Results 61 to 70 of about 31,493 (191)
CROATIAN GEOSTATISTICAL DICTIONARY
Rudarsko-geološko-naftni Zbornik, 2013 Geostatistical model and interpretation very often are made by using computer programs. Consequently, application and development of geostatistics are closely connected with progress of informatics and computers.
Tomislav Malvić +1 more
doaj
A Framework for the Cross‐Validation of Categorical Geostatistical Simulations
Earth and Space Science, 2020 The mapping of subsurface parameters and the quantification of spatial uncertainty requires selecting adequate models and their parameters. Cross‐validation techniques have been widely used for geostatistical model selection for continuous variables, but
Przemysław Juda +2 more
doaj +1 more source
A geostatistical model based on Brownian motion to Krige regions in R2 with irregular boundaries and holes [PDF]
, 2019 Master's Project (M.S.) University of Alaska Fairbanks, 2019Kriging is a geostatistical interpolation method that produces predictions and prediction intervals.
Bernard, Jordy
core
Interpolating point spread function anisotropy
, 2012 Planned wide-field weak lensing surveys are expected to reduce the statistical errors on the shear field to unprecedented levels. In contrast, systematic errors like those induced by the convolution with the point spread function (PSF) will not benefit ...
Courbin, F., Gentile, M., Meylan, G.
core +1 more source
A Stochastic Approach to Quantifying the Propagation of Uncertainty in Soil Organic Carbon Content
Journal of Plant Nutrition and Soil Science, Volume 189, Issue 1, Page 117-130, February 2026.ABSTRACT Background Precision agriculture (PA) is a site‐specific management approach that utilises spatiotemporal information to improve productivity while also promoting sustainability. Accurate estimates of soil properties, along with the uncertainty of these estimates, are necessary for decision‐making in PA.
Leonardo Inforsato +6 more
wiley +1 more source
Revista Brasileira de Ciências Ambientais, 2015 The detection and monitoring of environmental degradation requires both low-cost and easy-to-perform techniques. This study intended to conduct sampling and use geostatistics to predict the spatial variability of environmental degradation indicators. The
Sebastião Cavalcante de Sousa +4 more
doaj +1 more source
Weed mapping using techniques of precision agriculture [PDF]
Planta Daninha, 2015 The aim of this study was to identify and map the weed population in a no-tillage area. Geostatistical techniques were used in the mapping in order to assess this information as a tool for the localized application of herbicides.
F.C. ROCHA +5 more
doaj +1 more source
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.Abstract Accurate characterization of gravel structures is essential for understanding riverbed roughness, flow resistance, and sediment transport. However, quantifying the definitive characteristics of these gravel structures remains challenging due to the inherent complexity of particle spatial arrangement. This study presents an improved statistical
Jie Qin, Teng Wu
wiley +1 more source
Performing Spatial Variabilityof Peat Depth by Using Geostatistics
E3S Web of Conferences, 2018 Geostatistics has been knowns as a reliable tool to explore variability in space of any measured parameter. This research aims to study how peat depth change and vary in space using geostatistics aproach.
Zuhdi Mohd. +3 more
doaj +1 more source
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.Abstract Cokriging is a widely used geostatistical method for modeling the shallow groundwater table, often incorporating digital elevation models (DEMs) as secondary variables. However, existing approaches rarely include robust validation procedures to reduce local uncertainty or iteratively improve spatial predictions.
Massimiliano Schiavo, Daniele Pedretti
wiley +1 more source