Author:
Buscail Camille,Upegui Erika,Viel Jean-François
Abstract
Abstract
Background
Climate change poses unprecedented challenges, ranging from global and local policy challenges to personal and social action. Heat-related deaths are largely preventable, but interventions for the most vulnerable populations need improvement. Therefore, the prior identification of high risk areas at the community level is required to better inform planning and prevention. We aimed to demonstrate a simple and flexible conceptual framework relying upon satellite thermal data and other digital data with the goal of easily reproducing this framework in a variety of urban configurations.
Results
The study area encompasses Rennes, a medium-sized French city. A Landsat ETM + image (60 m resolution) acquired during a localized heatwave (June 2001) was used to estimate land surface temperature (LST) and derive a hazard index. A land-use regression model was performed to predict the LST. Vulnerability was assessed through census data describing four dimensions (socio-economic status, extreme age, population density and building obsolescence). Then, hazard and vulnerability indices were combined to deliver a heatwave health risk index. The LST patterns were quite heterogeneous, reflecting the land cover mosaic inside the city boundary, with hotspots of elevated temperature mainly observed in the city center. A spatial error regression model was highly predictive of the spatial variation in the LST (R
2
= 0.87) and was parsimonious. Three land cover descriptors (NDVI, vegetation and water fractions) were negatively linked with the LST. A sensitivity analysis (based on an image acquired on July 2000) yielded similar results. Southern areas exhibited the most vulnerability, although some pockets of higher vulnerability were observed northeast and west of the city. The heatwave health risk map showed evidence of infra-city spatial clustering, with the highest risks observed in a north–south central band. Another sensitivity analysis gave a very high correlation between 2000 and 2001 risk indices (r = 0.98, p < 10-12).
Conclusions
Building on previous work, we developed a reproducible method that can provide guidance for local planners in developing more efficient climate impact adaptations. We recommend, however, using the health risk index together with hazard and vulnerability indices to implement tailored programs because exposure to heat and vulnerability do not require the same prevention strategies.
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health,General Business, Management and Accounting,General Computer Science
Reference64 articles.
1. Frich P, Alexander L, Della-Marta P, Gleason B, Haylock M, Klein Tank A, Peterson T: Observed coherent changes in climatic extremes during the second half of the twentieth century. Clim Res. 2002, 19: 193-212.
2. IPCC: Summary for policymakers. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Edited by: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL. 2007, New York: Cambridge University Press
3. Tebaldi C, Hayhoe K, Arblaster JM, Meehl GA: Going to the extremes. Clim Chang. 2006, 79: 185-211. 10.1007/s10584-006-9051-4.
4. Meehl GA, Tebaldi C: More intense, more frequent, and longer lasting heat waves in the 21st century. Science. 2004, 305: 994-997. 10.1126/science.1098704.
5. Arnfield AJ: Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. Int J Climatol. 2003, 23: 1-26. 10.1002/joc.859.
Cited by
124 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献