title: Urban-hazard risk analysis: mapping of heat-related risks in the elderly in major Italian cities.
abstract: BACKGROUND
  Short-term impacts of high temperatures on the elderly are well known. Even though Italy has the highest proportion of elderly citizens in Europe, there is a lack of information on spatial heat-related elderly risks.
  
  
  OBJECTIVE
  Development of high-resolution, heat-related urban risk maps regarding the elderly population (≥ 65).
  
  
  METHODS
  A long time-series (2001-2013) of remote sensing MODIS data, averaged over the summer period for eleven major Italian cities, were downscaled to obtain high spatial resolution (100 m) daytime and night-time land surface temperatures (LST). LST was estimated pixel-wise by applying two statistical model approaches: 1) the Linear Regression Model (LRM); 2) the Generalized Additive Model (GAM). Total and elderly population density data were extracted from the Joint Research Centre population grid (100 m) from the 2001 census (Eurostat source), and processed together using "Crichton's Risk Triangle" hazard-risk methodology for obtaining a Heat-related Elderly Risk Index (HERI).
  
  
  RESULTS
  The GAM procedure allowed for improved daytime and night-time LST estimations compared to the LRM approach. High-resolution maps of daytime and night-time HERI levels were developed for inland and coastal cities. Urban areas with the hazardous HERI level (very high risk) were not necessarily characterized by the highest temperatures. The hazardous HERI level was generally localized to encompass the city-centre in inland cities and the inner area in coastal cities. The two most dangerous HERI levels were greater in the coastal rather than inland cities.
  
  
  CONCLUSIONS
  This study shows the great potential of combining geospatial technologies and spatial demographic characteristics within a simple and flexible framework in order to provide high-resolution urban mapping of daytime and night-time HERI. In this way, potential areas for intervention are immediately identified with up-to-street level details. This information could support public health operators and facilitate coordination for heat-related emergencies.
authors.affiliation: Institute of Biometeorology, National Research Council, Florence, Italy; Interdepartmental Centre of Bioclimatology, University of Florence, Florence, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Morabito
authors.affiliation: Institute of Biometeorology, National Research Council, Florence, Italy.
authors.forename: Alfonso
authors.initials: A
authors.lastname: Crisci
authors.affiliation: Institute of Biometeorology, National Research Council, Florence, Italy.
authors.forename: Beniamino
authors.initials: B
authors.lastname: Gioli
authors.affiliation: Institute of Biometeorology, National Research Council, Florence, Italy.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Gualtieri
authors.affiliation: Institute of Biometeorology, National Research Council, Florence, Italy.
authors.forename: Piero
authors.initials: P
authors.lastname: Toscano
authors.affiliation: Fondazione per il Clima e la Sostenibilità, Florence, Italy.
authors.forename: Valentina
authors.initials: V
authors.lastname: Di Stefano
authors.affiliation: Interdepartmental Centre of Bioclimatology, University of Florence, Florence, Italy; Fondazione per il Clima e la Sostenibilità, Florence, Italy; Department of Agrifood Production and Environmental Sciences, University of Florence, Florence, Italy.
authors.forename: Simone
authors.initials: S
authors.lastname: Orlandini
authors.affiliation: Interdepartmental Centre of Bioclimatology, University of Florence, Florence, Italy; Clinica Medica e Cardiologia, University of Florence, Florence, Italy.
authors.forename: Gian Franco
authors.initials: GF
authors.lastname: Gensini
mesh_terms: D000368:Aged; D002947:Cities; D006358:Hot Temperature; D006801:Humans; D007558:Italy; D016014:Linear Models; D008962:Models, Theoretical; D018570:Risk Assessment; D012621:Seasons