When representing the geometry of voxelized three-dimensional scenes (especially if they have been voxelized to high resolutions) in a naive—uncompressed—form, one may end up using vast amounts of data. These can easily attack the availab...
With the advancement of service robot technology, the demand for higher boundary precision in indoor semantic segmentation has increased. Traditional methods of extracting Euclidean features using point cloud and voxel data often neglect geodesic inf...
Although voxel models have been applied to address diverse problems in computer-aided design processes, their role in multi-domain data integration in digital architecture and planning has not been extensively studied. The primary objective of this s...
In autonomous vehicles, the LiDAR and radar sensors are indispensable components for measuring distances to objects. While deep-learning-based algorithms for LiDAR sensors have been extensively proposed, the same cannot be said for radar sensors. LiD...
As an important component of urban vegetation, street trees play an important role in maintenance of environmental quality, aesthetic beauty of urban landscape, and social service for inhabitants. Acquiring accurate and up-to-date inventory informati...
This study proposes a voxel-based design approach based on the subtractive mechanism of shading envelopes and attributes information of point cloud data in tropical climates. In particular, the proposed method evaluates a volumetric sample of new bui...
Reversible data hiding in encrypted media enables auxiliary information to be embedded into protected content while allowing exact recovery of the processed data. Although this technique has been extensively investigated for images and surface-based...
Efforts in the domain of building studies involve the use of a diverse array of geomatic sensors, some providing invaluable information in the form of three-dimensional point clouds and associated registered properties. However, managing the vast amo...
The accuracy of point cloud processing results is greatly dependent on the determination of the voxel size and shape during the point cloud voxelization process. Previous studies predominantly set voxel sizes based on point cloud density or the size...
X-ray CT imaging is an important three-dimensional non-destructive testing technique, which has been widely applied in various fields. However, segmenting image voxels as discrete material compositions may lose information below the voxel size. In th...
The advancement of LiDAR technology has enabled more detailed evaluations of forest structures. The so-called “Volumetric pixel (voxel)” has emerged as a new comprehensive approach. The purpose of this study was to estimate plot-level above-ground bi...
The leaf area density (LAD) within a tree canopy is very important for the understanding and modeling of photosynthetic studies of the tree. Terrestrial light detection and ranging (LiDAR) has been applied to obtain the three-dimensional structural p...
Voxel-based data structures, algorithms, frameworks, and interfaces have been used in computer graphics and many other applications for decades. There is a general necessity to seek adequate digital representations, such as voxels, that would secure...
Canopy base height (CBH) is a key parameter used in forest-fire modeling, particularly crown fires. However, estimating CBH is a challenging task, because normally, it is difficult to measure it in the field. This has led to the use of simple estimat...
Magnetic resonance spectroscopy (MRS) is a noninvasive technique for measuring metabolite concentration. It can be used for preclinical small animal brain studies using rodents to provide information about neurodegenerative diseases and metabolic dis...
Understanding socio-ecological systems and the discovery, recovery and adaptation of land knowledge are key challenges for sustainable land use. The analysis of sustainable agricultural systems and practices, for instance, requires interdisciplinary...
Urban function labels in multi-dimensional geo-data cubes (GDCs) assign a single dominant function to each voxel, discarding within-voxel composition. This study extends multi-dimensional grid-point (MDGP) scaling from isotropic two-dimensional raste...
3D least-squares matching is an algorithm that allows to measure subvoxel-precise displacements between two data sets of computed tomography voxel data. The determination of precise displacement vector fields is an important tool for deformation anal...
In uneven-aged forests, trees of different diameters, heights, and ages are located in a small area, which is due to the felling of individual trees or groups of trees, as well as small-scale natural disturbances. In this article, we present an objec...
Accurate classification of individual tree types is a key component in forest inventory, biodiversity monitoring, and ecological modeling. This study evaluates and compares multiple Machine Learning (ML) and Deep Learning (DL) approaches for tree typ...
Deep learning models for three-dimensional (3D) data are increasingly used in domains such as medical imaging, object recognition, and robotics. At the same time, the use of AI in these domains is increasing, while, due to their black-box nature, the...
This perspective paper critically examines the emerging role of voxel-based analysis (VBA), also referred to as image-based data mining (IBDM), in dose–toxicity modeling for post-radiotherapy toxicity assessment. These techniques offer promisin...
This paper proposes an automated framework that utilizes Light Detection and Ranging (LiDAR) point cloud data to map and detect road obstacles that impact drivers’ field of view at urban intersections. The framework facilitates the simulation of a dr...
Currently, three-dimensional (3D) point clouds are widely used in the field of remote sensing and mapping, including the measurement of living vegetation volume (LVV) in cities. However, the existing quantitative methods for LVV measurement are mainl...
High-resolution traffic data, comprising trajectories of individual road users, are of great importance to the development of Intelligent Transportation Systems (ITS), in which they can be used for traffic microsimulations and applications such as co...
Digital transformation projects have been undertaken in the land transportation and railway industries, including the introduction of various smart construction technologies. With the expansion of policies to increase the share of railway transportat...
Current software solutions for solar-radiation modeling in 3D focus on the urban environment. Most of the published tools do not implement methods to consider complex objects, such as urban greenery in their models or they expect a rather complex 3D...
Convergence and rockmass failure are significant hazards to personnel and physical assets in underground tunnels, caverns, and mines. Mobile Laser Scanning Systems (MLS) can deliver large volumes of point cloud data at a high frequency and on a large...
To support design-consistent modeling of large-span trusses from field scans, this study aims to develop and evaluate a workflow guided by CAD priors for isolating load-bearing members and completing structural topology in severely occluded regions....
Point clouds are very common tools used in the work of documenting historic heritage buildings. These clouds usually comprise millions of unrelated points and are not presented in an efficient data structure, making them complicated to use. Furthermo...
Magnetic resonance spectroscopy (MRS), as a noninvasive method for molecular structure determination and metabolite detection, has grown into a significant tool in clinical applications. However, the relatively low signal-to-noise ratio (SNR) limits...
In vivo magnetic resonance spectroscopy (MRS) has two modalities, single-voxel (SV) and multivoxel (MV), in which one or more contiguous grids of SVs are acquired. Purpose: To test whether MV grids can be classified with models trained with SV. Metho...
Information extraction and three-dimensional (3D) reconstruction of buildings using the vehicle-borne laser scanning (VLS) system is significant for many applications. Extracting LiDAR points, from VLS, belonging to various types of building in large...
Ionospheric tomography, an effective method for reconstructing 3-D electron density, is traditionally pictured by 3-D IED (ionospheric electron density) slices to express ionospheric disturbances, which may overlook the critical information in 3-D sp...
A new algorithm for detecting branch attachments on stems based on a voxel approach and line object detection by a voting procedure is introduced. This algorithm can be used to evaluate the quality of stems by giving the branch density of each standi...
Accurate stem volume estimation is fundamental to forest resource inventory and carbon stock assessment. Traditional methods rely on destructive sampling, whereas terrestrial laser scanning (TLS) offers a non-destructive alternative. However, the acc...
In recent years, deep learning techniques for processing 3D point cloud data have seen significant advancements, given their unique ability to extract relevant features and handle unstructured data. These techniques find wide-ranging applications in...
In recent years, navigation has attracted widespread attention across various fields, such as geomatics, robotics, photogrammetry, and transportation. Modeling the navigation environment is a key step in building successful navigation services. While...
Studies that use magnetic resonance velocimetry (MRV) to assess flows through porous media require a sufficiently small voxel size to determine the velocity field at a sub-pore scale. The smaller the voxel size, the less information is lost through t...
Unmanned Aerial Vehicles (UAVs) are increasingly integral to construction site management, supporting monitoring, inspection, and data collection tasks. Effective UAV path planning is essential for maximizing operational efficiency, particularly in c...
Terrestrial laser scanning of forest structure is used increasingly in place of traditional technologies; however, deriving physical parameters from point clouds remains challenging because LiDAR returns do not have defined areas or volumes. While vo...
In order to reduce the loss of laser point cloud appearance contours by point cloud lightweighting, this paper takes the laser point cloud data of the segment beam of the expressway viaduct as a sample. After comparing the downsampling algorithm from...
Drone lidar has the potential to provide detailed measurements of vertical forest structure throughout large areas, but a systematic evaluation of unsampled forest structure in comparison to independent reference data has not been performed. Here, we...
Plane segmentation is a basic yet important process in light detection and ranging (LiDAR) point cloud processing. The traditional point cloud plane segmentation algorithm is typically affected by the number of point clouds and the noise data, which...
Aboveground biomass (AGB) of shrubs and low-statured trees constitutes a substantial portion of the total carbon pool in temperate forest ecosystems, contributing much to local biodiversity, altering tree-regeneration growth rates, and determining ab...
Segmentation and classification of urban range data into different object classes have several challenges due to certain properties of the data, such as density variation, inconsistencies due to missing data and the large data size that require heavy...
Amplified MRI (aMRI) is a promising new technique that can visualize pulsatile brain tissue motion by amplifying sub-voxel motion in cine MRI data, but it lacks the ability to quantify the sub-voxel motion field in physical units. Here, we introduce...
Three dimensional (3D) green volume is an important tree factor used in forest surveys as a prerequisite for estimating aboveground biomass (AGB). In this study, we developed a method for accurately calculating the 3D green volume of single trees fro...
Point cloud classification is a key technology for point cloud applications and point cloud feature extraction is a key step towards achieving point cloud classification. Although there are many point cloud feature extraction and classification metho...
The segmentation of urban scene mobile laser scanning (MLS) data into meaningful street objects is a great challenge due to the scene complexity of street environments, especially in the vicinity of street objects such as poles and trees. This paper...
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