Picture of athlete cycling

Open Access research with a real impact on health...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

Explore open research content by Physical Activity for Health...


Li, Jing-si and Pan, Run-qiu and FAN, Fu-lin (2016) 基于Kriging模型的地面气温空间插值研究. Journal of Southwest China Normal University (Natural Science Edition), 41 (5). pp. 21-27. ISSN 1000-5471

Text (Li-etal-JSCNU-2016-Spatial-interpolation-of-surface-air-temperature-by-Kriging)
Li_etal_JSCNU_2016_Spatial_interpolation_of_surface_air_temperature_by_Kriging.pdf - Accepted Author Manuscript

Download (672kB) | Preview


This paper aims to describe spatial interpolation methods to estimate surface air temperatures (SATs). The SAT at a particular location where SAT observations are not available is estimated through a Kriging interpolation between SAT measurements from 192 meteorological sites at which daily SAT observations have been obtained. A temporal de-trending method based on a Fourier series is used to model and remove the annual trend in original data in order to ensure the stationarity of de-trended data from which kriging parameters are determined. Furthermore, a spatial or surface de-trending in terms of geographic coordinates including altitude, latitude and longitude of each location is adopted in a Kriging model. Besides a Kriging model, an inverse distance weighting (IDW) interpolation method is tested as a comparison. The accuracies of both spatial interpolation approaches are assessed by calculating and comparing their mean absolute error (MAE) and root mean square error (RMSE) when taking each meteorological site as the target location in a cross-validation procedure. The results show that the Kriging model performs better than the IDW method at 174 sites. In addition, the temporal and spatial de-trending methods make the main contribution to the accurate capture of spatial correlations of SATs in the study area in a Kriging process.