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व्युत्क्रम दूरी भारण (IDW)×भौगोलिक भारित प्रतिगमन (GWR)×
क्षेत्रस्थानिक विश्लेषणस्थानिक विश्लेषण
परिवारRegression modelRegression model
उद्भव वर्ष19682002
प्रवर्तकDonald ShepardFotheringham, Brunsdon & Charlton
प्रकारDeterministic spatial interpolationLocal spatial regression
मौलिक स्रोतShepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. Proceedings of the 23rd ACM National Conference, 517–524. DOI ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
उपनामIDW, inverse distance interpolation, Shepard's method, ters mesafe ağırlıklı enterpolasyonGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
संबंधित35
सारांशInverse distance weighting is a simple, deterministic method for estimating values at unsampled locations by taking a weighted average of nearby measured points, where closer points carry more weight. Introduced by Donald Shepard in 1968, it embodies the first law of geography — near things are more related than distant things — and is one of the most widely used interpolation methods in GIS for mapping continuous fields such as rainfall, elevation, or pollution from scattered samples.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
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ScholarGateविधियों की तुलना करें: Inverse Distance Weighting · Geographically Weighted Regression. 2026-06-20 को यहाँ से प्राप्त https://scholargate.app/hi/compare