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Beyond global metrics: A geographically weighted framework for exploring multi-source spatial data validation

delete2026-04-25
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PRE
AI
B
Binbin Lu *
S
Siao Luo
P
Peng Yue
董冠鹏 cover
董冠鹏 (Guanpeng Dong)
L
Lex Comber
DOI：10.1016/j.compenvurbsys.2026.102450delete
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Abstract

Abstract

En 中文
• A local validation framework based on Geographically Weighted (GW) techniques is proposed. • GW indicators (GW ME, MAE, MRE, RMSE, CC, and univariate GWR) provide spatially detailed assessments for multi-source spatial datasets. • Bandwidth selection critically balances fine-scale detail and large-scale comparability. • Case study with GPWv4, GPCD, and NPC7 demonstrates the effectiveness and scalability of this local validation framework.
Keywords:
Geographically Weighted (GW) techniques
Multi-source spatial datasets
Local validation framework
Bandwidth selection
Spatial data validation

Journal

C
computers, environment and urban systems
IF:
0
Papers:
33
Citations:
0

Organization

H
Henan University
Scholars:
2.0K
Papers: 658
Citations: 4
W
Wuhan University
Scholars:
5.0K
Papers: 1.7K
Citations: 10.0W
U
University of Leeds
Scholars:
978
Papers: 514
Citations: 4.3W
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