15 resultados para 3D Point Cloud
em Publishing Network for Geoscientific
Resumo:
This paper assesses the along strike variation of active bedrock fault scarps using long range terrestrial laser scanning (t-LiDAR) data in order to determine the distribution behaviour of scarp height and the subsequently calculate long term throw-rates. Five faults on Cretewhich display spectacular limestone fault scarps have been studied using high resolution digital elevation model (HRDEM) data. We scanned several hundred square metres of the fault system including the footwall, fault scarp and hanging wall of the investigated fault segment. The vertical displacement and the dip of the scarp were extracted every metre along the strike of the detected fault segment based on the processed HRDEM. The scarp variability was analysed by using statistical and morphological methods. The analysis was done in a geographical information system (GIS) environment. Results show a normal distribution for the scanned fault scarp's vertical displacement. Based on these facts, the mean value of height was chosen to define the authentic vertical displacement. Consequently the scarp can be divided into above, below and within the range of mean (within one standard deviation) and quantify the modifications of vertical displacement. Therefore, the fault segment can be subdivided into areas which are influenced by external modification like erosion and sedimentation processes. Moreover, to describe and measure the variability of vertical displacement along strike the fault, the semi-variance was calculated with the variogram method. This method is used to determine how much influence the external processes have had on the vertical displacement. By combining of morphological and statistical results, the fault can be subdivided into areas with high external influences and areas with authentic fault scarps, which have little or no external influences. This subdivision is necessary for long term throw-rate calculations, because without this differentiation the calculated rates would be misleading and the activity of a fault would be incorrectly assessed with significant implications for seismic hazard assessment since fault slip rate data govern the earthquake recurrence. Furthermore, by using this workflow areas with minimal external influences can be determined, not only for throw-rate calculations, but also for determining samples sites for absolute dating techniques such as cosmogenic nuclide dating. The main outcomes of this study include: i) there is no direct correlation between the fault's mean vertical displacement and dip (R² less than 0.31); ii) without subdividing the scanned scarp into areas with differing amounts of external influences, the along strike variability of vertical displacement is ±35%; iii) when the scanned scarp is subdivided the variation of the vertical displacement of the authentic scarp (exposed by earthquakes only) is in a range of ±6% (the varies depending on the fault from 7 to 12%); iv) the calculation of the long term throw-rate (since 13 ka) for four scarps in Crete using the authentic vertical displacement is 0.35 ± 0.04 mm/yr at Kastelli 1, 0.31 ± 0.01 mm/yr at Kastelli 2, 0.85 ± 0.06 mm/yr at the Asomatos fault (Sellia) and 0.55 ± 0.05 mm/yr at the Lastros fault.
Resumo:
Underwater video transects have become a common tool for quantitative analysis of the seafloor. However a major difficulty remains in the accurate determination of the area surveyed as underwater navigation can be unreliable and image scaling does not always compensate for distortions due to perspective and topography. Depending on the camera set-up and available instruments, different methods of surface measurement are applied, which make it difficult to compare data obtained by different vehicles. 3-D modelling of the seafloor based on 2-D video data and a reference scale can be used to compute subtransect dimensions. Focussing on the length of the subtransect, the data obtained from 3-D models created with the software PhotoModeler Scanner are compared with those determined from underwater acoustic positioning (ultra short baseline, USBL) and bottom tracking (Doppler velocity log, DVL). 3-D model building and scaling was successfully conducted on all three tested set-ups and the distortion of the reference scales due to substrate roughness was identified as the main source of imprecision. Acoustic positioning was generally inaccurate and bottom tracking unreliable on rough terrain. Subtransect lengths assessed with PhotoModeler were on average 20% longer than those derived from acoustic positioning due to the higher spatial resolution and the inclusion of slope. On a high relief wall bottom tracking and 3-D modelling yielded similar results. At present, 3-D modelling is the most powerful, albeit the most time-consuming, method for accurate determination of video subtransect dimensions.
Resumo:
The classification of airborne lidar data is a relevant task in different disciplines. The information about the geometry and the full waveform can be used in order to classify the 3D point cloud. In Wadden Sea areas the classification of lidar data is of main interest for the scientific monitoring of coastal morphology and habitats, but it becomes a challenging task due to flat areas with hardly any discriminative objects. For the classification we combine a Conditional Random Fields framework with a Random Forests approach. By classifying in this way, we benefit from the consideration of context on the one hand and from the opportunity to utilise a high number of classification features on the other hand. We investigate the relevance of different features for the lidar points in coastal areas as well as for the interaction of neighbouring points.
Resumo:
The world's largest fossil oyster reef, formed by the giant oyster Crassostrea gryphoides and located in Stetten (north of Vienna, Austria) is studied by Harzhauser et al., 2015, 2016; Djuricic et al., 2016. Digital documentation of the unique geological site is provided by terrestrial laser scanning (TLS) at the millimeter scale. Obtaining meaningful results is not merely a matter of data acquisition with a suitable device; it requires proper planning, data management, and postprocessing. Terrestrial laser scanning technology has a high potential for providing precise 3D mapping that serves as the basis for automatic object detection in different scenarios; however, it faces challenges in the presence of large amounts of data and the irregular geometry of an oyster reef. We provide a detailed description of the techniques and strategy used for data collection and processing in Djuricic et al., 2016. The use of laser scanning provided the ability to measure surface points of 46,840 (estimated) shells. They are up to 60-cm-long oyster specimens, and their surfaces are modeled with a high accuracy of 1 mm. In addition to laser scanning measurements, more than 300 photographs were captured, and an orthophoto mosaic was generated with a ground sampling distance (GSD) of 0.5 mm. This high-resolution 3D information and the photographic texture serve as the basis for ongoing and future geological and paleontological analyses. Moreover, they provide unprecedented documentation for conservation issues at a unique natural heritage site.
Resumo:
Modeling natural phenomena from 3D information enhances our understanding of the environment. Dense 3D point clouds are increasingly used as highly detailed input datasets. In addition to the capturing techniques of point clouds with LiDAR, low-cost sensors have been released in the last few years providing access to new research fields and facilitating 3D data acquisition for a broader range of applications. This letter presents an analysis of different speleothem features using 3D point clouds acquired with the gaming device Microsoft® Kinect. We compare the Kinect sensor with terrestrial LiDAR reference measurements using the KinFu pipeline for capturing complete 3D objects (< 4m**3). The results demonstrate the suitability of the Kinect to capture flowstone walls and to derive morphometric parameters of cave features. Although the chosen capturing strategy (KinFu) reveals a high correlation (R2=0.92) of stalagmite morphometry along the vertical object axis, a systematic overestimation (22% for radii and 44% for volume) is found. The comparison of flowstone wall datasets predominantly shows low differences (mean of 1 mm with 7 mm standard deviation) of the order of the Kinect depth precision. For both objects the major differences occur at strongly varying and curved surface structures (e.g. with fine concave parts).
Resumo:
Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research.
Resumo:
Two 7-day mesocosm experiments were conducted in October 2012 at the Instituto Nacional de Desenvolvimento das Pescas (INDP), Mindelo, Cape Verde. Surface water was collected at night before the start of the respective experiment with RV Islândia south of São Vicente (16°44.4'N, 25°09.4'W) and transported to shore using four 600L food safe intermediate bulk containers. Sixteen mesocosm bags were distributed in four flow-through water baths and shaded with blue, transparent lids to approximately 20% of surface irradiation. Mesocosm bags were filled from the containers by gravity, using a submerged hose to minimize bubbles. The accurate volume inside the individual bags was calculated after addition of 1.5 mmol silicate and measuring the resulting silicate concentration. The volume ranged from 105.5 to 145 L. The experimental manipulation comprised addition of different amounts of inorganic N and P. In the first experiment, the P supply was changed at constant N supply in thirteen of the sixteen units, while in the second experiment the N supply was changed at constant P supply in twelve of the sixteen units. In addition to this, "cornerpoints" were chosen that were repeated during both experiments. Four cornerpoints should have been repeated, but setting the nutrient levels in one mesocosm was not succesfull and therefore this mesocosm also was set at the center point conditions. Experimental treatments were evenly distributed between the four water baths. Initial sampling of the mesocosms on day 1 of each run was conducted between 9:45 and 11:30. After nutrient manipulation, sampling was conducted on a daily basis between 09:00 and 10:30 for days 2 to 8.