Land use patterns, temperature distribution, and potential heat stress risk - The case study Berlin, Germany
Land use patterns, temperature distribution, and potential heat stress risk - The case study Berlin, Germany
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DOI：
10.1016/j.compenvurbsys.2014.07.005
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发表时间：
2014-11-01
影响因子：
6.8
通讯作者：
Kleinschmit, Birgit
中科院分区：
文献类型：
--
作者：
Dugord, Pierre-Adrien;Lauf, Steffen;Kleinschmit, Birgit
在西方社会，气候变暖、城市化进程和人口变化（如人口老龄化）的综合影响增加了城市人口遭受热相关压力的风险。为了给城市范围和空间上明确的适应性规划提供科学依据，需要在小空间尺度上研究城市热分布和风险人口。本研究的目的是（a）调查地表温度（LST）分布与城市土地利用模式的潜在影响，并（B）确定潜在风险的地区对热应力的温度分布和人口脆弱性的基础上。我们使用LST地图，来自两个Landsat热卫星图像为晚上10点和上午10点在随后的两个夏天，并通过土地利用类型，景观指标，结构参数，通过统计和GIS分析研究土地利用模式。使用线性回归，我们得到的土壤密封的程度是最好的预测LST的变化。但在一定条件下，NDVI、距市中心距离和容积率（FAR）是较好的预测因子。水体在上午10点有有利的影响，在晚上10点有相反的影响，反之亦然，耕地。绿色区域的降温效应早晨比晚上更显著。在晚上10点，住宅用途是受热量影响最大的土地利用类型之一，根据其密度水平，强度不同。为了在建筑物尺度上识别风险区域，我们引入了一个矩阵，将联合收割机模拟的气温与人口年龄和密度结合起来。结果表明，在密集的住宅用途的中心内城地区的潜在风险较高，特别是对老年居民的数量高的地区，并为两个主要的住宅建筑类型。确定的特定热应激风险的组成部分为城市规划者提供了有用的信息，以减轻未来热浪造成的不利影响。(C)2014爱思唯尔有限公司版权所有。
In western societies, the combined effects of climate warming, proceeding urbanization, and demographic change (e.g. population aging) increase the risk of city populations to be subjected to heat-related stress. To provide a scientific fundament for city-wide and spatially explicit adaptation planning, urban heat distribution and the population at risk need to be studied at small spatial scale. This study pursued to (a) investigate the land surface temperature (LST) distribution with regard to underlying effects of urban land use patterns, and to (b) identify areas at potential risk towards heat stress based on temperatures distribution and demographic vulnerability. We used LST maps as derived from two Landsat thermal satellite images for 10 pm and 10 am at two subsequent summer days and examined land use patterns through land use types, landscape metrics, and structural parameters via statistical and GIS analysis. Using linear regressions we obtained the degree of soil sealing to be the best predictor of LST-variations. However, under certain conditions, NDVI, distance to city center and floor area ratio (FAR) were better predictors. Water bodies had beneficial effects at 10 am and inverse effects at 10 pm, vice versa for arable land. The cooling effects of green areas were more significant in the morning than in the evening. Residential uses were among the most heat affected land use types at 10 pm, with different intensities according to their density level. For the identification of risk areas at the building scale, we introduced a matrix to combine simulated air temperature with population age and density. Results showed higher potential risk in central inner-city areas of dense residential uses, in particular for areas with high amounts of elderly residents, and for two major residential building types. The identified building blocks of specific heat stress risk provide urban planners with useful information to mitigate adverse effects caused by future heat waves. (C) 2014 Elsevier Ltd. All rights reserved.