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To design effective strategies for sustainable urban resource management, it is essential to understand which urban characteristics underlie consumption patterns. We used multiple linear regression analyses to examine sixteen factors on their explanatory power for spatial variation in residential electricity, gas and water consumption in Amsterdam. Four models per resource were used, based on distinct spatial units aggregating high-resolution data: neighbourhoods, districts, 100 m squares and 500 m squares. We found twelve explanatory variables for spatial variability in consumption in total and nine or ten per resource. The number and relative importance of explanatory variables varies with the spatial units used. Overall, neighbourhood models explain variance in consumption data best (adjusted R² = 0.88, 0.86, 0.74). Income level and building type stand out for having high relative importance (top 4) in all four models for two of the three resources; migration history shows an important correlation with water consumption, which was not described hitherto. We conclude that explanatory variables for resource consumption are sensitive to size and shape of spatial units used. We recommend to use future high resolution studies for different resources of interest to determine which spatial and temporal resolutions of analysis can support urban planners and designers in formulating context-specific interventions.

This paper tests the quality of calculated 2D isovist variables as predictors of perceived landscape openness. An isovist is the calculated field of view from a given viewpoint in space. Three isovist variables were selected to estimate openness: the minimum radial, the maximum radial and the average radial. An experiment with 32 participants was conducted to compare values of these calculated variables with perceived openness. The comparison showed that two variables, the maximum radial and average radial, explained most of the variation of perceived openness for groups and individuals. The three calculated isovist variables were strongly correlated to their measured equivalents in the field, which were obtained with a binocular with a rangefinder. The isovist variables also showed strong correlations with their perceived equivalents obtained by the perception of the 32 participants, except at very long distances. This research shows that the selected isovist variables are good indicators for perceived landscape openness. (C) 2014 Elsevier B.V. All rights reserved.

In the last decade policy makers have increasingly recognized the need to include people's perceptions in methods for describing landscape quality. At the same time, a third wave of Geographic Information Systems (GIS) has become available that make it technically possible to model landscape quality in a realistic manner. However, as there is often a mismatch between science and policy, it remains unclear to what extent perception-based models developed by scientists can be useful to policy makers. The aim of the present study was to evaluate the usefulness to policy making of a GIS-based procedure for describing perceived landscape openness. To this end, a workshop was organized which was attended by eight Dutch policy makers who acted as representatives of their province (region). The Group Decision Room (GDR) technique was used to elicit the policy makers' evaluations of the procedure in an anonymous and reliable manner. The procedure was presented to the policy makers using cases from their own province, which they assessed using a mixture of qualitative and quantitative methods. The results show that policy makers rated the procedure as being highly relevant to policy making, scientifically credible, usable by policy makers and feasible to implement in the policy making process. They especially appreciated the flexibility and transparency of the procedure. The policy makers concluded that the procedure would be of most value for monitoring landscape changes and for analysing impacts on landscape openness in land use scenario studies. However, they requested guidelines for proper implementation of the various options in the procedure. In general, the current study shows that explicit and transparent evaluation of the usefulness of GIS-based tools can aid integration at the science-policy interface and help to ensure that both scientists and policy makers are informed of interrelated options and requirements. (C) 2011 Elsevier Ltd. All rights reserved.