Statistical depth is widely used as a powerful tool to measure the center-outward rank of multivariate and functional data. Recent studies have introduced the notion of depth to the temporal point process, which exhibits randomness in the cardinality...
Many techniques have been proposed to model space-varying observation processes with a nonstationary spatial covariance structure and/or anisotropy, usually on a geostatistical framework. Nevertheless, there is an increasing interest in point process...
The spatial structure of trees is a template for forest dynamics and the outcome of a variety of processes in ecosystems. Identifying the contribution and magnitude of the different drivers is an age-old task in plant ecology. Recently, the modelling...
Spatial statistics is a powerful tool for analyzing data that are illustrated as points or positions in a regular or non-regular state space. Techniques that are proposed to investigate the spatial association between neighboring positions are based...
We investigate the Optimal Obstacle Placement (OOP) problem under uncertainty, framed as the dual of the Optimal Traversal Path problem in the Stochastic Obstacle Scene paradigm. We consider both continuous domains, discretized for analysis, and alre...
Using spatial data in mobile applications has grown significantly, thereby empowering users to explore locations, navigate unfamiliar areas, find transportation routes, employ geomarketing strategies, and model environmental factors. Spatial database...
The application of a process model to investigate pine tree infestation caused by bark beetles is discussed. The analysis of this disease was carried out using spatial and spatio−temporal models of random point patterns. Spatial point patterns...
This paper presents a survey of georeferenced point clouds. Concentration is, on the one hand, put on features, which originate in the measurement process themselves, and features derived by processing the point cloud. On the other hand, approaches f...
Research Highlights: The spatial distribution of trees results from several ecological processes that can be difficult to measure. We applied a point process modelling approach that uses the diameter and species of neighbouring trees to represent int...
Real-time reconstruction of virtual scenes in response to changing physical conditions remains a challenge in manufacturing digital-twin systems. During manufacturing operations, changes in object positions, orientations, and spatial arrangements req...
In this paper, we analyze the tornado occurrences in the Unites States. To perform inference procedures for the spatio-temporal point process we adopt a dynamic representation of Log-Gaussian Cox Process. This representation is based on the decomposi...
Updating the most recent set of point cloud data is critical in autonomous driving environments. However, existing systems for point cloud data management often fail to ensure real-time updates or encounter situations in which data cannot be effectiv...
The decomposition of a point process is useful for the analysis of spatial patterns and in the discovery of potential mechanisms of geographic phenomena. However, when a local repulsive cluster is present in a complex heterogeneous point process, the...
Volunteer-contributed geographic data (VGI) is an important source of geospatial big data that support research and applications. A major concern on VGI data quality is that the underlying observation processes are inherently biased. Detecting observ...
Digital histology of human postmortem brain tissue is fundamental to understanding neurodegeneration, yet resolving the spatial organisation of neuroinflammatory markers remains challenging because manual scoring and scalar summaries capture only par...
Landscape archaeology has a long history of using predictive models to improve our knowledge of extant archaeological features around the world. Important advancements in spatial statistics, however, have been slow to enter archaeological predictive...
Competition between plants has an important role during the natural succession of forest communities. Niche separation between plants can reduce such interspecific competition and enable multispecies plant to achieve coexistence, although this propos...
Background/Objectives: Predicting the behavior of clear cell renal cell carcinoma (ccRCC) is challenging using standard-of-care histopathologic examination. Indeed, pathologic RCC tumor grading, based on nuclear morphology, performs poorly in predict...
The study was performed on two former sulphur mines located in Southeast Poland: Jeziórko, where 216.5 ha of afforested area was reclaimed after borehole exploitation and Machów, where 871.7 ha of dump area was reclaimed after open cast strip mining....
This study evaluates coordinate consistency in the static Korean Geodetic Datum 2002 (KGD2002) by comparing GNSS station positions derived independently from GAMIT/GLOBK and Bernese software. Using a nationwide network of approximately 3000 unified g...
In smart ports, accurately perceiving the motion state of a ship during berthing and unberthing is essential for the safety and efficiency of the ship and port. However, in actual scenarios, the obtained data are not always complete, which impacts th...
Cox processes, also called doubly stochastic Poisson processes, are used for describing phenomena for which overdispersion exists, as well as Poisson properties conditional on environmental effects. In this paper, we consider situations where spatial...
Lidar can effectively obtain three-dimensional information on ground objects. In recent years, lidar has developed rapidly from single-wavelength to multispectral hyperspectral imaging. The multispectral airborne lidar Optech Titan is the first comme...
The adjacency effect and non-uniform responses complicate the precise delimitation of the surface support of remote sensing data and their derived products. Thus, modeling spatial response characteristics (SRCs) prior to using remote sensing informat...
Estimating underlying mechanisms and dynamics from observed tree patterns can provide guidance for plantation management. Robinia pseudoacacia can reproduce via clonally produced ramets, leading to a complex distribution of stems. Three second genera...
Traffic crashes have become one of the key public health issues, triggering significant apprehension among citizens and urban authorities. However, prior studies have often been limited by their inability to fully capture the dynamic and complex natu...
This study seeks a scientific methodology for ecological leisure industry planners to contribute to a more ecologically friendly leisure industry. This study creates an environment suitability model (LIDES) for leisure industry development. This mode...
Accurate and thorough detection of rock mass discontinuities is essential in geotechnical engineering as they have a significant impact on the stability of underground and surface excavations, yet they are difficult to automate. In the work reported...
Accurately extracting semantic features of urban functional zones is crucial for understanding urban functional zone types and urban functional spatial structures. Points of interest provide comprehensive information for extracting the semantic featu...
The statistical evaluation of the spatial similarity of human caused fire patterns is an important issue for wildland fire analysis. This paper proposes a method based on observed data and on a statistical tool (homogeneity test) that is based on non...
Maps at different scales have different emphases on the information representation of point data. With a focus on large scales, this paper proposes an improved sequential displacement method. While existing approaches mostly use a fixed order to plac...
Point cloud analyzing and processing have attracted extensive attention due to their broad application in numerous sectors. Although many previous deep learning-based frameworks have had significant improvement, they often struggle with processing ef...
A class of models for non-Gaussian spatial random fields is explored for spatial field reconstruction in environmental and sensor network monitoring. The family of models explored utilises a class of transformation functions known as Tukey g-and-h tr...
Geospatial Artificial Intelligence (GeoAI) and the rapid advancement of 3D data acquisition technologies (e.g., LiDAR) have enabled scalable semantic interpretation of georeferenced large-scale 3D point clouds across different applications. 3D deep l...
To accurately assess students’ cognitive state of knowledge points in the learning process within the smart classroom, a knowledge tracing (KT) model based on classroom network characteristic learning engagement and temporal-spatial feature fus...
To further comprehend kinetic processes in the unsaturated zone, a series of soil column experiments was conducted to simulate downward and upward water movement under variable saturation conditions. High-accuracy spatial and temporal measurements we...
As sustainable structures like steel structures become more widely used, so do their construction issues. Improper lifting measures of long-span spatial steel structures may delay the construction period and even cause safety accidents. These problem...
The identification and spatial positioning of welds are key links in welding process matching and automatic welding path planning. Therefore, achieving automatic recognition and spatial positioning of weld point cloud features under online scanning i...
Lasers with average powers of several kilowatts have become an important tool for industrial applications. Temporal and spatial beam shaping was demonstrated to improve existing and enable novel applications. A very promising technology for both high...
Deformation can effectively reflect the structural state of concrete dams and, thus, establishing na accurate concrete dam deformation prediction model is important for dam health monitoring and early warning strategies. To address the problem that t...
Geographically neural network weighted regression is an improved model of GWR combined with a neural network. It has a stronger ability to fit nonlinear functions, and complex geographical processes can be modeled more fully. GNNWR uses the distance...
Point clouds obtained from laser scanning techniques are now a standard type of spatial data for characterising terrain surfaces. Some have been shared as open data for free access. A problem with the use of these free point cloud data is that the da...
The spatial response of rectangular pulse heterodyne phase-sensitive optical time-domain reflectometry (
In the application domain of large-scale high-precision measurement systems, accurately calibrating the precision of point position measurements is a pivotal issue. Traditional calibration methods rely on laser interferometers and high-precision disp...
This study proposes a local edge matching method with a sequence alignment technique for adjacent spatial datasets. By assuming that the common boundary edges of the datasets are point strings, the proposed method obtains the sequence for point edit...
This paper proposes a simulation-driven data processing framework that transforms multiphysics simulation outputs into interactive representations suitable for immersive scientific visualization and analysis. The proposed workflow uses Comsol Multiph...
The study of convolutional neural networks for 3D point clouds is becoming increasingly popular, and the difficulty lies mainly in the disorder and irregularity of point clouds. At present, it is straightforward to propose a convolution operation and...
As one of the major forms of geological disaster, landslides cause huge casualties and economic losses in China every year. Given the importance of landslide prediction, it is a challenging task due to difficulties in efficiently leveraging the spati...
Terrain feature points, such as the peaks and saddles, are the basic framework of surface topography and its undulations, which significantly affect the spatial distribution of surface topography. In the past, terrain feature points were extracted se...
The digital orthophoto is an image with both map geometric accuracy and image characteristics, which is commonly used in geographic information systems (GIS) as a background image. Existing methods for digital orthophoto generation are generally base...
of 56