Results 11 to 20 of about 32,193 (219)
Regression Kriging in the Productive Capacity of Planted Forests [PDF]
Floresta e AmbienteThe objective of this study was to evaluate the classification of productive capacity in eucalyptus stands using regression kriging. The study was carried out in 62 stands with clonal plantations of Eucalyptus sp.
Emanuel José Gomes de Araújo +7 more
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Prediction by Regression and kriging for Spatial Data with Application [PDF]
المجلة العراقية للعلوم الاحصائية, 2011 This study deals with the prediction of the non-stationary spatial stochastic process. The prediction is done by two techniques which are regression technique (generalized least square estimation) and universal kriging technique.
doaj +3 more sources
Temperature prediction based on a space-time regression-kriging model. [PDF]
J Appl Stat, 2020 Many phenomena exist in the space-time domain, often with a low data sampling rate and sparsely distributed network of observed points. Therefore, spatio-temporal interpolation with high accuracy is necessary. In this paper, a space-time regression-kriging model was introduced and applied to monthly average temperature data.
Li S, Griffith DA, Shu H.
europepmc +3 more sources
Object-Based Area-to-Point Regression Kriging for Pansharpening [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2021 IEEE Optical earth observation satellite sensors often provide a coarse spatial resolution (CR) multispectral (MS) image together with a fine spatial resolution (FR) panchromatic (PAN) image. Pansharpening is a technique applied to such satellite sensor images to generate an FR MS image by injecting spatial detail taken from the FR PAN image while ...
Yihang Zhang 0001 +7 more
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Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single and binary component solids [PDF]
, 2014 A combination of systematic density functional theory (DFT) calculations and machine learning techniques has a wide range of potential applications.
Maekawa, Tomoya +3 more
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Tropical Agricultural Research, 2018 This study was conducted to explore performances of multivariate geostatistical techniques, co-kriging and regression kriging in contrast to univariate ordinary kriging, to generate detailed maps of soil texture by using proximally sensed apparent ...
R. A. A. S. Rathnayaka +2 more
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Augmenting Geostatistics with Matrix Factorization: A Case Study for House Price Estimation
ISPRS International Journal of Geo-Information, 2020 Singular value decomposition (SVD) is ubiquitously used in recommendation systems to estimate and predict values based on latent features obtained through matrix factorization.
Aisha Sikder, Andreas Züfle
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Regression and Classification by Zonal Kriging
CoRR, 2018 Consider a family $Z=\{\boldsymbol{x_{i}},y_{i}$,$1\leq i\leq N\}$ of $N$ pairs of vectors $\boldsymbol{x_{i}} \in \mathbb{R}^d$ and scalars $y_{i}$ that we aim to predict for a new sample vector $\mathbf{x}_0$. Kriging models $y$ as a sum of a deterministic function $m$, a drift which depends on the point $\boldsymbol{x}$, and a random function $z ...
Jean Serra +2 more
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Soil and Water Research, 2013 North Bohemia belongs to one of the most heavily industrialized and polluted regions in Europe. The enormous acid deposition which culminated in the 1970s has largely contributed to the accelerated acidification process in the soils and consequently to ...
Radim VAŠÁT +4 more
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Random Forest Spatial Interpolation
Remote Sensing, 2020 For many decades, kriging and deterministic interpolation techniques, such as inverse distance weighting and nearest neighbour interpolation, have been the most popular spatial interpolation techniques.
Aleksandar Sekulić +4 more
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