Thermal data analysis for urban climate research: A case study of Olomouc, Czechia

Abstract

Due to the recent advancements in thermal camera technology, it is easier than ever to acquire information about surface temperature in very-high or extreme spatial resolution from manned or unmanned airborne vehicles. The main objective of the paper is to investigate the possibilities of extreme resolution thermal data for urban climate research. The main dataset used for the work is thermal mosaic acquired by an aeroplane above the city of Olomouc in the morning and afternoon on 10 th July 2016. The spatial resolution of the dataset fluctuates between 90 and 100 cm per pixel edge. Auxiliary data used for the analysis included open data from European programmes Urban Atlas and CORINE Land Cover. For further analysis, building height information, material type and Local Climate Zones classification were used. The results show a possible comparison in various neighbourhoods and material types while maintaining reference units-Urban Atlas/CORINE Land Cover classes or Local Climate Zones. Verticality analysis shows a significant difference between ground and rooftop levels that need to be taken into account when investigating heat for quality of life. All the analyses confirmed knowledge about the difference between natural and artificial surfaces that most artificial surfaces tend to heat up much more during daytime and fail to cool down completely during the night-time. Moreover, this research lays the foundation to future urban climate research based on extreme resolution thermal images over multiple areas or during long-lasting campaigns.

Mapping Local Climate Zones and Their Applications in European Urban Environments: A Systematic Literature Review and Future Development Trends

“…Explicit consideration of the geometric and surface properties, as defined in the definitive LCZ study [33], served to classify the LCZs as fixed measure-ment sites [75], while mobile measurement traverses formed the basis of urban climate research in Cluj-Napoca (Romania) [75] and Uppsala (Sweden) [50]. Pour et al [76] and Pour and Voženílek [77] personally delineated and visualized the most common LCZs in Olomouc (Czech Republic) by combining local expert knowledge and Urban Atlas classification with airborne thermal remote-sensing datasets to assess the thermal regime of a range of urban patterns. An alternative approach, addressing urban thermal and wind modelling, was taken in the definition of ten built-up LCZs in Basel (Switzerland) by Theeuwes et al [78] and Droste et al [79].…”

“…Gholami and Beck [124] determined the relationship between LST and LCZ for 25 cities worldwide, but with only a few examples for European cities. Pour et al [76] and Pour and Voženílek [77] took airborne thermal images (using a thermal camera installed in a light aeroplane) for the city of Olomouc (Czech Republic), and determined that the highest surface temperatures occurred in LCZs 2, 4, 5, and 8. In similar fashion, Skarbit et al [84] analysed LST differences between the LCZs of Szeged on the basis of airborne thermal measurements during the early night hours, and the general results indicated that LCZ 6 has the lowest early nighttime LST compared with other densely built-up LCZs such as LCZs 2, 3, and 5.…”

Determining the influence of population density on the land surface temperature based on remote sensing data and GIS techniques: application to Prizren, Kosovo

“…In cases when in the study area there are different restrictions on measuring the UHI phenomenon, such as the lack of equipment/instruments for measuring temperature and their inhomogeneous distribution (as in our case of the study area), then it is necessary to use GIS and remote sensing techniques (Berila & Dushi, 2021). Using them to measure the UHI phenomenon represents SUHI, which is determined using geospatial technology through the calculation of the land surface temperature (Voogt & Oke, 2003;Despini et al, 2016;Pour & Voženílek, 2020).…”

Mapping summer SUHI and its impact on the environment using GIS and Remote Sensing techniques: A case study on Municipality of Prishtina (Kosovo)

“…This is evident in cases where the study area has insufficient data on the measured temperaturethe distribution of measuring equipment is inhomogeneous and rare. Thus, the use of geospatial technology emerges as a suitable tool to determine such a phenomenon through the calculation of LST (Land Surface Temperature) (Pour & Voženílek, 2020;Despini et al, 2016;Voogt & Oke, 2003). Atmospheric UHI is called as such by merging BLHI and CLHI.…”