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Urban Heat Island Modelling Based on MUKLIMO

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Urban Heat Island Modelling Based on MUKLIMO AGILE: GIScience Series, 2, 5, 2021. https://doi.org/10.5194/agile-giss-2-5-2021 Proceedings of the 24th AGILE Conference on Geographic Information Science, 2021. Editors: Panagiotis Partsinevelos, Phaedon Kyriakidis, and Marinos Kavouras. This contribution underwent peer review based on a full paper submission. © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Urban heat island modelling based on MUKLIMO: examples from Slovakia Monika Kopeckáa (corresponding author), Daniel Szatmária, Juraj Holecb and Ján Feraneca [email protected], daniel.szatmari@ savba.sk, [email protected], [email protected] aInstitute of Geography, Slovak Academy of Sciences, Bratislava, Slovakia bSlovak Hydrometeorological Institute, Bratislava, Slovakia which temperature tends to be higher in urban Abstract. Cities are generally expected to experience landscape than surrounding non-urban areas has been higher temperatures than surrounding rural areas due to observed worldwide. Over the last few decades, the Urban Heat Island (UHI) effect. The aim of this advancements in remote sensing increased the number paper is to document identification and delimitation of of UHI studies that can be classified into two broad land cover/land use (LC/LU) classes based on Urban categories: ”air” (or “atmospheric”) and “surface” Atlas data in three cities in Slovakia: the capital UHIs (Zhou et al., 2019). Air UHI refers to UHI effects Bratislava and two regional centres, Trnava and Žilina, in the canopy (CLHI) or boundary (BLHI) layer (Oke, in the years 1998-2016 and their effect on the 1995). The CLHI is usually measured by in situ sensors temperature change. The concept of Local Climate on the fixed meteorological stations or traverses of Zones (replaced by LC/LU classes in this study) was vehicles while more special platforms (aircrafts, used as an input for the UHI modelling by application radiosondes, etc.) are needed to measure the BLHI. On of the Mikroskaliges Urbanes KLIma MOdell the other hand, surface UHI (SUHI) represents the (MUKLIMO). The model MUKLIMO was validated radiative temperature difference between urban and by data taken in five stations in Bratislava, two in non-urban surfaces measured by satellite thermal Trnava, and one in Žilina, while a good rate of remote sensing data. SUHI usually develops during agreement between the modelled and measured data hot, sunny summer days. The sun heats dry, exposed was statistically proved. A single representative day urban surfaces, like roofs, roads, and pavements, to (August 22, 2018) was chosen for which UHI was temperatures 25 to 50 °C higher than the temperature modelled with three inputs of LC/LU classes: situation of the ambient air mass (Hofierka et al., 2020). in 1998, 2007, and 2016 to assess the effect of change of LC/LU classes on the distribution of temperatures. UHI mitigation requires understanding of factors The spatial manifestation of UHI was assessed in the affecting the interaction between solar radiation and frame of LC/LU classes for 2016 at 21:00 of Central urban land cover classes (Majkowska et al., 2017). It is European Summer Time (CEST). The results indicate obvious from many studies that the LC/LU classes and that UHI intensity trends are spatially correlated with their changes influence the frequency and intensity of LC/LU classes and their change pattern. Results of the UHI. Oke (2004) proposed a simple classification Bratislava show, regarding the size of the city and of what are referred to as urban climate zones (UCZs), relief dissection, greater variability than smaller Trnava which roughly correspond to LC/LU classes. situated in flat terrain and Žilina situated in the river The aim of the paper is to use LC/LU classes based on valley surrounded by the mountain ranges. Urban Atlas (UA) data in three cities in Slovakia: the Keywords: urban heat island (UHI), MUKLIMO, capital Bratislava and two regional centres, Trnava and Urban Atlas, Slovakia Žilina (located in different geographical conditions), in the years 1998-2016 and document the impact of their changes on the air temperature difference by 1 Introduction application of MUKLIMO_3. This model has been used for the studies of UHI in various cities, e.g. Climate change is expected to increase the frequency Vienna (Žuvela-Aloise et al., 2014), Brno (Geletič and duration of excessive heat events, especially in et al., 2018), Bratislava and Trnava (Holec and cities. The urban heat island (UHI) – a phenomenon in Šťastný, 2017; Holec et al., 2020), Szeged (Gál and 1 of 11 Skarbit, 2017) or comparison of five central European meter resolution was used as a source of elevation data cities (Bokwa et al., 2015; Bokwa et al., 2019). (Jarvis et al., 2008). This model is freely available after registration via USGS Earth Explorer (https://earthexplorer.usgs.gov/). The model was 2 Methodology subsequently recalculated into 100-meter resolution. The increasing availability of high-resolution Table 1: Input data to the MUKLIMO model. geospatial data allows the development of multiple Input data Data specification modelling approaches in urban areas. MUKLIMO_3 Digital Elevation SRTM DEM was applied in this study for UHI modelling. This Model Urban Atlas data 2012, SPOT three-dimensional model was developed for the micro- Land Use/Land Cover 4/1998, SPOT 5/2007, Sentinel- data scale applications aimed at the issues of urban climate, 2/2016 primarily the UHI mapping (Sievers and Zdunkowski, HRL Imperviousness HRL Imperviousness 2012 1985). The algorithm of the model includes prognostic equations for air temperature and humidity, Data from the period August 15 Meteorological data – 24, 2018 (Bratislava, Jaslovské parametrisation of undetermined buildings, short and Bohunice and Dolný Hričov) long-wave radiation, soil temperature and moisture Urban Greenery data SPOT balance, as well as the vegetation model. It also uses Building layer ZBGIS database the categorisation of proportions of surfaces of varied The Urban Atlas (UA) provides pan-European reliable, kinds by an established scale: built-up, impermeable inter-comparable, high-resolution LC/LU data for 305 and permeable surface parts like vegetation cover, and Functional Urban Areas (FUA) with more than soil (Sievers et al., 1983). The model allows working 100,000 inhabitants for the 2006 reference year and with up to 99 user-defined LC/LU classes and grid 785 FUA with more than 50,000 inhabitants for the resolution in tens to hundreds of meters. A horizontal 2012 reference year in EEA39 countries. They are resolution of 100 m was selected for this study. This mainly based on the combination of (statistical) image resolution is higher than other urban climate models, classification and computer assisted photointerpretation e.g. the WRF model works with resolution in (CAPI; Feranec et al., 2016) of Very High Resolution kilometres for UHI studies (Giannaros et al., 2013). satellite imagery (e.g. multispectral SPOT 5 & 6 and Formosat-2 pan-sharpened imagery with a 2 to 2.5 m 2.1 Software and Data Availability spatial resolution). The nomenclature includes 17 urban classes with a minimum mapping unit (MMU) of 0.25 MUKLIMO_3 is a product of the German Weather ha and 10 rural classes with MMU 1 ha (Meirich, 2008; Service (DWD) available upon request for non- Urban Atlas, 2012). These data are available after commercial research and teaching purposes. The model registration on https://land.copernicus.eu/local/urban- predicts air temperature, relative humidity, wind speed atlas. Boundaries of UA 2012 classes were modified and direction, and soil and surface temperatures. Model using backdating according to the SPOT-4/1998, outputs can be converted into NetCDF format and SPOT-5/2007, Sentinel-2/2016 satellite images by postprocessed in GIS software. In this study, QGIS CAPI. They were further specified by building heights 3.6.3-Noosa was used for model outputs and parking areas using ZBGIS data (ZBGIS is a postprocessing. Python console within QGIS spatial object-oriented database that is a reference basis environment was used for raster calculator operations of the National Spatial Data Infrastructure created and running iteratively for three cities and more extracted maintained by the Geodesy Cartography and Cadastre hours. Model MUKLIMO_3 can be used to simulate Authority of the Slovak Republic), and data about the impact of planned changes on the local or regional the urban greenery (woody vegetation, grass vegetation climate, namely, the effects of different climate change or mixed vegetation (trees and grass) prevails outside adaptation measures, including the implementation of the sealed areas) obtained by supervised classification green infrastructure or unsealing of sealed surfaces of the quoted satellite images. Copernicus (e.g. Žuvela-Aloise et al., 2016). Imperviousness high resolution layer was used to Several model inputs are necessary: layers of digital specify soil sealing degree of LC/LU data. In this way, elevation model, LC/LU data, and meteorological 53 classes of prevailingly urban landscape (according inputs (Tab. 1). SRTM DEM (Shuttle Radar to the intensity of impermeable surfaces), farming Topography Mission Digital Elevation Model) with 90- landscape, semi-natural landscape, forest landscape, AGILE: GIScience Series, 2, 5, 2021 | https://doi.org/10.5194/agile-giss-2-5-2021 2 of 11 waterlogged areas, and waters were derived (Tab. 2; 1.1.2.4.2* Building height 5.1–10 m Szatmári et al., 2018). Areas of these classes identified 1.1.2.4.3* Building height 10.1–15 m for the years 1998, 2007, and 2016 were the input data 1.1.2.4.4* Building height 15.1–20 m for the MUKLIMO model. Due to the technical 1.1.2.4.5* Building height > 20 m 1.1.2.4.6* Mixed building heights requirements of the model, a regular cut-out from FUA 1.1.3.0.0* Isolated structures was used. 1.2 Industrial, commercial, and transportation units August 22, 2018, was chosen for modelling with the 1.2.1 Industrial, commercial, public, military, private areas MUKLIMO model.
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