2013
DOI: 10.1016/j.apgeog.2013.07.012
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Spatial interpolation of temperature in the United States using residual kriging

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Cited by 126 publications
(76 citation statements)
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“…For each heavy metal, at least two hundred different combinations of scenarios and parameters were tested, and the best model result was used to create a relevant kriging surface in ArcGIS. The predicted water pollution data of the 174 cities was extracted from the kriging surface and validated by comparing them to the observed values using a paired t test and root-mean-square-error (RMSE) [45]. The optimal estimation data set for each heavy metal was identified based on the results of paired t test (p-value > 0.05) and smallest RMSE.…”
Section: Methodsmentioning
confidence: 99%
“…For each heavy metal, at least two hundred different combinations of scenarios and parameters were tested, and the best model result was used to create a relevant kriging surface in ArcGIS. The predicted water pollution data of the 174 cities was extracted from the kriging surface and validated by comparing them to the observed values using a paired t test and root-mean-square-error (RMSE) [45]. The optimal estimation data set for each heavy metal was identified based on the results of paired t test (p-value > 0.05) and smallest RMSE.…”
Section: Methodsmentioning
confidence: 99%
“…The ICBl units were located in an open, windless space. To observe the temperature changes, a Kriging interpolation map was generated for different temperatures using ArcGIS 10.0 [23]. To analyze error estimates, grid points on the right side of the ICBl, 15 cm apart, were inspected regularly.…”
Section: Temperature Changes In Icbl Longitudinal Sectionmentioning
confidence: 99%
“…Kriging models in ArcGIS were used to estimate the levels of five types of heavy metals from industrial wastewater. Previous studies have shown kriging to be an accurate method for data estimation because of its low bias [3,[51][52][53][54]. For each metal, at least 50 different scenarios with different parameters were tested, and the optimal model was identified by comparing root-mean-square deviation (RMSE) and paired t test results.…”
Section: Methodsmentioning
confidence: 99%