Archive · dataset · 2015
Hotterdam Physical Heat Map
Listed in DataCite
Description
Method
The map identifies the social features that have been identified in previous research projects as possible causes of heat-related problems. Regression analysis was used to establish which of these are statistically significant: imperviousness, surface water, foliage (leaf area index), building envelopes and shade. A cluster analysis of these features was carried out.
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This analysis was used to identify and group the links between features. Results: The result is eight clusters (or typologies) 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.
Links
Where it is published
- Repository landing page data.4tu.nl/articles/_/12681611/1 ↗
landing page · from DataCite
- DOI doi.org/10.4121/uuid:1c6fd774-7e93-4991-bae0-713997b58e29 ↗
DOI / persistent id · from DataCite
Documentation and papers
- 4TU General Terms of Use doi.org/10.4121/resource:terms_of_use ↗
license · from DataCite
- doi.org /10.5379/urbani-izziv-en-2018-29-01-001 ↗
References 10.5379/urbani-izziv-en-2018-29-01-001
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.4121/uuid:1c6fd774-7e93-4991-bae0-713997b58e29 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.4121/uuid:1c6fd774-7e93-4991-bae0-713997b58e29 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Environmental engineering · Health sciences · Social and economic geography
- Inferred from text
- Image 65%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.4121/uuid:1c6fd774-7e93-4991-bae0-713997b58e29 | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].fos:environmental-engineering | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:health-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:social-and-economic-geography | source · DataCite | connector:datacite@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · DataCite | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · DataCite | connector:datacite@1.0.0 | /data/attributes/descriptions |
| license_text | source · DataCite | connector:datacite@1.0.0 | |
| publication_date | source · DataCite | connector:datacite@1.0.0 | /data/attributes/dates |
| spatial | source · DataCite | connector:datacite@1.0.0 | |
| title | source · DataCite | connector:datacite@1.0.0 | /data/attributes/titles/0/title |
| version_label | source · DataCite | connector:datacite@1.0.0 |