GEUS Bulletin, 2023 Estimating a covariance model for kriging purposes is traditionally done using semivariogram analyses, where an empirical semivariogram is calculated, and a chosen semivariogram model, usually defined by a sill and a range, is fitted. We demonstrate that
Frederik Alexander Falk +1 more
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Spring Rainfall Spatial Pattern Analysis in Northwest of Iran with Spatial Statistics Methods [PDF]
نشریه جغرافیا و برنامهریزی, 2021 Introduction Rainfall is amongst the most important climatic elements with a lot of spatial and temporal changes; in contrast to the other climatic phenomena, rainfall features more notable movement complexity.
Hossein Asakereh +2 more
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Minimax Approach for Semivariogram Fitting in Ordinary Kriging [PDF]
IEEE Access, 2020 This research paper aims to analyze the minimax approach used in the semivariogram fitting process that forms one stage of the kriging operation performed for interpolation. The conventional method uses the weighted least squares fit for various theoretical functions such as stable, exponential, spherical.
Andie Setiyoko +2 more
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On the classification error rates in terms of semivariograms for Gaussian universal kriging models
Lithuanian Journal of Statistics, 2021 Bayes multiclass classification of spatial Gaussian data following the universal kriging model is considered. The closed-form expressions for the maximum likelihood (ML) estimator of regression parameters and the actual error rate (AER) in terms of ...
Kęstutis Dučinskas, Lina Dreižienė
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E-Jurnal Matematika, 2015 Spatial data is data that is presented in the geographic of an object, related to the location, shape and relationship of the earth in space. One of example of spatial data is rainfall. To determine the value of rainfall in an area, built to predict rain
PUTU MIRAH PURNAMA D. +2 more
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Comparison Between Iterative Least Square and Nonparametric Epanechnikov Kernel in Semivariogram Modeling, Case study: Urban Land Cover in East Java Province [PDF]
ITM Web of ConferencesLandcover is an example of spatial data that contains location coordinate information along with the variables measured at each location, namely height, slope, and curvature.
Sari Kurnia Novita +3 more
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Comparison of fitting results obtained using different semivariogram models.
, 2022 Comparison of fitting results obtained using different semivariogram models.
Liang Zijun (12446819) +3 more
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Semivariogram models for estimating fig fly population density throughout the year
Pesquisa Agropecuária Brasileira, 2014 The objective of this work was to select semivariogram models to estimate the population density of fig fly (Zaprionus indianus; Diptera: Drosophilidae) throughout the year, using ordinary kriging.
Mauricio Paulo Batistella Pasini +2 more
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Spatial variability of air dry bulb temperature and black globe humidity index in a broiler house during the heating phase [PDF]
Engenharia Agrícola, 2013 The air dry-bulb temperature (t db),as well as the black globe humidity index (BGHI), exert great influence on the development of broiler chickens during their heating phase. Therefore, the aim of this study was to analyze the structure and the magnitude
Patrícia F. Ponciano +4 more
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Comparison of semivariogram models in rain gauge network design [PDF]
, 2019 The well-known geostatistics method (variance-reduction method) is com- monly used to determine the optimal rain gauge network. The main problem in geostatis- tics method to determine the best semivariogram model in order to be used in estimating the ...
Mohd. Daud, Zalina +4 more
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