Modelling the impact of green solutions upon the urban heat island phenomenon by means of satellite data

被引:5
|
作者
Colaninno, Nicola [1 ]
Morello, Eugenio [1 ]
机构
[1] Politecn Milan, Dept Architecture & Urban Studies DAStU, Lab Simulaz Urbana Fausto Curti, Via Bonardi 3, I-20133 Milan, Italy
来源
CLIMATE RESILIENT CITIES - ENERGY EFFICIENCY & RENEWABLES IN THE DIGITAL ERA (CISBAT 2019) | 2019年 / 1343卷
关键词
GEOGRAPHICALLY WEIGHTED REGRESSION; SURFACE AIR-TEMPERATURE; LANDSAT TM; MODIS DATA;
D O I
10.1088/1742-6596/1343/1/012010
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Climate change causes a critical increase of temperature and frequency of heat waves, whose impact is particularly sensitive within the urban environment. Here, the loss of natural areas, beside morphological and thermal properties, makes urban temperature to be significantly higher compared to peri-urban and rural areas. This phenomenon is commonly known as urban heat island (UHI). Because green infrastructure provides an effective strategy for reducing the UHI effect, we explore the feasibility of remotely sensed data and statistical modelling for assessing the effectiveness of green measures. We simulated how implementing green roofs over the city of Milan could affect temperature. Geographically weighted regression has been used to model the correlation among satellite-derived vegetation map and near-surface air temperature.
引用
收藏
页数:6
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