Geographically weighted regression of the urban heat island of a small city
Geographically weighted regression of the urban heat island of a small city
复制标题
DOI：
10.1016/j.apgeog.2014.07.001
复制
发表时间：
2014-09
影响因子：
4.9
通讯作者：
Danijel Ivajnšič;M. Kaligarič;Igor Žiberna
中科院分区：
文献类型：
--
作者：
Danijel Ivajnšič;M. Kaligarič;Igor Žiberna
尽管区域气候存在差异，但世界各地的城市都形成了一个共同的特征——城市热岛（UHI）。其大小与城市规模有关，特别是在无云的区域条件下，尽管个别城市可能受到诸如靠近大型水体或盛行风等当地因素的影响。本文研究了Ljutomer小城市的热岛热岛格局，以评估其强度和形态，并检验地理加权回归（GWR）方法在模拟该小城市平均气温与相关影响因素回归关系中的实用性。测量了城市和农村地区平均气温的显著差异。结果表明，柳托默的建成区在冬季比农村地区平均温度高1°C。回归分析证实了局部非平稳解释变量（到城市地区的距离、地形位置指数和土地覆盖多样性）和全球平稳变量（每地区建筑体积和北纬）在解释平均气温的空间变化方面的重要作用。利用半参数GWR方法，平均气温与这五个解释变量之间的关系产生了91%的总体模型拟合，该方法在迄今为止发表的最小规模上进行了测试。
Despite differences in regional climates, cities world-wide have developed one common characteristic - the urban heat island (UHI). Its magnitude is related to city size, especially under cloudless sky conditions on a regional basis, although individual cities may be impacted by such local factors as proximity to large water bodies or prevailing winds. The UHI pattern in the small city of Ljutomer was examined in order to assess its intensity and morphology and to test the utility of the geographically weighted regression (GWR) method in modeling the regression relationships between mean air temperature and related influence factors in this small-scale urban example. Significant differences in mean air temperature between urban and rural areas were measured. It turned out that built-up areas in Ljutomer are on average 1 °C warmer than the rural surroundings in winter time. The regression analyses confirmed the important role of local non-stationary explanatory variables - distance to urban area, topographic position index and land-cover diversity - and global stationary variables - building volume per area and northness - in explaining spatial variation in mean air temperature. The relationships between mean air temperature and these five explanatory variables produced an overall model fit of 91%, utilizing the semiparametric GWR method, which was tested on the smallest scale so far published.