Journal Report

INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

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Journal Information
Journal Title
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
Publisher
TAYLOR & FRANCIS LTD
ISSN
1365-8816
E-ISSN
1362-3087
Database
Clarivate
Domain
Health Sciences, Life Sciences, Physical Sciences, Social Sciences
Classification History
Year A+ A B C
2026 ✓ ✓
2025 ✓ ✓
2024 ✓ ✓
2023 ✓ ✓
2021/2022 ✓ ✓
2020 ✓ ✓
2019 ✓ ✓
2018 ✓
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Recent Articles
Regional gravity: a zoning heuristic for detecting heterogeneous distance decay effect in spatial interaction
Hao Guo, Lei Dong, Xiaodong Zhang et al.
2026-11-9 Pages 1-33
The task utility gap in human mobility modeling: evidence from environmental exposure assessment
Xin Jin, Zihan Kan, Sylvia Y. He et al.
2026-11-4 Pages 1-27
Pop-HSTM: a multi-scale coupled framework for dynamic population modeling
Dehao Li, Sijin Li, Haiping Zhang et al.
2026-11-4 Pages 1-28
From social media to flood 3D scenes: leveraging large language models and knowledge graphs for flood spatiotemporal evolution representation
Qingqing Ran, Weilian Li, Juan Liu et al.
2026-11-3 Pages 1-33
Representing spatial dependence and heterogeneity <i>via</i> deep kriging and compressed sensing for urban human activity intensity forecasting
Kaiyuan Lei, Kaiqi Chen, Min Deng
2026-10-30 Pages 1-30
Unraveling vegetation carbon storage using STVisX: a spatiotemporal visual explainable AI framework
Chuan Chen, Yeming Lao, Youjia Liang et al.
2026-10-29 Pages 1-25
Residualized Local Conditional Mutual Information (LCMI): a scalable information-theoretic framework for interpretable and nonlinear spatially varying effect modelling
Lingbo Liu
2026-10-29 Pages 1-24
Omission error in geographically weighted regression
Binbin Lu, Bo Wu, Guanpeng Dong et al.
2026-10-15 Pages 1-27
Efficient computation for continuous Hausdorff and average Euclidean distance between polylines
Barry J. Kronenfeld, Barbara P. Buttenfield, Lawrence V. Stanislawski et al.
2026-10-13 Pages 1-24
Rethinking neighbourhood boundaries for urban planning: a data-driven framework for perception-based delineation
Shubham Pawar, Craig Anderson, Armando Marino et al.
2026-10-8 Pages 1-22
Articles retrieved from Crossref.
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Printed: November 9, 2026 12:19