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Hotterdam Vulnerability Cluster

dataset
posted on 11.12.2015 by Alexander Wandl, F. (Frank) van der Hoeven
Method: The atlas identifies the social features that have been designated in previous research projects as possible causes of heat-related problems. Hierarchical multiple regression analyses were used to establish which of these are statistically significant in the case of Rotterdam: the number of those aged 75 and over per hectare, the average age of the buildings, the sum of sensible heat and ground heat flux. A cluster analysis was used to identify the links between these features. Results: This results in six clusters (or typologies) that are shown here on the map with different colours, together with a table explaining the underlying values. Parent item: Hotterdam: Urban heat in Rotterdam and health effects Heat waves will occur in Rotterdam with greater frequency in the future. Those affected most will be the elderly – a group that is growing in size. In the light of the Paris heat wave of August 2003 and the one in Rotterdam in July 2006, mortality rates among the elderly in particular are likely to rise in the summer. The aim of the Hotterdam research project was to gain a better understanding of urban heat. Heat was measured and the surface energy balance modelled from that perspective. Social and physical features of the city were identified in detail with the help of satellite images, GIS and 3D models. The links between urban heat/surface energy balance and the social/physical features of Rotterdam were determined on the basis of multivariable regression analysis. The decisive features of the heat problem were then clustered and illustrated on a social and a physical heat map. The research project produced two heat maps, an atlas of underlying data.

History

Contributors

TU Delft, Faculty of Architecture and the Built Environment, Department of Urbanism

Publisher

TU Delft

Time coverage

2014

Geolocation

Rotterdam - in-habitat areas: Rotterdam excluding the harbour

Geolocation Longitude

4.4681

Geolocation Latitude

51.9156

Format

The data is in ESRI shape format. The values of every variable are available on 1 ha grid, which is the same as the CBS vierkanten 100m and can therefore be brought into relation to CBS data. media types: application/octet-stream, application/vnd.google-earth.kml+xml, application/zip, text/plain

Exports