विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| स्थानीय क्रिगिंग (मूविंग-विंडो क्रिगिंग)× | ऑर्डिनरी क्रिगिंग× | |
|---|---|---|
| क्षेत्र | स्थानिक विश्लेषण | स्थानिक विश्लेषण |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 1990 | 1963 |
| प्रवर्तक≠ | Haas, T. C. | Georges Matheron (formalising D.G. Krige's empirical work) |
| प्रकार≠ | Spatial interpolation (local variant) | Geostatistical interpolation |
| मौलिक स्रोत≠ | Haas, T. C. (1990). Kriging and automated variogram modeling within a moving window. Atmospheric Environment, 24(7), 1759-1769. DOI ↗ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246-1266. DOI ↗ |
| उपनाम | moving-window kriging, local kriging interpolation, windowed kriging, neighborhood kriging | OK, kriging interpolation, geostatistical interpolation, BLUE spatial predictor |
| संबंधित≠ | 3 | 4 |
| सारांश≠ | Local Kriging is a spatially adaptive geostatistical interpolation method that restricts each prediction to a moving neighborhood of nearby observations, fitting a variogram model locally within that window. This allows spatial covariance structure to vary across the study region rather than imposing a single global variogram, making it better suited to large or non-stationary spatial fields. | Ordinary Kriging (OK) is the standard geostatistical method for interpolating a continuous spatial variable at unsampled locations. It derives optimal, unbiased weights from the spatial covariance structure of the data, making it the Best Linear Unbiased Predictor (BLUP) under stationarity assumptions. Unlike simpler distance-based methods, it also provides a prediction uncertainty (kriging variance) at every interpolated point. |
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