A graph-based segmentation technique has been tailored to segment airborne LiDAR points which, unlike images, are irregularly distributed. In our method, every point is labeled as a node and interconnected graph extended its neighborhood, defined in 4-D feature space: the spatial coordinates (x,y,z) reflection intensity. The interconnections between pairs of neighboring nodes weighted based on distance space. consists an iterative process classification into homogeneous groups their...

Topographic laser scanning is a remote sensing method to create detailed 3D point cloud representations of the Earth's surface. Since data acquisition expensive, simulations can complement real given certain premises are met: (i) models scene and scanner available (ii) modelling beam-scene interaction simplified computationally feasible while physically realistic level. A number simulators for different purposes exist, which we enrich by presenting HELIOS++. HELIOS++ an open-source...

Road extraction from Light Detection and Ranging (LiDAR) has become a hot topic over recent years. Nevertheless, it is still challenging to perform this task in fully automatic way. Experiments are often carried out small datasets with focus on urban areas unclear how these methods less urbanized sites. Furthermore, some require the manual input of critical parameters, such as an intensity threshold. Aiming address issues, paper proposes method for road points suitable different landscapes....

Over the last two decades, a wide range of applications have been developed from Light Detection and Ranging (LiDAR) point clouds. Most LiDAR-derived products require distinction between ground non-ground points. Because this, filtering its being one most studied topics in literature robust methods are nowadays available. However, these designed to work with offline data they generally not well suited for real-time scenarios. Aiming address this issue, paper proposes an efficient method...

Light Detection and Ranging (LiDAR) has attracted the interest of research community in many fields, including object classification earth surface. In this paper we present an object-based method for airborne LiDAR that distinguishes three main classes (buildings, vegetation ground) based only on information. The key components our proposal are following: First, point cloud is stored octree its efficient processing normal vector each estimated using adaptive neighborhood algorithm. Then,...

Abstract. Light Detection and Ranging (LiDAR) is nowadays one of the most used tools to obtain geospatial data. In this paper, a method detect characterise power lines both high low voltage their surroundings from 3D LiDAR point clouds exclusively proposed. First, identify points global search candidate carried out based on height each compared its neighbours. Then, Hough Transform (HT) applied set extract catenaries that belong line, allowing identification conductor individually. Finally,...

Purpose The slope of roads is one the most important elements to be monitored prevent landslides and ensure safety vehicles. This fact particularly relevant in areas such as Galicia (Spain), where, due its orography, slopes always are a factor road construction projects. Method Typically, visually by inspectors only case problems do they use measuring equipment (e.g. extensometer, inclinometer). aim this work introduce routine mobile LiDAR systems for monitoring slopes. Results & Discussion...

In this paper, a graph-based technique originally intended for image processing has been tailored the segmentation of airborne LiDAR points, that are irregularly distributed. Every point is labeled as node and interconnected graph extended to its neighborhood defined in 4D feature space (x, y, z, reflection intensity). The interconnections between pairs neighboring nodes weighted based on distance space. consists an iterative process classification into homogeneous groups their similarity....

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Light detection and ranging is being a hot topic in the remote sensing field, development of robust point cloud processing methods essential for adoption this technology. In order to understand, evaluate, show these methods, it key visualize their outputs. Several visualization tools exist, although usually difficult find suited one specific application. On hand, proprietary (closed source) projects are not flexible enough because they cannot be modified adapt them particular applications....

In this paper we present a simulation study for comparing differents methods estimating the prediction error rate in discrimination problem. We consider Cross-validation, Bootstrap and Bayesian such as problem, while also elaborating on both simple by smoothing techniques. observe procedure lead to improvements estimation of true rule, specially case smooth estimator, whose reduction M.S.E. resulted from high positive correlation between its estimations based method.