Spatio-temporal Missing Data Imputation
Spatio-Temporal Missing Data Imputation is a computational method in spatial time series analysis that specifically reconstructs unobserved or corrupted observations by leveraging both spatial dependencies and temporal dynamics inherent in spatio-temporal datasets.
216
Publications
10.4K
Citations
645
Authors
292
Institutions
Publications per year
2017–2026
152
Variants
Spatiotemporal Missing Data Imputation
Parents
216
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292

McGill University
Montreal, Canada
8 h-index
13 publications
1.6K citations
Wuhan University
Wuhan, China
7 h-index
25 publications
1.8K citations

Chinese Academy of Sciences
Beijing, China
6 h-index
12 publications
571 citations
Institute of Geographic Sciences and Natural Resources Research
Beijing, China
6 h-index
14 publications
584 citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
6 h-index
18 publications
1.2K citations

Shanghai Jiao Tong University
Shanghai, China
5 h-index
6 publications
430 citations

Fuzhou University
Fuzhou, China
5 h-index
12 publications
491 citations
Nanyang Technological University
Singapore, Singapore
5 h-index
14 publications
943 citations
1–8 of 292
14 publications · 1.2K citations
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9 publications · 1.3K citations
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Repository · 6 publications · 251 citations
6
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TRR · 3 publications · 147 citations
5
h-index
4 publications · 160 citations
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