2025 June - 28 articles
Global High-Resolution Land Cover Maps (GHRLCs), characterized by spatial resolutions higher than 30 m per pixel, have become essential tools for environmental monitoring, urban planning, and climate modeling. Over the past two decades, new GHRLCs ha...
The generation of road interchange networks benefits various applications, such as vehicle navigation and intelligent transportation systems. Traditional methods often focus on common road structures but fail to fully utilize long-term trajectory con...
Unsupervised representation learning can train deep learning models to formally express the semantic connotations of objects in the case of unlabeled data, which can effectively realize the expression of the semantics of geospatial entity categories...
Accurate and detailed spatial data on wind energy infrastructure is essential for renewable energy planning, grid integration, and system analysis. However, publicly available datasets often suffer from limited spatial accuracy, missing attributes, a...
In recent years, with the development of sensor technology, the volume of spatial data has grown exponentially. However, this data is often unevenly distributed, and traditional indexing methods cannot predict the overall data distribution when data...
With the advancement of spatial positioning technology, trajectory data have been growing rapidly. Trajectory data record the spatiotemporal information and behavioral characteristics of moving objects, and in-depth analysis can provide decision supp...
Governments often plan multiple fire stations simultaneously to improve firefighting capabilities, but constructing them within limited resources and time remains a challenge. A spatial decision support model is proposed in this study to determine th...
Vegetation change profoundly influences ecosystem sustainability and human activities, with solar radiation serving as a primary driver. However, the effects of surface radiative forcing (SRF) and related factors on vegetation dynamics remain poorly...
Accurate address matching is crucial for the analysis, integration, and intelligent management of urban geospatial data and is also a key step in achieving geocoding. However, due to the complexity, diversity, and irregularity of address expression,...
Discovering spatially associated objects involves measuring objects’ similarities and retrieving associated objects. The integration of spatial topology and network models for discovering associated objects remains largely unexplored. Here, the...
Examining the relationship between built environment (BE) and urban vitality (UV) is beneficial for promoting urban planning, as it deepens the understanding of how spatial design shapes urban life and activity patterns. However, the nonlinear effect...
Integrating spatio-temporal kriging with machine learning improves estimation accuracy by addressing complex spatial and temporal variations in spatio-temporal phenomena. The improvement can be attributed to the enhanced flexibility of machine learni...
Geographic Information System (GIS)-based noise management is crucial in urban environments as it provides precise spatial analysis, helping to identify noise hotspots and optimize noise control measures. By integrating noise propagation models with...
Accurate clustering of buildings is a prerequisite for map generalization in densely populated urban data. Edge buildings at the edge of building groups, identified through human-eye recognition, may serve as boundary constraints for clustering. This...
Extensive scientific evidence underscores the importance of identifying spatiotemporal patterns for investigating urban dynamics. The recent proliferation of location-based social networks (LBSNs) facilitates the measurement of urban rhythms through...
The integration of artificial intelligence (AI), specifically through convolutional neural networks (CNNs), is paving the way for significant advancements in archaeological research. This study explores the innovative application of the so-called Mas...
Narrative mapping, an advanced geographic information visualization technology, presents spatial information episodically, enhancing readers’ spatial understanding and event cognition. However, during 3D scene construction, viewpoint selection...
Rapid acquisition of 3D reconstruction models of landslides is crucial for post-disaster emergency response and rescue operations. This study explores the application potential of Neural Radiance Fields (NeRF) technology for rapid post-disaster site...
In the context of digital transformation, examining the differences in commercial site selection and the factors influencing these decisions holds significant practical value for understanding market adaptation strategies across varying business mode...
As the diversity and complexity of geographic statistical data continue to increase, it becomes increasingly important to present multi-level information in order to meet a broader range of needs. In response to the limitations of existing visualizat...
Micro-terrain recognition plays a crucial role in the planning, design, and safe operation of transmission lines. To achieve intelligent and automatic recognition of micro-terrain surrounding transmission lines, this paper proposes an improved semant...
The recognition of point patterns in spatial vector data has important applications in geographic mapping and formation recognition. However, the application of traditional methods to spatial vector data faces two difficulties. Firstly, these data ar...
Recognizing functionally cohesive building groups is crucial for urban analysis, geospatial intelligence, and smart city applications. Traditional methods rely heavily on geometric information and often overlook the functional and semantic coherence...
While deep learning-based image matching methods excel at extracting high-level semantic features from remote sensing data, their performance degrades significantly under cross-daylight conditions and wide-baseline geometric distortions, particularly...
This study collected site and spatial morphological data from 63 typical aging community activity spaces and extracted 12 spatial types through statistical analysis. A parametric modeling tool was used to generate spatial models. Based on clearly def...
Digital tools, especially games, are increasingly important for enabling citizen participation in urban planning. Among these, Minecraft has been widely utilized to engage children, leveraging its virtual environment to represent geospatial data. How...
This study presents an innovative approach to mitigating the urban heat island (UHI) effect by constructing a cold island spatial pattern (CSP) from the perspective of landscape connectivity, integrating three-dimensional (3D) urban morphology and me...
As climate change intensifies, cities are experiencing more severe rainfall and frequent waterlogging. When rainfall exceeds the carrying capacity of urban drainage networks, it poses a significant risk to urban facilities and public safety, seriousl...
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