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Deciphering controls for debris-flow erosion derived from a LiDAR-recorded extreme event and a calibrated numerical model (Ro?bichelbach, Germany)
摘要： Debris flows are among the most destructive and hazardous mass movements on steep mountains. An understanding of debris-flow erosion, entrainment and resulting volumes is a key requirement for modelling debris-flow propagation and impact, as well as analysing the associated risks. As quantitative controls of erosion and entrainment are not well understood, total volume, runout and impact energies of debris flows are often significantly underestimated. Here, we present an analysis of geomorphic change induced by an erosive debris-flow event in the German Alps in June 2015. More than 50 terrestrial laser scans (TLS) of a 1.2 km long mountain torrent recorded geomorphic change in comparison to an airborne laser scan (ALS) performed in 2007. Errors were calculated using a spatial variable threshold based on the point density of ALS and TLS and the slope of the digital elevation models. Highest erosion rates approach 5.0 m3/m2 (mean 0.6 m3/m2). During the event 9,550 ± 1,550 m3 was eroded whereas only 650 ± 150 m3 was deposited in the channel. Velocity, flow pressure, momentum and shear stress were calculated using a carefully calibrated RAMMS Debris Flow model including material entrainment. Here we present a linear regression model relating debris-flow erosion rates to momentum and shear stress with an R2 up to 68 %. Channel transitions from bedrock to loose debris sections cause excessive erosion up to 1 m3/m2 due to previously unreleased random kinetic energy now available for erosion.
关键词： erosion,numerical modeling,debris flow,geomorphic change,RAMMS,LiDAR
更新于2025-09-23 15:22:29
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Camera localization for augmented reality and indoor positioning: a vision-based 3D feature database approach
摘要： The recent fast development in computer vision and mobile sensor technology such as mobile LiDAR and RGB-D cameras is pushing the boundary of the technology to suit the need of real-life applications in the fields of Augmented Reality (AR), robotics, indoor GIS and self-driving. Camera localization is often a key and enabling technology among these applications. In this paper, we developed a novel camera localization workflow based on a highly accurate 3D prior map optimized by our RGB-D SLAM method in conjunction with a deep learning routine trained using consecutive video frames labeled with high precision camera pose. Furthermore, an AR registration method tightly coupled with a game engine is proposed, which incorporates the proposed localization algorithm and aligns the real Kinetic camera with a virtual camera of the game engine to facilitate AR application development in an integrated manner. The experimental results show that the localization accuracy can achieve an average error of 35 cm based on a fine-tuned prior 3D feature database at 3 cm accuracy compared against the ground-truth 3D LiDAR map. The influence of the localization accuracy on the visual effect of AR overlay is also demonstrated and the alignment of the real and virtual camera streamlines the implementation of AR fire emergency response demo in a Virtual Geographic Environment.
关键词： LiDAR,virtual geographic environment (VGE),localization,indoor positioning,camera pose,Augmented reality (AR),indoor GIS,3D reconstruction
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA) - Concepcion, Chile (2018.10.17-2018.10.19)] 2018 IEEE International Conference on Automation/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA) - Mobile LiDAR Scanner for the Generation of 3D Georeferenced Point Clouds
摘要： Mobile laser scanning systems are a modern tool used by leading companies in surveying. These systems are capable of making a three-dimensional reconstruction of the environment by capturing thousands of aligned points. This article describes a hardware and software-based solution for a 3D LiDAR scanner capable of generating a georeferenced point cloud. This solution uses an integrated microcomputer-based hardware architecture, integration of navigation components and data logging. In addition, the effect caused by the measurement errors of the inertial sensors is displayed. To minimize these undesired effects, the use of high-precision navigation system is necessary. For the estimation of the position and orientation of the data captured by the LiDAR sensor, a non-linear interpolation is used for the oversampling of navigation data. Likewise, the scientific problem of direct georeferencing is modeled with a mathematical approach to conventional robotic structure. The product developed meets the technical requirements for most applications in topographic surveys and structural modeling. The system is portable on multiple platforms such as land vehicles and unmanned aerial vehicles.
关键词： point cloud,LiDAR,georeferencing,INS,MLS,hardware
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Geological Mapping of Hydrothermal Alteration on Volcanoes from Multi-Sensor Platforms
摘要： Hydrothermal alteration due to geothermal fluids often introduces mineral alteration and weathering that poses significant natural hazards around volcanoes. Hydrothermal alteration can be mapped remotely using satellite and airborne derive images. In this study, we explored the capacity of available multispectral satellites, high-resolution airborne hyperspectral and LiDAR imagery to provide an improved geological mapping and classification capability for volcanic terrains. Image classification experiments using a Random Forest approach trained using ground class data to classify 15 ground cover types show that Sentinel-2 and Landsat 8 OLI+TIR can provide a geological map with Overall (OA) and Kappa Accuracies (KA) of 69% and 66% respectively. Classification accuracy was dramatically improved when high-resolution airborne datasets were included. The use of full-spectrum AisaFENIX hyperspectral images improved accuracies to OA = 84% and KA = 82%. The maximum image classification accuracy is reached (OA = 87, KA = 85%) when all input features were combined.
关键词： Sentinel-2,volcano,geological mapping,Landsat 8,LiDAR,hyperspectral imaging
更新于2025-09-23 15:21:21
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Estimating Gravimetric Moisture of Vegetation Using an Attenuation-Based Multi-Sensor Approach
摘要： Estimating parameters for global climate models via combined active and passive microwave remote sensing data has been a subject of intensive research in recent years. A variety of retrieval algorithms has been proposed for the estimation of soil moisture, vegetation optical depth and other parameters. A novel attenuation-based retrieval approach is proposed here to globally estimate the gravimetric moisture of vegetation (????) and retrieve information about the amount of water [kg] per amount of wet vegetation [kg]. The parameter ???? is particularly interesting for agro-ecosystems, to assess the status of growing vegetation. The key feature of the proposed approach is that it relies on multi-sensor data from three sensor types (microwave radar, microwave radiometer, and lidar) to solve the physics equations and obtain ????-estimates. The comparability of these estimates to literature values as well as to results of a globally applied, retrieval approach of Grant [4], reveal the potential of the developed method.
关键词： lidar,radiometer,Multi-sensor,SMAP,vegetation water content,vegetation optical depth,radar
更新于2025-09-23 15:21:21
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Suivi topographique c?tier au moyen d’un système LiDAR mobile terrestre : exemple d’une recharge sédimentaire de plage
摘要： L’évolution c?tière est complexe, notamment par la migration de la ligne de rivage et l’apparition successive de zones d’érosion ou d’accumulation. Les suivis quantitatifs des systèmes c?tiers sont largement utilisés afin de comprendre leurs évolutions temporelle et spatiale. Plusieurs méthodes d’acquisition topographiques ont été utilisées (GNSS RTK, LiDAR aéroporté et LiDAR terrestre statique ou mobile) où chaque méthode présente des avantages et des inconvénients lors de suivis d’environnements c?tiers. L’objectif de cet article est de quantifier la précision d’un système LiDAR mobile (SLM) terrestre et d’évaluer s’il peut répondre aux principaux défis des levés topographiques en milieu c?tier qui consistent à réaliser des levés à une haute résolution temporelle, à moindre co?t, tout en assurant une bonne précision altimétrique et une bonne résolution spatiale. Les résultats montrent que la résolution spatiale est centimétrique et que la précision altimétrique est de 0,039 m (RMS calculé sur 124 points de contr?le). La haute précision altimétrique et la haute résolution spatiale permettent de maximiser la précision des calculs de volume sédimentaire et ainsi diminuer les co?ts associés à l’erreur de calcul, notamment lors de projets de recharge sédimentaire de plage. Cela permet aussi d’assurer le positionnement exact de limites marégraphiques et géomorphologiques. En comparaison à des profils topographiques obtenus par méthodes classiques, la forte densité des nuages de points observés avec un SLM permet de cartographier des formes morphologiques de faible amplitude diminuant ainsi l’erreur due à l’interpolation.
关键词： LiDAR mobile,résolution spatiale,précision altimétrique,suivi topographique,géomorphologie c?tière
更新于2025-09-23 15:21:21
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A Heuristic Method for Power Pylon Reconstruction from Airborne LiDAR Data
摘要： Object reconstruction from airborne LiDAR data is a hot topic in photogrammetry and remote sensing. Power fundamental infrastructure monitoring plays a vital role in power transmission safety. This paper proposes a heuristic reconstruction method for power pylons widely used in high voltage transmission systems from airborne LiDAR point cloud, which combines both data-driven and model-driven strategies. Structurally, a power pylon can be decomposed into two parts: the pylon body and head. The reconstruction procedure assembles two parts sequentially: firstly, the pylon body is reconstructed by a data-driven strategy, where a RANSAC-based algorithm is adopted to fit four principal legs; secondly, a model-driven strategy is used to reconstruct the pylon head with the aid of a predefined 3D head model library, where the pylon head’s type is recognized by a shape context algorithm, and their parameters are estimated by a Metropolis–Hastings sampler coupled with a Simulated annealing algorithm. The proposed method has two advantages: (1) optimal strategies are adopted to reconstruct different pylon parts, which are robust to noise and partially missing data; and (2) both the number of parameters and their search space are greatly reduced when estimating the head model’s parameters, as the body reconstruction results information about the original point cloud, and relationships between parameters are used in the pylon head reconstruction process. Experimental results show that the proposed method can efficiently reconstruct power pylons, and the average residual between the reconstructed models and the raw data was smaller than 0.3 m.
关键词： 3D pylon reconstruction,airborne LiDAR,Metropolis–Hastings sampler,RANdom Sample Consensus (RANSAC),simulated annealing
更新于2025-09-23 15:21:21
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A novel approach for the extraction of cloud motion vectors using airglow imager measurements
摘要： The paper explores the possibility of implementing an advanced photogrammetric technique, generally employed for satellite measurements, on airglow imager, a ground-based remote sensing instrument primarily used for upper atmospheric studies, measurements of clouds for the extraction of cloud motion vectors (CMVs). The major steps involved in the algorithm remain the same, including image processing for better visualization of target elements and noise removal, identification of target cloud, setting a proper search window for target cloud tracking, estimation of cloud height, and employing 2-D cross-correlation to estimate the CMVs. Nevertheless, the implementation strategy at each step differs from that of satellite, mainly to suit airglow imager measurements. For instance, climatology of horizontal winds at the measured site has been used to fix the search window for target cloud tracking. The cloud height is estimated very accurately, as required by the algorithm, using simultaneous collocated lidar measurements. High-resolution, both in space and time (4 min), cloud imageries are employed to minimize the errors in retrieved CMVs. The derived winds are evaluated against MST radar-derived winds by considering it as a reference. A very good correspondence is seen between these two wind measurements, both showing similar wind variation. The agreement is also found to be good in both the zonal and meridional wind velocities with RMSEs < 2.4 m s?1. Finally, the strengths and limitations of the algorithm are discussed, with possible solutions, wherever required.
关键词： lidar measurements,photogrammetric technique,MST radar,cloud motion vectors,ground-based remote sensing,airglow imager
更新于2025-09-23 15:21:21
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Estimating forest structural attributes using UAV-LiDAR data in Ginkgo plantations
摘要： Estimating forest structural attributes in planted forests is crucial for sustainably management of forests and helps to understand the contributions of forests to global carbon storage. The Unmanned Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR) has become a promising technology and attempts to be used for forest management, due to its capacity to provide highly accurate estimations of three-dimensional (3D) forest structural information with a lower cost, higher flexibility and finer resolution than airborne LiDAR. In this study, the effectiveness of plot-level metrics (i.e., distributional, canopy volume and Weibull-fitted metrics) and individual-tree-summarized metrics (i.e., maximum, minimum and mean height of trees and the number of trees from the individual tree detection (ITD) results) derived from UAV-LiDAR point clouds were assessed, then these metrics were used to fit estimation models of six forest structural attributes by parametric (i.e., partial least squares (PLS)) and non-parametric (i.e., k-Nearest Neighbors (k-NN) and Random Forest (RF)) approaches, within a Ginkgo plantation in east China. In addition, we assessed the effects of UAV-LiDAR point cloud density on the derived metrics and individual tree segmentation results, and evaluated the correlations of these metrics with aboveground biomass (AGB) by a sensitivity analysis. The results showed that, in general, models based on both plot-level and individual-tree-summarized metrics (CV-R2 = 0.66–0.97, rRMSE = 2.83–23.35%) performed better than models based on the plot-level metrics only (CV-R2 = 0.62–0.97, rRMSE = 3.81–27.64%). PLS had a relatively high prediction accuracy for Lorey’s mean height (CV-R2 = 0.97, rRMSE = 2.83%), whereas k-NN and AGB (CV-R2 = 0.95, performed well rRMSE = 8.81%). For the point cloud density sensitivity analysis, the canopy volume metrics showed a higher dependence on point cloud density than other metrics. ITD results showed a relatively high accuracy (F1-score > 74.93%) when the point cloud density was higher than 10% (16 pts·m?2). The correlations between AGB and the metrics of height percentiles, lower height level of canopy return densities and canopy cover appeared stable across different point cloud densities when the point cloud density was reduced from 50% (80 pts·m?2) to 5% (8 pts·m?2).
关键词： Ginkgo,UAV,LiDAR,Forest structural attributes,Point cloud density,Planted forest
更新于2025-09-23 15:21:21
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AIP Conference Proceedings [Author(s) PROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2017 (ICCMSE-2017) - Thessaloniki, Greece (21–25 April 2017)] - Geomorphic record of historical ferrous metallurgy in Ma?a Panew and Czarna River valleys (Poland) – Analysis of DEM from airborne LiDAR
摘要： Ferrous metallurgy, through the centuries of its activity contributed the transformation of the natural landscape. We can find information on the time of functioning of iron works in historical sources. Among historians, there is an opinion that the traces of iron works activity are not visible in the field, but using GIS methods we can identify different types of objects related to ferrous metallurgy like dams, canals, smelter ponds and charcoal kilns. The aim of the study was to identify imprints of ferrous metallurgy in relief of two valleys in Southern Poland. The study was conducted in Ma?a Panew and Czarna River valleys where ferrous metallurgy, based on historical sources, has started in the 14th century and declined in the end of the 19th century. The tools used for identification objects related to ferrous metallurgy were standard shaded relief visualization techniques. We created models of terrain elevation with hillshading and spatial density of 0.2 m. During the analysis of DEM images we detected objects interpreted as traces of smelter ponds with accompanying dams and canals, and oval objects recognized as remnants of charcoal kilns. Large number and vast distribution of relief features related to ferrous metallurgy, charcoal kilns in particular, clearly indicate that the historical smelting and ironwork activity natural environment of studied areas was transformed. Relief of valley floors, in particular, was a subject of change.
关键词： LiDAR images,charcoal kilns,iron ponds,dikes,ferrous metallurgy
更新于2025-09-23 15:21:21