Morabito Marco, Crisci Alfonso, Gioli Beniamino, Gualtieri Giovanni, Toscano Piero, Di Stefano Valentina, Orlandini Simone, Gensini Gian Franco
Institute of Biometeorology, National Research Council, Florence, Italy; Interdepartmental Centre of Bioclimatology, University of Florence, Florence, Italy.
Institute of Biometeorology, National Research Council, Florence, Italy.
PLoS One. 2015 May 18;10(5):e0127277. doi: 10.1371/journal.pone.0127277. eCollection 2015.
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.
Development of high-resolution, heat-related urban risk maps regarding the elderly population (≥ 65).
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).
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.
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.
高温对老年人的短期影响众所周知。尽管意大利是欧洲老年公民比例最高的国家，但缺乏与空间热相关的老年人风险信息。
绘制针对老年人口（≥65岁）的高分辨率、与热相关的城市风险地图。
对意大利11个主要城市夏季期间的长时间序列（2001 - 2013年）遥感MODIS数据进行降尺度处理，以获得高空间分辨率（100米）的白天和夜间陆地表面温度（LST）。通过应用两种统计模型方法逐像素估计LST：1）线性回归模型（LRM）；2）广义相加模型（GAM）。从2001年人口普查（欧盟统计局来源）的联合研究中心人口网格（100米）中提取总人口和老年人口密度数据，并使用“克里顿风险三角”危害 - 风险方法进行处理，以获得与热相关的老年人风险指数（HERI）。
与LRM方法相比，GAM程序在白天和夜间LST估计方面有所改进。为内陆和沿海城市绘制了白天和夜间HERI水平的高分辨率地图。具有危险HERI水平（非常高风险）的城市地区不一定具有最高温度。危险的HERI水平通常集中在内陆城市的市中心和沿海城市的内部区域。沿海城市中两个最危险的HERI水平比内陆城市更高。
本研究表明，在一个简单灵活的框架内结合地理空间技术和空间人口特征，以提供白天和夜间HERI的高分辨率城市地图具有巨大潜力。通过这种方式，可以立即确定潜在的干预区域，并提供街道级别的详细信息。这些信息可以支持公共卫生工作者，并促进与热相关紧急情况的协调。
