Many applications in Earth sciences require spatial prediction, that is, obtaining a continuous scalar field from a set of discrete scalar data points on the Earth's surface. Such applications include model-data comparisons and derivation of continuous scalar fields as input for Earth system models. The advantage of kriging as an interpolation method is that it provides predictions with confidence intervals for datasets of irregularly distributed points in space. However, the theory of kriging for non-Euclidean domains such as oblate spheroids (e.g., the Earth's surface) is poorly developed, and existing kriging algorithms for global interpolation oftentimes cannot guarantee the validity of their predictions. Here, we present Global-Krigger...
Abstract- We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of sp...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Abstract- We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of sp...
This paper explores the use of universal Kriging to interpolate sparsely-sampled satellite-based atm...
Kriging interpolation is an important supplement method for the lack of high-resolution reference ma...
The interpolation f spatial data has been considered in many different forms. The various forms of k...
Spatial interpolation is performed to predict data values of unseen locations based on the distribut...
Geographical information systems could be improved by adding procedures for geostatistical spatial a...
Global change research requires data for large expanses of the earth. Data are normally obtained by ...
A wide class of interpolation methods, including thin-plate and tension splines, kriging, sinc funct...
In this survey we present various classical geostatistical prediction methods with a focus on interp...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Abstract- We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of sp...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Abstract- We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of sp...
This paper explores the use of universal Kriging to interpolate sparsely-sampled satellite-based atm...
Kriging interpolation is an important supplement method for the lack of high-resolution reference ma...
The interpolation f spatial data has been considered in many different forms. The various forms of k...
Spatial interpolation is performed to predict data values of unseen locations based on the distribut...
Geographical information systems could be improved by adding procedures for geostatistical spatial a...
Global change research requires data for large expanses of the earth. Data are normally obtained by ...
A wide class of interpolation methods, including thin-plate and tension splines, kriging, sinc funct...
In this survey we present various classical geostatistical prediction methods with a focus on interp...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Abstract- We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of sp...
Kriging is a widely employed method for interpolating and estimating elevations from digital elevati...
Abstract- We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of sp...