Constraint-based Interpolation
Constraint-Based Interpolation is a population interpolation method that integrates ancillary spatial constraints—such as land use, infrastructure, or administrative boundaries—to guide and refine the distribution of population counts across target spatial units, thereby ensuring that interpolated estimates conform to known biophysical or sociopolitical limitations.
8
Publications
206
Citations
18
Authors
10
Institutions
Publications per year
2017–2026
2
Parents
8
Bilateral interpolation filters for image size conversion
Seungjoon Yang, Kihyun Hong · 2005 · 13 citations
1–5 of 8
18
Schlumberger (British Virgin Islands), British Virgin Islands
2 publications · 103 citations
2
h-index
2
h-index
1
h-index
1
h-index
1
h-index
1–5 of 18
10
Stanford University
Stanford, United States
2 h-index
2 publications
103 citations
University of Nebraska–Lincoln
Lincoln, United States
1 h-index
2 publications
22 citations
Northern University of Malaysia
Jitra, Malaysia
1 h-index
1 publications
15 citations
Max Planck Institute for Informatics
Saarbrücken, Germany
1 h-index
1 publications
44 citations
Ludwig-Maximilians-Universität München
Munich, Germany
1 h-index
2 publications
20 citations

Universiti Teknologi Petronas
Ipoh, Malaysia
1 h-index
1 publications
15 citations

LMU Klinikum
Munich, Germany
1 h-index
2 publications
20 citations
Technical University of Munich
Munich, Germany
1 h-index
1 publications
44 citations
1–8 of 10
2 publications · 103 citations
2
h-index
1 publications · 44 citations
1
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Conference · 1 publications · 11 citations
1
h-index
Conference · 1 publications · 10 citations
1
h-index
1 publications · 15 citations
1
h-index
1–5