Cross-scale analysis of cluster correspondence using different operational neighborhoods

Cluster correspondence analysis examines the spatial autocorrelation of multi-location events at the local scale. This paper argues that patterns of cluster correspondence are highly sensitive to the definition of operational neighborhoods that form the spatial units of analysis. A subset of multi-location events is examined for cluster correspondence if they are associated with the same operational neighborhood. This paper discusses the construction of operational neighborhoods for cluster correspondence analysis based on the spatial properties of the underlying zoning system and the scales at which the zones are aggregated into neighborhoods. Impacts of this construction on the degree of cluster correspondence are also analyzed. Empirical analyses of cluster correspondence between paired vehicle theft and recovery locations are conducted on different zoning methods and across a series of geographic scales and the dynamics of cluster correspondence patterns are discussed.      

Atmospheric Artifact Compensation in Ground-Based DInSAR Applications

In this letter, a coherence-based technique for atmospheric artifact removal in ground-based (GB) zero-baseline synthetic aperture radar (SAR) acquisitions is proposed. For this purpose, polarimetric measurements acquired using the GB-SAR sensor developed at the Universitat Politecnica de Catalunya are employed. The heterogeneous environment of Collserola Park in the outskirts of Barcelona, Spain, was selected as the test area. Data sets were acquired at X-band during one week in June 2005. The effects of the atmosphere variations between successive zero-baseline SAR polarimetric acquisitions are treated here in detail. The need to compensate for the resulting phase-difference errors when retrieving interferometric information is put forward. A compensation technique is then proposed and evaluated using the control points placed inside the observed scene.     

Income distribution dynamics and cross-region convergence in Europe

This paper presents a continuous version of the model of distribution dynamics to analyse the transition dynamics and implied long-run behaviour of the EU-27 NUTS-2 regions over the period 1995–2003. It departs from previous research in two respects: first, by introducing kernel estimation and three-dimensional stacked conditional density plots as well as highest density regions plots for the visualisation of the transition function, based on Hyndman et al. (J Comput Graph Stat 5(4):315–336, 1996), and second, by combining Getis’ spatial filtering view with kernel estimation to explicitly account for the spatial dimension of the growth process. The results of the analysis indicate a very slow catching-up of the poorest regions with the richer ones, a process of shifting away of a small group of very rich regions, and highlight the importance of geography in understanding regional income distribution dynamics.