Abstract-The aim of this study was to identify typical and specific features of land surface temperature (LST) distribution in the city of Krakow and its surroundings with the use of Landsat/ ETM? data. The paper contains a detailed description of the study area and technical properties of the Landsat program and data, as well as a complete methodology of LST retrieval. Retrieved LST records have been standardized in order to ensure comparability between satellite images acquired during different seasons. The method also enables identification of characteristic thermal regions, i.e. areas always colder and always warmer than a zonal mean LST value for Krakow. The research includes spatial analysis of the standardized LST with regard to different land cover types. Basic zonal statistics such as mean standardized LST and percentage share of hot and cold regions within 10 land cover types were calculated. GIS was used for automated data processing and mapping. The results confirmed the most obvious dependence of the LST on different land cover types. Some more factors influencing the LST were recognized on the basis of detailed investigation of the LST pattern in the urban agglomeration of Krakow. The factors are: emission of anthropogenic heat, insolation of the surfaces depending first of all on land relief and shape of buildings, seasonal changes of vegetation and weather conditions at the time of satellite image acquisition.
In cities located in concave landforms, urban heat island (UHI) is an element of a complicated thermal structure and occurs due to the common impact of urban built-up areas and orography-induced processes like katabatic flows or air temperature inversions. Kraków, Poland (760,000 inhabitants) is located in a large valley of the river Vistula. In the years 2009-2013, air temperature was measured with the 5-min sampling resolution at 21 urban and rural points, located in various landforms. Cluster analysis was used to process data for the night-time. Sodar and synoptic data analysis provided results included in the definition of the four types of nighttime thermal structure representing the highest and the lowest spatial air temperature variability and two transitional types. In all the types, there are three permanent elements which show the formation of the inversion layer, the cold air reservoir and the UHI peak zone. As the impact of land use and relief on air temperature cannot be separated, a concept of relief-modified UHI (RMUHI) was proposed as an alternative to the traditional UHI approach. It consists of two steps: (1) recognition of the areal thermal structure taking into consideration the city centre as a reference point and (2) calculation of RMUHI intensity separately for each vertical zone.
Diurnal variability of spatial pattern of air temperature was studied in five cities in Central Europe: Bratislava (Slovakia), Brno (Czech Republic), Kraków (Poland), Szeged (Hungary) and Vienna (Austria), during one of the heat waves in 2015 (4-14 August), with the application of micro-climate model MUK-LIMO_3. 8th August was chosen to study in detail the urban heat load at 10.0 0, 16.0 0, 22.0 0 and 4.00 CEST. Local Climate Zones concept was used to supply data for the model and for the interpretation of the results obtained. Model outcomes were validated with measurement data from 86 points belonging to the networks which operate in the cities studied. The results obtained show that among urban LCZ, the highest heat load was observed for LCZ 2 and 3 from 16.00 to 4.00, while at 10.00 there is no such clear pattern. Unlike forested areas, open green areas can contribute to the generation of high air temperature: > 35 °C during day time and > 30 °C during night time. Important factors controlling the intra-zonal and inter-zonal variability of air temperature in particular LCZs are the local environmental conditions. During the day time, diversified relief in the area of the city and its vicinities generates higher heat load in the valleys' floors than in areas located above, both in rural and urban areas. The same landforms experience lower heat load during the night time due to air temperature inversions effect.
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