Abstract:The main factors influencing the spatiotemporal variability of urban climate are quite widely recognized, including, for example, the thermal properties of materials used for surfaces and buildings, the mass, height and layout of the buildings themselves and patterns of land use. However, the roles played by particular factors vary from city to city with respect to differences in geographical location, overall size, number of inhabitants and more. In urban climatology, the concept of "local climate zones" (LCZs) has emerged over the past decade to address this heterogeneity. In this contribution, a new GIS-based method is used for LCZ delimitation in Prague and Brno, the two largest cities in the Czech Republic, while land surface temperatures (LSTs) derived from LANDSAT and ASTER satellite data are employed for exploring the extent to which LCZ classes discriminate with respect to LSTs. It has been suggested that correctly-delineated LCZs should demonstrate the features typical of LST variability, and thus, typical surface temperatures should differ significantly among most LCZs. Zones representing heavy industry (LCZ 10), dense low-rise buildings (LCZ 3) and compact mid-rise buildings (LCZ 2) were identified as the warmest in both cities, while bodies of water (LCZ G) and densely-forested areas (LCZ A) made up the coolest zones. ANOVA and subsequent multiple comparison tests demonstrated that significant temperature differences between the various LCZs prevail. The results of testing were similar for both study areas (89.3% and 91.7% significant LST differences for Brno and Prague, respectively). LSTs computed from LANDSAT differentiated better between LCZs, compared with ASTER. LCZ 8 (large low-rise buildings), LCZ 10 (heavy industry) and LCZ D (low plants) are well-differentiated zones in terms of their surface temperatures. In contrast, LCZ 2 (compact mid-rise), LCZ 4 (open high-rise) and LCZ 9 (sparsely built-up) are less distinguishable in both areas analyzed. Factors such as seasonality and thermal anisotropy remain a challenge for future research into LST differences.
Stewart and Oke (2012)
Czech Republic). The method is based on measurable physical properties and a clearly defined decision-making algorithm. Our analysis shows that the decision-making algorithm for defining the percentage coverage for individual LCZs showed good agreement (in 79-89% of cases) with areas defined on the basis of expert knowledge. When the distribution of LCZs on the basis of our method and the method of Bechtel and Daneke (2012) was compared, the results were broadly similar; however, considerable differences occurred for LCZs 3, 5, 10, D, and E. It
The stations of the Metropolitan Station Network in Olomouc (Czech Republic) were assigned to local climatic zones, and the temperature characteristics of the stations were compared. The classification of local climatic zones represents an up-to-date concept for the unification of the characterization of the neighborhoods of climate research sites. This study is one of the first to provide a classification of existing stations within local climate zones. Using a combination of GIS-based analyses and field research, the values of geometric and surface cover properties were calculated, and the stations were subsequently classified into the local climate zones. It turned out that the classification of local climatic zones can be efficiently used for representative documentation of the neighborhood of the climate stations. To achieve a full standardization of the description of the neighborhood of a station, the classification procedures, including the methods used for the processing of spatial data and methods used for the indication of specific local characteristics, must be also standardized. Although the main patterns of temperature differences between the stations with a compact rise, those with an open rise and the stations with no rise or sparsely built areas were evident; the air temperature also showed considerable differences within particular zones. These differences were largely caused by various geometric layout of development and by unstandardized placement of the stations. For the direct comparison of temperatures between zones, particularly those stations which have been placed in such a way that they are as representative as possible for the zone in question should be used in further research.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.