An Improved Distance Metric for the Interpolation of Link-based Traffic Data using Kriging: A Case Study of a Large-scale Urban Road Network

International Journal of Geographical Information ScienceInternational Journal of Geographical Information Science, Volume 26, Issue 4, 2012

Haixiang Zou, Yang Yue, Qingquan Li & Anthony G.O. Yeh

“The interpolation of link-based traffic data is an important topic for transportation researchers and engineers. In recent years the kriging method has been used in traffic data interpolation from the viewpoint of spatial analysis. This method has shown promising results, especially for a large-scale road network. However, existing studies using the Euclidean distance metric, which is widely used in traditional kriging, fail to accurately describe the spatial distance in a road network. In this article we introduce road network distance to describe spatial distance between road links, and we propose an improved distance metric called approximate road network distance (ARND), based on the isometric embedding theory, for solving the problem of the invalid spatial covariance function in kriging caused by the non-Euclidean distance metric. An improved Isomap algorithm is also proposed for obtaining the ARND metric. This study is tested on a large-scale urban road network with sparse road-link travel speeds derived from approximately 1200 ‘floating cars’ (GPS-enabled taxis). Comparison was conducted on both the Euclidean distance metric and the ARND metric. The validation results show that the use of the ARND metric can obtain better interpolation accuracy in different time periods and urban regions with different road network structures. Therefore, we conclude that the improved distance metric has the ability for improving kriging interpolation accuracy for link-based traffic data within real situations, providing more reliable basic traffic data for various traffic applications.”

Temporal and Spatial Analysis of Phosphate Concentrations in Surface Waters in the ‘Gelderse Vallei’, the Netherlands

Master thesis, Universiteit Utrecht, 30 March 2012

Simon van Dijk

“High phosphate concentrations in surface waters are regarded as bad for the ecosystem integrity and leads to loss of aesthetic, ecological and economic value of the system. Therefore the European Union set targets for phosphate concentrations in the Water Framework Directive, which must be met by 2015 and ultimately by 2027. For the majority of the surface waters in the ‘Gelderse Vallei’ these targets are not met at the moment.

Spatial distribution of the mean Total-P values in mg/L over the period 2005-2010.

Spatial distribution of the mean Total-P values in mg/L over the period 2005-2010.

“This study focuses on the temporal and spatial trends of phosphate concentrations in the ‘Gelderse Vallei’, with respect to the Water Framework Directive. An extensive dataset with phosphate concentrations is provided by water board ‘Vallei & Eem’ and is analyzed by using ordinary linear regressions and ANOVAs for the temporal trends. For the spatial analyses maps are made to provide quick visual output of spatial patterns.

“For the temporal analyses no clear statistical trends are shown, however 70% of all ordinary linear regressions were negative, possibly indicating decreasing phosphate concentrations in the ‘Gelderse Vallei’. From the spatial analyses phosphate concentrations tend to decrease in northern direction. The change in phosphate between time periods does not show a clear spatial pattern.

“Considering the standards from the Water Framework Directive, respectively 60% and 50% of the studied surface waters will not meet the standards by 2015 and 2027. For water board ‘Vallei & Eem’ this means that measures should be taken to meet these standards. Furthermore, more attention should be given to the south of the ‘Gelderse Vallei’, for phosphate concentrations in the north are meeting the standards by 2015 and 2027 while in the south most surface waters do not meet the standards by 2015 and 2027.

“Extending the dataset, extending the amount of analyzed surface waters and extending research on explanations of the trends can contribute to a better understanding of the trends and therefore to stronger conclusions and indicating possible measures.”