In: Stilla U, Gamba P, Juergens C, Maktav D (Eds) JURSE 2011 - Joint Urban Remote Sensing Event --- Munich, Germany, April 11-13, 2011
Application of remotely sensed data for spatial approximation of urban heat island in the city of Wrocáaw, Poland Mariusz Szymanowski and Maciej Kryza Institute of Geography and Regional Development University of Wrocáaw Wrocáaw, Poland Email:
[email protected] Szymanowski and Kryza [3] revealed that the most accurate results of the UHI spatialization are obtained with the multidimensional spatial interpolation techniques including multiple linear regression (MLR) and residual kriging (RK). Such methods require a set of spatially continuous auxiliary variables that determine UHI spatial structure. Up to recently, land-use and topographic maps were the main sources to prepare proper explanatory data. Nowadays, these inputs can be replaced by remotely sensed data [4, 5]. Several studies show that the remotely sensed data can be successfully used for spatial interpolation of UHI [6]. The main goal of this paper is to estimate usefulness of remotely sensed data and theirs derivatives for the assessment of the spatial pattern of air (screen level) temperature heat island.
Abstract—The study addresses the issue of potential usefulness of remotely sensed data and their derivatives for urban heat island (UHI) modeling. The methodology is illustrated with examples of selected UHI cases in Wrocáaw, a mid-sized city in SW Poland. Three cases of UHI (early summer, autumn and winter) are analyzed with equivalent remotely sensed data. Measurements of air temperature in each case were done by mobile meteorological stations, and available from 206 sites. Corresponding Landsat ETM+ and LIDAR-originated data were prepared and cover: albedo, selected vegetation indices (NDVI, SAVI, NDMI), emissivity, land surface temperature, roughness length, porosity, sky view factor and sums of daily solar irradiance. All these spatially continuous parameters were filtered using focal mean to simulate the role of source area around measurement site. Circular matrices, with radii varying from 25 to 1000 m, were applied in filtering procedure. Next, correlation analysis was used to determine the most influencing variables for each UHI case. The best correlations were achieved while considering the area of 550–600 m from a given measurement site. Regardless the seasons, the most influential factors for air temperature are: albedo, roughness length, sky view factor and sums of daily irradiance. Some parameters are significant only seasonally, e.g. vegetation indices in summer. Because spatial variables are in most cases multicollinear, step-wise regression supported with the analysis of variance inflation factor was used to determine final multiple linear models. Statistically significant models explain from 71% to 85% of the air temperature variance.
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STUDY AREA
The city of Wrocáaw (293 km2; population ~640 000) is located in SW Poland (51°N, 17°E) at ~120 m a.s.l. The altitude in the city area varies only from 105 to 148 m a.s.l., thus the temperature field is practically unaffected by elevation. Wrocáaw is situated along the Odra River. Approximately 31.4% of the city area is built-up, mainly with housing estates, industrial and warehouse buildings. The rest of the area consists of urban green space (36.6%), agricultural areas (28.9%) and water (3.1%). The annual mean UHI intensity in the centre of the city reaches 1.0 K. Thermal excess is weaker in large housing estates (0.7 K) or in residential areas (0.3 K). As in other cities, the magnitude of the nighttime UHI is 2–3 times higher than the average for daytime. The maximum difference between the city centre and surroundings can be as high as 9 K [3, 7]. The spatial structure of the Wrocáaw UHI can be described as amoebic [8] and multicellular [9], reflecting the land-use structure of the city.
INTRODUCTION
Urban heat island (UHI) is probably the most significant, though inadvertent, phenomena of urban climate [1]. It has strong impact on urban environment in many fields: socioeconomic and health (e.g. human comfort, mortality, air pollution chemistry and dispersion, water use) as well as meteorological ones (UHI circulation, atmospheric stability, humidity, clouds and fog, precipitation, evaporation, and snow cover) [2]. Urban heat island processes in individual cities are generally similar though some detailed characteristics are different. The most important features describing UHI are the magnitude and spatio-temporal structure. Such information is expected not only by town-planners and municipal services but is also an essential input for various modeling studies (e.g. air pollutants dispersion). The analysis conducted by
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METEOROLOGICAL DATA
Air temperature measurements for the selected cases of Wrocáaw UHI were gathered in the years 2001-2002 during three nights with relatively weak winds (
