologies [ 46 , 49 ]. To that end, open sourcing the methodology and software is another pressing topic, which could help further accelerate the paradigm shift. The paper provides a methodology for the application of LiDAR to automated solar photovoltaic deployment analysis on the regional scale.
First, a comprehensive examination and comparisons of existing algorithms and approaches to turn LiDAR point cloud into 2. The methodology implements what previous literature recommends in terms of integrating cross disciplinary competences in remote sensing, GIS, computer vision and urban environmental studies. It is a robust methodology that can work with poor-quality data and reconstruct vegetation and building separately but concurrently.
Since the coarse selection of building regions is crucial to reliable results considerable attention was focused on this first step. Subsequent steps in building extraction, segmentation and reconstruction were carried out accompanied with mathematical proofs and illustrations. The approach was data driven hence the whole attempt can be regarded as a large scale optimization problem aiming at best approximating the point cloud.
Rules of thumb were collected to incorporate in the development of such scripts for extracting rooftops for solar photovoltaic potential. But there is still room for the more mathematically rigorous or biologically minded audience to contribute and orient the workflow to suit their needs. Hence this can be regarded as the next step towards a new generation of urban analysis software.
National Center for Biotechnology Information , U. Journal List Sensors Basel v. Sensors Basel. Published online Apr Nguyen , 1 Joshua M. Joshua M. Author information Article notes Copyright and License information Disclaimer. This article has been cited by other articles in PMC. Introduction Solar photovoltaic PV energy conversion offers a sustainable method of producing electricity to provide for contemporary society's needs [ 1 ].
Background 2. LiDAR and the Cityscape The proverbial Holy Grail of the urban remote sensing research community is the ability to quickly and easily build accurate 2D and 3D representations of urban areas. Building Detection Reliable and accurate building generation from LiDAR data requires a number of processes beyond capture of accurate raw data.
Building Segmentation Segmentation provides an excellent starting point for subsequent geospatial analyses [ 50 , 51 ]. Building Reconstruction After individual cloud segments that correspond to building faces are recognized a method is needed to interpolate the heights in between the points and hence transform the working geometry from points to polygons. Methodology As outlined above, a wide range of techniques have been used to extract building geometry, and in particular roof geometry, from LiDAR point clouds and from imagery with or without independent building outline data.
Open in a separate window. Figure 1. Figure 2. Elevation Cut-Off Next, all points within the roofs' outlines are filtered by introducing a threshold value above the bare earth elevation level DEM , with the goal being to remove LiDAR points sampled through skylights, into small courtyards, and the like. Figure 3. Individual Point Subcloud Processing. Tree and Noise Detection Since the automation algorithms are highly sensitive to any remaining noise, i. Roof Fitting The subpoints at this point are ready to be segmented and used for reconstruction.
Noise points were to be eliminated before running the script Section 3. Results 4. Buffering Size Determination The effects of each buffer size on the chosen area were investigated by counting the number of points being encompassed by each buffer. Figure 4. Elevation Cutoff Based on point counts it was found that i 2. Figure 5. Figure 6. Figure 7. Point Cloud Statistical Analysis Point cloud statistical analysis was carried out to distinguish flat rooftops from tilted roof planes. Error Analysis Nyruhuma assessed how accurate the reconstructed urban scene was to reality using roof angle, roof area and building height [ 56 ].
Figure 8. Conclusions The paper provides a methodology for the application of LiDAR to automated solar photovoltaic deployment analysis on the regional scale. References 1. Pearce J. Photovoltaics—A path to sustainable futures. Olz S. Contribution of Renewables to Energy Security. Wong J. Getting out of the shade: Solar energy as a National Security Strategy. China Secur. Branker K. Financial return for government support of large-scale thin film solar photovoltaic manufacturing in Canada. Energy Policy.
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Use of LIDAR in landslide investigations: a review
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Synthetic aperture lidar as a future tool for earth observation
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A remote forest monitoring system
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This method makes it possible to discriminate efficiently the true cliffs from the one drawn on topographic maps. As discussed in Janeras et al. Hazard assessment requires often performing trajectographic modelling in order to delineate the propagation area. In addition, the kinetic energy profile is greatly modified when the resolution of the DEM is increased.
Both parameters are of primary importance for hazard mapping and dimensioning of mitigation measures. But obtaining the complete field of displacements for the whole landslide is of great help to understand landslide kinematics and failure mechanism Fig. Laser scanning is nowadays a common tool for displacement monitoring even if few published papers exists. Nevertheless, as monitoring requires both high resolution and high precision data sets, most of the works have been done up to now using TLS-derived HRDEMs.
The results are either vectors between two points or common areas or distances between two data sets point to surface comparison either in a user-defined direction or as shortest distance Hausdorff distance between the two surfaces. This difference calculation allows for the computation of volume differences, as is discussed by different authors Bitelli et al.
Together with these monitoring results, the possibility to link spatial and temporal prediction of rockfalls constitutes a great challenge for landslide monitoring. Indeed, two different precursory indicators are currently being investigated: 1 the increase in rockfall activity before the final collapse, shown by Rosser et al. Although in certain cases precursory movements can be of the same order of magnitude than instrumental errors, different authors have observed that errors can be considerably reduced by taking into account the information of the neighbouring points, i.
As an example, it was shown that it is possible to detect millimetric surface displacements in an outdoor experiment, even if single points had a higher standard deviation Abellan et al. As we already mentioned, it is possible to monitor the channel changes using TLS Oppikofer ; Theules et al. Recently, Scheidl et al. Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author s and source are credited.
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Headwall integrates hyperspectral and lidar instruments aboard UAV platforms
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