2025 September - 47 articles
With the growing emphasis on running in urban health initiatives, understanding the spatiotemporal dynamics of running behavior has become essential for smart city development. This study harnesses multi-source big data—including running trajec...
Unmanned aerial vehicle (UAV) image object detection has become an increasingly important research area in computer vision. However, the variable target shapes and complex environments make it difficult for the model to fully exploit its features. In...
Precise object detection is fundamental to robust indoor navigation and localization. However, the practical deployment of deep learning-based detectors on mobile platforms is frequently impeded by their extensive parameter counts, substantial comput...
Allotment—the division of Native American reservations into individually-owned plots of land—has been extensively studied; yet there exists a paucity of reservation-level studies at granular geospatial scales, i.e., at the level of examin...
Clarifying how the community-scale built environment shapes the spatial heterogeneity of cardiovascular disease (CVD) prevalence is essential for precision urban health interventions. We integrated CVD prevalence data from the Guangxi Zhuang Autonomo...
In recent years, the rapid expansion of urban rail transit has significantly improved travel efficiency, yet it has also exacerbated spatial inequality in service coverage. Accessibility, as a fundamental metric for evaluating the equity of service d...
Maritime safety, environmental protection, and efficient traffic management increasingly rely on data-driven technologies. However, leveraging Automatic Identification System (AIS) data for predictive modelling faces two major challenges: the massive...
Based on provincial panel data from 2014 to 2023, this study employs the entropy weight method to construct an indicator system for measuring the logistical resilience of regions along China’s Belt and Road Initiative (BRI). The Dagum Gini coef...
Electric micro-mobility modes, such as e-scooters and e-bikes, are increasingly used in urban areas, posing challenges for accurate travel mode detection in mobility studies. Traditional supervised learning approaches require large labeled datasets,...
Unmanned Aerial Vehicles (UAVs) have become increasingly valuable for accident scene reconstruction and forensic surveying due to their flexibility and ability to capture high-resolution imagery. This study investigates the impact of flight altitude,...
Globally, land degradation represents both an environmental and socioeconomic challenge, necessitating continuous monitoring due to its impacts on ecosystem services. Given the substantial changes in land use and land cover in Maranhão, this s...
As the spatial carrier, the high-quality development of land complements the high-quality development of the economy and society. Imbalanced land use severely restricts regional high-quality development. This study uses panel data from 110 cities at...
This paper defines the term “graffiti” and outlines the origins of this concept. The terminological arrangement allowed for the subject of this research, i.e., illegal graffiti, to be situated in reality, i.e., an urban space. It was assu...
Urban and territorial development increasingly threatens the preservation of architectural heritage, often leading to degradation or loss. Many historic architectural works, once integral to community identity, now face the impacts of time and neglec...
Dividing large areas into smaller sub-areas is a common practice across many disciplines, with specific requirements determined by their intended use. This study focuses on preparing search sectors for locating missing persons in non-urban environmen...
With rapid urbanization and increasing emphasis on sustainable mobility, slow-moving traffic systems, including pedestrian and cycling infrastructure, have become critical to urban transportation and quality of life. Conventional assessment methods a...
Mapping lithology in areas with dense vegetation remains a major challenge for remote sensing, as plant cover tends to obscure the spectral signatures of underlying rock formations. This study tackles that issue by comparing the performance of three...
As the world’s most populous and geographically diverse continent, active fire occurrence in Asia exhibits pronounced spatiotemporal heterogeneity, driven by climactic and anthropogenic factors. However, systematic analyses of Asian fire occurr...
Urban green space, a vital part of urban ecosystems, offers inhabitants essential ecosystem services, and ensuring its fair distribution is essential to preserving their ecological well-being. This study uses Kaifeng City in Henan Province as the res...
In modern urban planning, the problem of bank location requires not only considering geographical factors but also integrating competitive elements to optimize resource allocation and enhance market competitiveness. This study addresses the multi-siz...
Geological Disasters (Geo-disasters) are common in the Ili River Basin, with extreme precipitation being a major triggering factor. As the frequency and intensity of these events increase, the associated risks also rise. This study proposes a hazard...
Ship trajectory prediction plays an important role in numerous maritime applications and services. With the development of deep learning technology, the deep learning prediction method based on Automatic Identification System (AIS) data has become on...
Heart disease remains the leading cause of death in both the United States and globally. Urban heat is increasingly recognized as a significant public health challenge, particularly in its connection to cardiovascular conditions. This study, conducte...
Toponym groups are fundamental units of quantitative spatial analysis of toponyms. Using suitable technical methods to investigate the spatial distribution and co-occurrence characteristics of these groups has significant implications for identifying...
This study develops an open, reproducible geospatial workflow to identify high-potential retail locations across Germany using a 1 km census grid and OpenStreetMap points of interest. It combines multi-criteria suitability modelling with spatial auto...
The Integrated Choice and Latent Variable (ICLV) model has been widely applied in travel behavior studies, yet its use in understanding pedestrian route choice remains very limited. This paper seeks to address this gap by analyzing data from a series...
Proportional symbol maps are a frequently used method of thematic cartography. Using an intuitive principle—the larger, the more—provides a simple and precise way of visualizing quantity in maps using geographic information systems (GIS)....
Landslide susceptibility mapping (LSM) faces persistent challenges in defining representative stable samples as conventional random selection often includes unstable areas, introducing spatial bias and compromising model accuracy. To address this, we...
Urban livability and sustainability are increasingly studied at the neighborhood scale, where built, social, and governance conditions shape residents’ everyday experiences. Yet existing assessment frameworks often fail to integrate subjective...
To achieve the objective of a “15 min living circle” for educational services, this study develops an integrated method for primary school site selection in Tianjin, China, by combining multi-source data and ensemble learning techniques....
Nowadays, various technologies exist with differing rendering performance for interactive web maps. These maps are consumed on devices with varying capabilities; therefore, choosing the best-performing library for a dataset is emphasized. Unlike exis...
Visibility of the sea plays a significant role in shaping spatial perception, property value, and planning decisions in coastal areas. While traditional GIS-based viewshed analysis provides useful tools for modeling visibility, it remains limited by...
This study examines how hotel characteristics and urban spatial context influence tourist satisfaction in Seoul, South Korea, by integrating sentiment analysis of online reviews with regression modeling. Drawing on 4500 TripAdvisor reviews from 75 ho...
As bike-sharing systems become increasingly integral to sustainable urban mobility, understanding their economic viability requires moving beyond conventional linear models to capture complex operational dynamics. This study develops an interpretable...
Traffic violations, the primary cause of road accidents, threaten public safety by disrupting traffic flow and causing substantial casualties and economic losses. Accurate spatiotemporal prediction of violations offers critical insights for proactive...
Spatial co-location patterns are used to describe the spatial associations between features, finding wide applications in geographic information systems, urban planning, and other fields. Traditional frameworks for mining spatial features typically c...
This study presents an initial evaluation of the heuristic landslide susceptibility map for the Municipality of Rio de Janeiro by comparing it with the official landslide inventory. The objective is to provide a first analysis of the accuracy of the...
Continental ecosystems are crucial constituents of the worldwide carbon process, and their carbon source and sink processes are highly sensitive to human-induced climate change. However, the spatiotemporal changes and principal determinants of carbon...
A large number of cities have created semantic 3D city models, but these models are rarely used as input data for simulations, such as noise and flooding, in the urban planning process. Reasons for this are that many simulations require detailed land...
There is voluminous literature concerning the scope of topological relations that span various embedding spaces from
In the context of the rapid development of e-commerce, the selection of optimal land plots for the construction of warehouse complexes that meet environmental, technical, and political requirements has become increasingly relevant. This task requires...
With the growing adoption of electric vehicles, optimizing the user experience of charging infrastructure has become critical. However, extracting actionable insights from the vast number of user reviews remains a significant challenge, impeding dema...
This study explores the potential of National Spatial Data Infrastructure (NSDI) to strengthen governance and policy processes in Pakistan. Drawing on the UNESCAP principles of good governance and the EGU policy cycle model, this research applies a d...
The solar angle of incidence is the angle between the sunlight and the normal on the impact surface. The lower the angle of incidence, the more sun radiation the surface can absorb. There are several methods for calculating of this angle. Determining...
This study investigates the spatiotemporal optimization of small-scale emergency infrastructure in high-density urban environments, using nucleic acid testing sites in Macao as a case study. The objective is to enhance emergency responsiveness during...
Recent approaches to geo-referencing X posts have focused on the use of language modelling techniques that learn geographic region-specific language and use this to infer geographic coordinates from text. These approaches rely on large amounts of lab...
Due to extensive soft soil and high human activities, Wuhan is a hotspot for land subsidence. This study used the time-series InSAR to calculate the spatial and temporal distribution map of subsidence in Wuhan and analyze the causes of subsidence. An...
