2025 November - 47 articles
As road users and means of transport in Germany become more diverse, we must better understand the causes and influencing factors of serious crashes. The aim of this work is to develop an AI-supported analysis approach that identifies and clearly vis...
CerMapp is a multi-platform and system application designed to address a critical gap in veterinary public health: the lack of a standardized, national-scale geodatabase for wildlife diseases. This gap has long hindered the effective application of G...
To reveal the cross-scale trade-offs and synergies of ecosystem services (ESs) in resource-based cities, this study took Xingtai City, Hebei Province, as a case. Six ESs—water yield (WY), soil retention (SDR), habitat quality (HQ), urban coolin...
Urban building change detection (UBCD) is essential for urban planning, land-use monitoring, and smart city analytics, yet bi-temporal optical methods remain limited by spectral confusion, occlusions, and weak sensitivity to structural change. To ove...
Benford’s Law, also known as the First-Digit Law, describes the non-uniform distribution of leading digits in many naturally occurring datasets. This phenomenon can be observed in data such as financial transactions, tax records, or demographic...
This research aims to develop a novel spatial optimization model for locating obnoxious facilities. While various obnoxious facility location problems (OFLP) have been introduced, the optimal spatial arrangements in existing models may not adequately...
Accurate prediction of urban grid-scale population inflow is crucial for smart city management and emergency response. However, existing methods struggle to model spatial heterogeneity and quantify prediction uncertainty, limiting their accuracy and...
In the context of sustainable development, the concept of active mobility plays a key role in modern urban areas. To evaluate active mobility in these areas, we formulate a framework for characterising active mobility by calculating street network in...
Contour lines, as the primary elements of fundamental geospatial data, have long been a research focus for similarity measurement. With the evolution of cartographic generalization, the representation of contour lines across varying scales must maint...
Recent advancements in remote sensing and geospatial processing tools have ushered in a new era of mapping and monitoring landscape changes across various scales. This progress is critical for understanding and anticipating the underlying drivers of...
The chorematic method represents an innovative and contemporary approach for organizing tourist space, supporting the sustainable regional development of the future UNESCO Geopark, and guiding research, evaluation, and tourism monitoring activities i...
The Dvorak technique has represented a fundamental tool for understanding the power of tropical cyclones based on their shape and geometric evolution. However, it should be noted that the Dvorak technique is purely morphological in nature and was dev...
Virtual reality (VR) creates immersive environments that allow users to interact with digital content, fostering a sense of presence and engagement comparable to real-world experiences. VR360 technology, combined with affordable head-mounted displays...
GPS tracking has made ski injury data abundant, yet few studies have mapped where incidents actually occur or how those patterns differ between skiers and snowboarders. To address this gap, we analyzed 8719 GPS-located incidents (4196 skier; 4523 sno...
Collaborative mapping has emerged in recent decades as a key practice for producing open geospatial knowledge and fostering critical citizenship. However, several studies have shown that these platforms may reproduce existing gender inequalities, bot...
Emergency department (ED) overcrowding has become a critical public health issue worldwide, driven by increasing demand and limited healthcare resources. This study analyzes the spatio-temporal variability of ED visits at Royo Villanova Hospital (Zar...
Detecting anomalous pedestrian behaviors is critical for enhancing safety in dense urban environments, particularly in complex back streets where movement patterns are irregular and context-dependent. While extensive research has been conducted on tr...
The rapid expansion of mobile user behavior data has made next-Point-of-Interest (POI) recommendation increasingly vital for enhancing personalized location-based services. However, the non-uniform spatio-temporal distribution of user behavior poses...
The housing prices are crucial to the sustainable development of the real estate market. Nowadays, few academic attempts have focused on the impact of multi-dimensional accessibility on housing prices in a large-scale area. This study utilized machin...
The cross-scale fusion and consistent representation of cross-source heterogeneous vector polygon data are fundamental tasks in the field of GIS, and they play an important role in areas such as the refined management of natural resources, territoria...
A proactive traffic safety approach provides a forward-looking method for managing traffic and preventing accidents by identifying high-risk conditions before they occur. Previous studies have often focused on historical crash data or demographic fac...
Location-based services (LBSs) are a crucial element of the Internet of Things (IoT) and have garnered significant attention from both researchers and users, driven by the rise of wireless devices and a growing user base. However, the use of LBS-enab...
Assessing the accessibility of urban metro stations is essential for optimizing metro system planning and improving travel efficiency for residents. This study proposes an innovative evaluation framework—the CWM-GRA-TOPSIS model—for compr...
Geographic Named Entity Recognition (Geo-NER) is a crucial task for extracting geography-related entities from unstructured text, and it plays an essential role in geographic information extraction and spatial semantic understanding. Traditional appr...
Normal faults play a key role in accommodating extensional deformation within the South Tibet Rift. The MS 6.8 Tingri earthquake of 7 January 2025 therefore provides a rare opportunity to investigate how these normal faults accommodate east–wes...
Accurate volumetric modeling of indoor spaces is essential for emerging 3D cadastral systems, yet existing workflows often rely on manual intervention or produce surface-only models, limiting precision and scalability. This study proposes and validat...
The automatic reconstruction of existing buildings has gained momentum through the integration of Building Information Modeling (BIM) into architecture, engineering, and construction (AEC) workflows. This study presents a hybrid methodology that comb...
Rapid urbanization elevates land surface temperature (LST) through complex urban spatial relationships, intensifying the urban heat island (UHI) effect. This necessitates efficient methods to analyze surface urban heat island (SUHI) factors to help d...
Wildfire risk assessment requires integrating heterogeneous geospatial data to capture complex environmental dynamics. This study develops a hierarchical multimodal fusion framework combining high-resolution aerial imagery, historical fire data, topo...
Accurate and robust feature matching across multi-view urban imagery is fundamental for urban mapping, 3D reconstruction, and large-scale spatial alignment. Real-world urban scenes involve significant variations in viewpoint, illumination, and occlus...
Geolocating Twitter users from social media data holds significant value in applications such as targeted advertising, disaster response, and social network analysis. However, existing social network-based geolocation methods tend to focus primarily...
Building function identification plays a crucial role in providing basic data for urban planning, management, and various intelligent applications. Today, building function identification methods using Street View Images (SVIs) have made significant...
Urban streets serve as essential spaces for commercial activities and social interaction, yet the mechanisms through which their landscape elements influence consumption vitality remain insufficiently explored. Focusing on Lixia District, Jinan, Chin...
Under the dual pressures of climate change and rapid urbanization, extreme heat events pose growing risks to densely populated megaregions. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA), a densely populated and economically vital r...
Accurate and up-to-date data on built-up areas are crucial for urban planning, disaster management, and sustainable development, yet Romania still lacks a unified, official database. In this study we integrated the three widely used global data sourc...
Lagrangian Relaxation (LR) is an effective method for solving spatial optimization problems in geospatial analysis and GIS. Among others, it has been used to solve the classic p-median problem that served as a unified local model in GIS since the 199...
Image-based geo-localization is a challenging task that aims to determine the geographic location of a ground-level query image captured by an Unmanned Ground Vehicle (UGV) by matching it to geo-tagged nadir-view (top-down) images from an Unmanned Ae...
Street vitality has become a crucial metric for smart city management. Classical theories qualitatively explain that street vitality originates from the dynamic interaction between people and spatial carriers, yet the threshold effect within this pro...
Google Earth Engine (GEE) has become one of the most widely used platforms for Land Use and Land Cover (LULC) research, offering cloud-based access to petabyte-scale datasets and scalable analytical tools. While earlier reviews provided valuable over...
Building clustering is a key challenge in cartographic generalization, where the goal is to group spatially related buildings into semantically coherent clusters while preserving the true distribution patterns of urban structures. Existing methods of...
The Yellow River Basin faces severe challenges in water security and ecological protection: at the basin scale, complex hydrological processes and fragile ecosystems undermine the water security pattern; at the local scale, waterlogging risks have in...
The safe operation of low-altitude UAVs is crucial for the effective utilization of low-altitude airspace, necessitating the development of appropriate risk assessment methods to evaluate the associated operational risks. However, current research pr...
Depth completion aims to achieve high-quality dense depth prediction from a pair of synchronized sparse depth map and RGB image, and it plays an important role in many intelligent applications, including urban mapping, scene understanding, autonomous...
Land use classification based on multi-modal data fusion has gained significant attention due to its potential to capture the complex characteristics of urban environments. However, effectively extracting and integrating discriminative features deriv...
The escalating environmental crisis and the threat posed by environmental crime demand more effective prevention strategies. The predictive mapping of environmental crimes can address this challenge by improving monitoring and response. This study pr...
The study is referenced by interdisciplinary theories, i.e., routine activity, and social cohesion, to investigate the impacts of sport clubs and events on London’s expressive crimes at varied geographical scales, by utilizing Geographical-temp...
Accurate placement and geometry of simulation plots are essential for spatially explicit modeling of forest ecosystems. This study introduces a Monte Carlo-based approach for optimizing the spatial alignment of simulation plots with their source poly...
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