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ISPRS International Journal of Geo-Information, Volume 14, Issue 8

August 2025 - 39 articles

Cover Story: In this study, we propose the Multi-Channel Spatio-Temporal Data Fusion (MCST-DF) framework, designed to integrate heterogeneous “big” and “small” data sources across complex road networks. Leveraging a novel Residual Spatio-Temporal Transformer Network (RSTTNet), our method captures both fine-grained local dynamics and global spatio-temporal patterns. By introducing multi-scale temporal channels and hierarchical spatial modelling, the framework effectively addresses challenges of data mismatch, sparsity, and heterogeneity. Evaluated on London traffic flow data, our approach achieves over 89% prediction accuracy and outperforms several strong baselines. This work contributes a generalisable solution to spatio-temporal data fusion, with wide implications for urban mobility, infrastructure monitoring, and geospatial AI systems. View this paper
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Articles (39)

  • Article
  • Open Access
834 Views
27 Pages

Accurate side road detection is essential for traffic management, urban planning, and vehicle navigation. However, existing research mainly focuses on road network construction, lane extraction, and intersection identification, while fine-grained sid...

  • Article
  • Open Access
1,763 Views
23 Pages

A Novel Method for Estimating Building Height from Baidu Panoramic Street View Images

  • Shibo Ge,
  • Jiping Liu,
  • Xianghong Che,
  • Yong Wang and
  • Haosheng Huang

Building height information plays an important role in many urban-related applications, such as urban planning, disaster management, and environmental studies. With the rapid development of real scene maps, street view images are becoming a new data...

  • Article
  • Open Access
773 Views
21 Pages

Statistical data depth measures have been applied to density-based clustering techniques in an effort to achieve robustness in parameter selection via the affine invariant property of the depth measure. Specifically, the Mahalanobis depth measure is...

  • Article
  • Open Access
1,144 Views
22 Pages

Spatial association analysis is essential for understanding interdependencies, spatial proximity, and distribution patterns within spatial data. The spatial scale is a key factor that significantly affects the result of spatial association mining. Tr...

  • Article
  • Open Access
1,766 Views
24 Pages

A Spatio-Temporal Evolutionary Embedding Approach for Geographic Knowledge Graph Question Answering

  • Chunju Zhang,
  • Chaoqun Chu,
  • Kang Zhou,
  • Shu Wang,
  • Yunqiang Zhu,
  • Jianwei Huang,
  • Zhaofu Wu and
  • Fei Gao

In recent years, geographic knowledge graphs (GeoKGs) have shown great promise in representing spatio-temporal and event-driven knowledge. However, existing knowledge graph embedding approaches mainly focus on structural patterns and often overlook t...

  • Article
  • Open Access
1,886 Views
25 Pages

With the emergence of Survey 4.0, the oil and gas (O & G) industry is now considering spatial digital twins during their field design to enhance visualization, efficiency, and safety. O & G companies have already initiated investments in the...

  • Article
  • Open Access
1 Citations
2,189 Views
28 Pages

Automating Three-Dimensional Cadastral Models of 3D Rights and Buildings Based on the LADM Framework

  • Ratri Widyastuti,
  • Deni Suwardhi,
  • Irwan Meilano,
  • Andri Hernandi and
  • Juan Firdaus

Before the development of 3D cadastre, cadastral systems were based on 2D representations, which now require transformation or updating. In this context, the first issue is that existing 2D rights are not aligned with recent 3D data acquired using ad...

  • Article
  • Open Access
824 Views
22 Pages

Towards an Extensible and Text-Oriented Analytical Semantic Trajectory Framework

  • Damião Ribeiro de Almeida,
  • Cláudio de Souza Baptista,
  • Fabio Gomes de Andrade and
  • Anselmo Cardoso de Paiva

Semantically enriched trajectories have attracted growing interest in recent research, driven by the need for more expressive and context-aware movement data analysis. Two primary approaches have emerged for the storage and management of such data: m...

  • Article
  • Open Access
1,163 Views
22 Pages

Ride-pooling, as a sustainable mode of ride-hailing services, enables different riders to share a vehicle while traveling along similar routes. The COVID-19 pandemic led to the suspension of this service, but Transportation Network Companies (TNCs) s...

  • Article
  • Open Access
1,043 Views
27 Pages

XT-SECA: An Efficient and Accurate XGBoost–Transformer Model for Urban Functional Zone Classification

  • Xin Gao,
  • Xianmin Wang,
  • Li Cao,
  • Haixiang Guo,
  • Wenxue Chen and
  • Xing Zhai

The remote sensing classification of urban functional zones provides scientific support for urban planning, land resource optimization, and ecological environment protection. However, urban functional zone classification encounters significant challe...

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ISPRS Int. J. Geo-Inf. - ISSN 2220-9964