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A Geostatistical Investigation into the Effective Spatiotemporal Coverage of Road Weather Information Systems in Alberta, Canada
2018
Journal of Advanced Transportation
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The findings of this research offer insight for constructing a detailed spatiotemporal RWIS database to manage and deploy different types of RWISs, optimize winter road maintenance resources, and provide ...
To meet such demand, this study presents an innovative geostatistical approach to quantitatively analyze the spatiotemporal variations of the road weather and surface conditions. ...
Acknowledgments This research work was jointly supported by the National Natural Science Foundation of China (61703236), Shandong Provincial Natural Science Foundation, China (ZR2017QF014, ZR2018MF027), and ...
doi:10.1155/2018/5179694
fatcat:kng7bhcnqbeexja76wgoz2ibzi
Spatiotemporal forecast with local temporal drift applied to weather patterns in Patagonia
2020
SN Applied Sciences
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Finally, its results are comparable with the ARIMA Models Panels with the advantage that it can generate maps with spatiotemporal correlation and better than the often-used methods (stkriging and global ...
Using this principle, this study aims to decompose the time series of a spatiotemporal dataset as external drifts and estimate its residuals by spatiotemporal kriging. ...
The spatiotemporal ordinary kriging as computed to all three datasets with their respective variogram models. ...
doi:10.1007/s42452-020-2814-0
fatcat:xsnbqnjvtzakvmbmrzbzteaso4
Combining Geostatistics and Remote Sensing Data to Improve Spatiotemporal Analysis of Precipitation
2021
Sensors
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The purpose of this research is to use publicly available remote sensing product data computed from geostationary, polar and near-polar satellites and radar to improve space-time modeling and prediction ...
In addition, it represents an alternative option for the improved modeling of precipitation variations in space and time. ...
in the spatiotemporal variogram. ...
doi:10.3390/s21093132
pmid:33946422
fatcat:zdd7leyyfrgtxlvmspfanlg7dy
Identification of long-term annual pattern of meteorological drought based on spatiotemporal methods: evaluation of different geostatistical approaches
2014
Natural Hazards
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The selected geostatistical methods have been compared based on leave-one-out cross-validation procedure and spatiotemporal distribution of SPI values. ...
The purpose of this paper was to produce meteorological drought occurrence probability maps for different SPI classes by spatiotemporal analysis. ...
variogram/covariance models. ...
doi:10.1007/s11069-014-1499-3
fatcat:o6gkalxwv5ej7ojowbzt4icfby
Implementation of a Parallel GPU-Based Space-Time Kriging Framework
2018
ISPRS International Journal of Geo-Information
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In the study of spatiotemporal geographical phenomena, the space-time interpolation method is widely applied, and the demands for computing speed and accuracy are increasing. ...
Using the OpenCL framework to integrate central processing unit (CPU) and graphic processing unit (GPU) computing resources, a parallel spatiotemporal kriging algorithm was implemented, and three experiments ...
s (h s ), γ t (h t ), and γ st (h s , h t ) are the spatial, temporal, and spatiotemporal variograms, C s (h s ), C t (h t ), and C st (h s , h t ) are the spatial, temporal, and spatiotemporal covariance ...
doi:10.3390/ijgi7050193
fatcat:mrx7kb3apvhitni75zuec4mdl4
Modeling Spatiotemporal Rainfall Variability in Paraíba, Brazil
2019
Water
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As a consequence of this behavior, there is a need to model the rainfall distribution jointly with space and time. ...
The purpose of this study was to provide a detailed framework to use the spatiotemporal kriging to model the space-time variability of precipitation data in Paraíba, which is located in the northeastern ...
Acknowledgments: The main author wish to acknowledge the administrative support provided by the UFLA (Federal University of Lavras) and UFGD (Federal University of Grande Dourados) and the technical support ...
doi:10.3390/w11091843
fatcat:k7ip7ouhvvdvxdto4vors6qazu
Page 142 of Environmetrics Vol. 17, Issue 2
[page]
2006
Environmetrics
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Two cases are considered, respectively corresponding to a separable and a non-separable covariance model for the spatiotemporal input process which is fractionally integrated, under suitable conditions ...
ANISOTROPIC LONG-RANGE DEPENDENCE SPATIOTEMPORAL MODELS
In this section, anisotropic long-range dependence spatiotemporal models are formulated by applying
fractional integration operators of different ...
Water shortage risk assessment using spatiotemporal flow simulation
2016
Geoscience Letters
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Like many other environmental variables, streamflows are asymmetric and non-Gaussian. Such properties exacerbate the difficulties in spatiotemporal modeling of streamflow data. ...
It generally involves modeling the temporal variation and spatial correlation of streamflow data at different sites. ...
of semi-variogram modeling. ...
doi:10.1186/s40562-016-0034-7
fatcat:x6i467emkzdgzfiquhm3rrfv3u
Spatiotemporal geostatistical analysis of precipitation combining ground and satellite observations
2021
Hydrology Research
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This work presents a methodology that combines satellite and ground observations leading to improved spatiotemporal mapping and analysis of precipitation. ...
This work introduces an improved spatiotemporal approach for precipitation mapping. ...
In addition, the compact form of the Spartan variogram model provides faster (by about 36% running Matlab in Windows 10 environment on a computer with CPU: i7-8750, 2.2 GHz, RAM: 16G) space-time interpolation ...
doi:10.2166/nh.2021.160
fatcat:4wezf22gybb47fztx5m4qq5bsy
Reconstructing Cloud Contaminated Pixels Using Spatiotemporal Covariance Functions and Multitemporal Hyperspectral Imagery
2019
Remote Sensing
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This paper proposes not only the use of image time-series, but also the implementation of a geostatistical model that considers the spatiotemporal correlation between them to fill the cloud-related gaps ...
To do this, cloudy pixels were masked and a parametric family of non-separable covariance functions was automated fitted, using a composite likelihood estimator. ...
Spatiotemporal Covariance Model For the cloudy scene, t 8 , a spatiotemporal covariance function was fitted for predicting reflectance across cloud affected pixels. ...
doi:10.3390/rs11101145
fatcat:kbxlxlosxvfkfcgghlxgyj2rxe
Implementation of the Kalman Filter for a Geostatistical Bivariate Spatiotemporal Estimation of Hydraulic Conductivity in Aquifers
2020
Water
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, the smallest number of cells with values above 2 m2/day2 correspond to the bivariate spatiotemporal case) and the best agreement between the estimated errors and the selected model variance (SMSE values ...
Geostatistical tools were used to describe the correlation between simulated spatiotemporal data of hydraulic head and the spatial distribution of the hydraulic conductivity in a group of model nodes. ...
Acknowledgments: To CONACyT for the PhD scholarship provided to Olmos-Trujillo E. and Pacheco-Guerrero A.I. Thanks also to Edgar Saucedo Barrios for his support in the model proposition. ...
doi:10.3390/w12113136
fatcat:q5nnnlsmijf2tlhclnndxhuvv4
A class of covariate-dependent spatiotemporal covariance functions for the analysis of daily ozone concentration
2011
Annals of Applied Statistics
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In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. ...
We discuss the properties of the induced covariance functions and discuss methods to assess its dependence on local covariate information by means of a simulation study and the analysis of data observed ...
The authors wish to thank the Editor, Associate Editor and referees for their helpful comments which greatly improved the manuscript. ...
doi:10.1214/11-aoas482
pmid:24772199
pmcid:PMC3998774
fatcat:an2jxftrsbhd7ipxwoways7g4e
Space-Time Geostatistics for Geography: A Case Study of Radiation Monitoring Across Parts of Germany. 地理学的时空地统计学:横跨德国部分区域的辐射监测的案例研究
2010
Geographical Analysis
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The space-time variable of interest is treated as a sum of independent stationary spatial, temporal, and spatiotemporal components, which leads to a sum-metric space-time variogram model. ...
Therefore, conventional geostatistics needs to be extended with methods that estimate and quantify spatiotemporal variation and use it in spatiotemporal interpolation and stochastic simulation. ...
Acknowledgements We thank Ulrich Stoehlker and Sven Burbeck (Bundesamt fü r Strahlenschutz, Freiburg, Germany) for making the case study data available and for their valuable help with interpretations. ...
doi:10.1111/j.1538-4632.2010.00788.x
fatcat:snkg2n5rdjfbrhq6urjqi4deey
Modeling Seasonal and Spatiotemporal Variation: The Example of Respiratory Prescribing
2017
American Journal of Epidemiology
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We demonstrate a strategy for modeling data that exhibit both seasonal trend and spatiotemporal correlation, using an application to respiratory prescribing. ...
After adjusting for the fitted values from the DHR model, we did not detect any remaining spatiotemporal correlation in the model's residuals. ...
The spatiotemporal variogram was computed for distances 1, 2, … 20 kilometers and time differences of 0, 1, 2, and 3 months. Finally, we examined practice-level random effects. ...
doi:10.1093/aje/kww246
pmid:28453604
pmcid:PMC5860516
fatcat:44soq3iqazhcrc343pfcwnhvpa
Problems in space-time kriging of geohydrological data
1990
Mathematical Geology
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These problems can be grouped into four general categories: (1) fundamental differences with respect to spatial problems, (2) data characteristics, (3) structural analysis including valid models, and ( ...
Adequate consideration of these problems leads to more appropriate estimation techniques for spatiotemporal data. ...
and no official endorsement should be inferred. ...
doi:10.1007/bf00890508
fatcat:bcmrm46vzvht5lkyz3eah77fh4
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