Detection of millimetric deformation using a terrestrial laser scanner: experiment and application to a rockfall event

Terrestrial laser scanning (TLS) is one of the most promising surveying techniques for rockslope characterization and monitoring. Landslide and rockfall movements can be detected by means of comparison of sequential scans. One of the most pressing challenges of natural hazards is combined temporal and spatial prediction of rockfall. An outdoor experiment was performed to ascertain whether the TLS instrumental error is small enough to enable detection of precursory displacements of millimetric magnitude. This consists of a known displacement of three objects relative to a stable surface. Results show that millimetric changes cannot be detected by the analysis of the unprocessed datasets. Displacement measurement are improved considerably by applying Nearest Neighbour (NN) averaging, which reduces the error (1¿) up to a factor of 6. This technique was applied to displacements prior to the April 2007 rockfall event at Castellfollit de la Roca, Spain. The maximum precursory displacement measured was 45 mm, approximately 2.5 times the standard deviation of the model comparison, hampering the distinction between actual displacement and instrumental error using conventional methodologies. Encouragingly, the precursory displacement was clearly detected by applying the NN averaging method. These results show that millimetric displacements prior to failure can be detected using TLS.

Using Scanning Lasers for Real-Time Pavement Thickness Measurement, TR-538, 2006

Due to limited budgets and reduced inspection staff, state departments of transportation (DOTs) are in need of innovative approaches for providing more efficient quality assurance on concrete paving projects. The goal of this research was to investigate and test new methods that can determine pavement thickness in real time. Three methods were evaluated: laser scanning, ultrasonic sensors, and eddy current sensors. Laser scanning, which scans the surface of the base prior to paving and then scans the surface after paving, can determine the thickness at any point. Also, scanning lasers provide thorough data coverage that can be used to calculate thickness variance accurately and identify any areas where the thickness is below tolerance. Ultrasonic and eddy current sensors also have the potential to measure thickness nondestructively at discrete points and may result in an easier method of obtaining thickness. There appear to be two viable approaches for measuring concrete pavement thickness during the paving operation: laser scanning and eddy current sensors. Laser scanning has proved to be a reliable technique in terms of its ability to provide virtual core thickness with low variability. Research is still required to develop a prototype system that integrates point cloud data from two scanners. Eddy current sensors have also proved to be a suitable alternative, and are probably closer to field implementation than the laser scanning approach. As a next step for this research project, it is suggested that a pavement thickness measuring device using eddy current sensors be created, which would involve both a handheld and paver-mounted version of the device.

Monitoring and failure mechanism interpretation of an unstable slope in Southern Switzerland based on terrestrial laser scanner

We present the application of terrestrial laser scanning (TLS) for the monitoring and characterization of an active landslide area in Val Canaria (Ticino, Southern Swiss Alps). At catchment scale, the study area is affected by a large Deep Seated Gravitational Slope Deformation (DSGSD) area presenting, in the lower boundary, several retrogressive landslides active since the 1990s. Due to its frequent landslide events this area was periodically monitored by TLS since 2006. Periodic acquisitions provided new information on 3D displacements at the bottom of slope and the detection of centimetre to decimetre level scale changes (e.g. rockfall and pre-failure deformations). In October 2009, a major slope collapse occured at the bottom of the most unstable area. Based on the comparison between TLS data before and after the collapse, we carried out a detailed failure mechanism analysis and volume calculation.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.

Influence of energy and pulse repetition rate of Er : YAG laser on enamel ablation ability and morphological analysis of the laser-irradiated surface

Objective: To assess the influence of energy and pulse repetition rate of Er:YAG laser on the enamel ablation ability and substrate morphology. Methods: Fifteen crowns of molars were sectioned in four fragments, providing 60 samples, which were ground to flatten the enamel surface. The initial mass was obtained by weighing the fragments. The specimens were hydrated for I h, fixed, and a 3-mm-diameter area was delimited. Twelve groups were randomly formed according to the combination of laser energies (200, 250, 300, or 350 mJ) and pulse repetition rates (2, 3, or 4 Hz). The final mass was obtained and mass loss was calculated by the difference between the initial and final mass. The specimens were prepared for SEM. Data were submitted to ANOVA and Scheffe test. Results: The 4 Hz frequency resulted in higher mass loss and was statistically different from 2 and 3 Hz (p < 0.05). The increase of frequency produced more melted areas, cracks, and unselective and deeper ablation. The 350 mJ energy promoted greater mass loss, similar to 300 mJ. Conclusions: The pulse repetition rate influenced more intensively the mass loss and morphological alteration. Among the tested parameters, 350 mJ/3 Hz improved the ability of enamel ablation with less surface morphological alterations. (C) 2007 Wiley Periodicals, Inc. J Biomed Mater Res.

Monitoramento da morfologia costeira em setores da bacia potiguar sob influência da indústria petrolífera utilizando geodésia de alta precisão e laser escâner terrestre

The objective of this Doctoral Thesis was monitoring, in trimestral scale, the coastal morphology of the Northeastern coast sections of Rio Grande do Norte State, in Brazil, which is an area of Potiguar Basin influenced by the oil industry activities. The studied sections compose coastal areas with intense sedimentary erosion and high environmental sensitivity to the oil spill. In order to achieve the general objective of this study, the work has been systematized in four steps. The first one refers to the evaluation of the geomorphological data acquisition methodologies used on Digital Elevation Model (DEM) of sandy beaches. The data has been obtained from Soledade beach, located on the Northeastern coast of Rio Grande Norte. The second step has been centered on the increasing of the reference geodetic infrastructure to accomplish the geodetic survey of the studied area by implanting a station in Corta Cachorro Barrier Island and by conducting monitoring geodetic surveys to understand the beach system based on the Coastline (CL) and on DEM multitemporal analysis. The third phase has been related to the usage of the methodology developed by Santos; Amaro (2011) and Santos et al. (2012) for the surveying, processing, representation, integration and analysis of Coastlines from sandy coast, which have been obtained through geodetic techniques of positioning, morphological change analysis and sediment transport. The fourth stage represents the innovation of surveys in coastal environment by using the Terrestrial Laser Scanning (TLS), based on Light Detection and Ranging (LiDAR), to evaluate a highly eroded section on Soledade beach where the oil industry structures are located. The evaluation has been achieved through high-precision DEM and accuracy during the modeling of the coast morphology changes. The result analysis of the integrated study about the spatial and temporal interrelations of the intense coastal processes in areas of building cycles and destruction of beaches has allowed identifying the causes and consequences of the intense coastal erosion in exposed beach sections and in barrier islands

Extração automática de contornos de telhados usando dados de varredura a laser e campos randômicos de Markov

This paper proposes a methodology for automatic extraction of building roof contours from a Digital Elevation Model (DEM), which is generated through the regularization of an available laser point cloud. The methodology is based on two steps. First, in order to detect high objects (buildings, trees etc.), the DEM is segmented through a recursive splitting technique and a Bayesian merging technique. The recursive splitting technique uses the quadtree structure for subdividing the DEM into homogeneous regions. In order to minimize the fragmentation, which is commonly observed in the results of the recursive splitting segmentation, a region merging technique based on the Bayesian framework is applied to the previously segmented data. The high object polygons are extracted by using vectorization and polygonization techniques. Second, the building roof contours are identified among all high objects extracted previously. Taking into account some roof properties and some feature measurements (e. g., area, rectangularity, and angles between principal axes of the roofs), an energy function was developed based on the Markov Random Field (MRF) model. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing (SA) algorithm. Experiments carried out with laser scanning DEM's showed that the methodology works properly, as it delivered roof contours with approximately 90% shape accuracy and no false positive was verified.

Uso de dados fotogramétricos no refinamento geométrico de contornos de telhados de edifícios extraídos de dados laser

In this paper, a methodology is proposed for the geometric refinement of laser scanning building roof contours using high-resolution aerial images and Markov Random Field (MRF) models. The proposed methodology takes for granted that the 3D description of each building roof reconstructed from the laser scanning data (i.e., a polyhedron) is topologically correct and that it is only necessary to improve its accuracy. Since roof ridges are accurately extracted from laser scanning data, our main objective is to use high-resolution aerial images to improve the accuracy of roof outlines. In order to meet this goal, the available roof contours are first projected onto the image-space. After that, the projected polygons and the straight lines extracted from the image are used to establish an MRF description, which is based on relations ( relative length, proximity, and orientation) between the two sets of straight lines. The energy function associated with the MRF is minimized by using a modified version of the brute force algorithm, resulting in the grouping of straight lines for each roof object. Finally, each grouping of straight lines is topologically reconstructed based on the topology of the corresponding laser scanning polygon projected onto the image-space. The preliminary results showed that the proposed methodology is promising, since most sides of the refined polygons are geometrically better than corresponding projected laser scanning straight lines.

Confocal Laser Microscopic Analysis of Biofilm on Newer Feldspar Ceramic

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Segmentação de dados de perfilamento a laser em áreas urbanas utilizando uma abordagem Bayesiana

In this paper is presented a region-based methodology for Digital Elevation Model segmentation obtained from laser scanning data. The methodology is based on two sequential techniques, i.e., a recursive splitting technique using the quad tree structure followed by a region merging technique using the Markov Random Field model. The recursive splitting technique starts splitting the Digital Elevation Model into homogeneous regions. However, due to slight height differences in the Digital Elevation Model, region fragmentation can be relatively high. In order to minimize the fragmentation, a region merging technique based on the Markov Random Field model is applied to the previously segmented data. The resulting regions are firstly structured by using the so-called Region Adjacency Graph. Each node of the Region Adjacency Graph represents a region of the Digital Elevation Model segmented and two nodes have connectivity between them if corresponding regions share a common boundary. Next it is assumed that the random variable related to each node, follows the Markov Random Field model. This hypothesis allows the derivation of the posteriori probability distribution function whose solution is obtained by the Maximum a Posteriori estimation. Regions presenting high probability of similarity are merged. Experiments carried out with laser scanning data showed that the methodology allows to separate the objects in the Digital Elevation Model with a low amount of fragmentation.

Extração de vias combinando métodos de detecção de regiões e linhas em imagens de intensidade de pulso laser

This paper aims at extracting street centerlines from previously isolated street regions by using the image of laser scanning intensity. In this image, streets are easily identified, since they manifest as dark, elongate ribbons contrasting with background objects. The intensity image is segmented by using the region growing technique, which generates regions representing the streets. From these regions, the street centerlines are extracted in two manners. The first one is through the Steger lines detection method combined with a line length thresholding by which lines being shorter than a minimum length are removed. The other manner is by combining the skeletonization method of regions based on the Medial Axis Transform and with a pruning process to eliminate as much as possible the ramifications. Experiments showed that the Steger-based method provided results better than the method based on skeletonization.

Effect of bleaching on sound enamel and with early artificial caries lesions using confocal laser microscopy

The aim of this study was to evaluate effect of bleaching agents on sound enamel (SE) and enamel with early artificial caries lesions (CL) using confocal laser scanning microscopy (CLSM). Eighty blocks (4 × 5 × 5 mm) of bovine enamel were used and half of them were submitted to a pH cycling model to induce CL. Eight experimental groups were obtained from the treatments and mineralization level of the enamel (SE or CL) (n=10). SE groups: G1 - unbleached (control); G2 - 4% hydrogen peroxide (4 HP); G3 - 4 HP containing 0.05% Ca (Ca); G4 - 7.5% hydrogen peroxide (7.5 HP) containing amorphous calcium phosphate (ACP). CL groups: G5 - unbleached; G6 - 4 HP; G7 - 4 HP containing Ca; G8 - 7.5 HP ACP. G2, G3, G6, G7 were treated with the bleaching agents for 8 h/day during 14 days, while G4 and G8 were exposed to the bleaching agents for 30 min twice a day during 14 days. The enamel blocks were stained with 0.1 mM rhodamine B solution and the demineralization was quantified using fluorescence intensity detected by CLSM. Data were analyzed using ANOVA and Fisher's tests (α=0.05). For the SE groups, the bleaching treatments increased significantly the demineralization area when compared with the unbleached group. In the CL groups, no statistically significant difference was observed (p>0.05). The addition of ACP or Ca in the composition of the whitening products did not overcome the effects caused by bleaching treatments on SE and neither was able to promote remineralization of CL.

Photogrammetric refinement of laser-based building roof contours

In this paper a photogrammetric method is proposed for refining 3D building roof contours extracted from airborne laser scanning data. It is assumed that laser-derived planar faces of roofs are potentially accurate, while laser-derived building roof contours are not well defined. First, polygons representing building roof contours are extracted from a high-resolution aerial image. In the sequence, straight-line segments delimitating each building roof polygon are projected onto the corresponding laser-derived roof planes by using a new line-based photogrammetric model. Finally, refined 3D building roof contours are reconstructed by connecting every pair of photogrammetrically- projected adjacent straight lines. The obtained results showed that the proposed approach worked properly, meaning that the integration of image data and laser scanning data allows better results to be obtained, when compared to the results generated by using only laser scanning data. © 2013 IEEE.

Detecção de regiões de via integrando dados de varredura a LASER aerotransportado e imagens de alta resolução

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reconstrução de contornos e cumeeiras de telhados de edifícios a partir de imagens aéreas de alta-resolução e poliedros representativos de edifícios extraídos de dados LASER

Pós-graduação em Ciências Cartográficas - FCT