Geoinformatics and Remote Sensing (GIdAj)
An Integrated Approach to Addressing Urban Overheating: Combining Earth Observation, Microclimate Modelling, and Social Data
EN
The aim of this doctoral dissertation is to develop an integrated framework for analysing and addressing urban overheating by systematically combining Earth observation data, microclimate modelling, and social data. Particular emphasis is placed on the advanced use of remote sensing to capture the spatial and temporal variability of urban surface and atmospheric properties that contribute to heat stress. Multi-source Earth observation data, including thermal infrared satellite imagery (e.g., Landsat, Sentinel-3), multispectral and hyperspectral data (e.g., Sentinel-2), and airborne or UAV-based observations, will be used to derive land surface temperature, vegetation indices, surface albedo, impervious surface fraction, and urban morphological parameters. Time-series analyses will enable the assessment of long-term trends, seasonal variability, and responses to extreme heat events. Data fusion techniques and spatial downscaling will be applied to improve the spatial and temporal resolution of thermal indicators relevant for urban-scale analyses. Earth observation–derived variables will serve both as inputs and validation datasets for microclimate models (e.g., ENVI-met), which will simulate air temperature, radiation fluxes, and biometeorological heat stress indices such as PET and UTCI at the scale of streets and urban blocks. The integration of remote sensing products with detailed urban geometry will allow for scenario-based simulations assessing the impacts of land cover changes, green and blue infrastructure interventions, and urban design modifications on thermal conditions. The modelling outputs will be combined with demographic and socio-economic data to identify spatial patterns of heat exposure, vulnerability, and risk among different population groups. This integrated approach will support the identification of priority areas for intervention and the evaluation of socially equitable adaptation strategies. The results will contribute to the development of a transferable methodological framework for urban heat assessment, strengthening the role of Earth observation in evidence-based urban climate adaptation and planning.
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prof. Mgr. Jaroslav Hofierka, PhD.
Mgr. Katarína Onačillová, PhD.
Geoinformatics and Remote Sensing (GId)
Effectiveness of Different Types of Green and Blue Infrastructure in Reducing Heat Stress
SK
The aim of this doctoral dissertation is to comprehensively evaluate the effectiveness of different types of green and blue infrastructure in reducing heat stress in urban environments, expressed using biometeorological indices such as the Physiological Equivalent Temperature (PET) and the Universal Thermal Climate Index (UTCI). The research focuses on analyzing and comparing the impacts of various forms of green infrastructure (e.g., urban parks, street trees, green roofs and façades) and blue infrastructure (e.g., water bodies, water features, retention measures) under different urban and climatic conditions. Methodologically, the dissertation will be based on a combination of micro-scale climate modelling (e.g., ENVI-met), spatial analyses within geographic information systems, and the use of Earth observation data. Selected typical and extreme meteorological situations, particularly during summer heatwaves, will be simulated in order to quantify the influence of individual green and blue infrastructure elements on air temperature, radiation conditions, and resulting human thermal stress. The study will compare the effectiveness of individual measures and their combinations, identify optimal solutions for different types of urban spaces (streets, courtyards, public spaces), and assess their potential for climate change adaptation. The results will contribute to a better understanding of interactions between urban structure, vegetation, water elements, and human thermal comfort, providing a scientific basis for urban planning and climate adaptation strategies.
prof. Mgr. Jaroslav Hofierka, PhD.
Geoinformatics and Remote Sensing (GIdAj)
Effectiveness of Different Types of Green and Blue Infrastructure in Reducing Heat Stress
EN
The aim of this doctoral dissertation is to comprehensively evaluate the effectiveness of different types of green and blue infrastructure in reducing heat stress in urban environments, expressed using biometeorological indices such as the Physiological Equivalent Temperature (PET) and the Universal Thermal Climate Index (UTCI). The research focuses on analyzing and comparing the impacts of various forms of green infrastructure (e.g., urban parks, street trees, green roofs and façades) and blue infrastructure (e.g., water bodies, water features, retention measures) under different urban and climatic conditions. Methodologically, the dissertation will be based on a combination of micro-scale climate modelling (e.g., ENVI-met), spatial analyses within geographic information systems, and the use of Earth observation data. Selected typical and extreme meteorological situations, particularly during summer heatwaves, will be simulated in order to quantify the influence of individual green and blue infrastructure elements on air temperature, radiation conditions, and resulting human thermal stress. The study will compare the effectiveness of individual measures and their combinations, identify optimal solutions for different types of urban spaces (streets, courtyards, public spaces), and assess their potential for climate change adaptation. The results will contribute to a better understanding of interactions between urban structure, vegetation, water elements, and human thermal comfort, providing a scientific basis for urban planning and climate adaptation strategies.
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prof. Mgr. Jaroslav Hofierka, PhD.
Geoinformatics and Remote Sensing (GId)
An Integrated Approach to Addressing Urban Overheating: Combining Earth Observation, Microclimate Modelling, and Social Data
SK
The aim of this doctoral dissertation is to develop an integrated framework for analysing and addressing urban overheating by systematically combining Earth observation data, microclimate modelling, and social data. Particular emphasis is placed on the advanced use of remote sensing to capture the spatial and temporal variability of urban surface and atmospheric properties that contribute to heat stress. Multi-source Earth observation data, including thermal infrared satellite imagery (e.g., Landsat, Sentinel-3), multispectral and hyperspectral data (e.g., Sentinel-2), and airborne or UAV-based observations, will be used to derive land surface temperature, vegetation indices, surface albedo, impervious surface fraction, and urban morphological parameters. Time-series analyses will enable the assessment of long-term trends, seasonal variability, and responses to extreme heat events. Data fusion techniques and spatial downscaling will be applied to improve the spatial and temporal resolution of thermal indicators relevant for urban-scale analyses. Earth observation–derived variables will serve both as inputs and validation datasets for microclimate models (e.g., ENVI-met), which will simulate air temperature, radiation fluxes, and biometeorological heat stress indices such as PET and UTCI at the scale of streets and urban blocks. The integration of remote sensing products with detailed urban geometry will allow for scenario-based simulations assessing the impacts of land cover changes, green and blue infrastructure interventions, and urban design modifications on thermal conditions. The modelling outputs will be combined with demographic and socio-economic data to identify spatial patterns of heat exposure, vulnerability, and risk among different population groups. This integrated approach will support the identification of priority areas for intervention and the evaluation of socially equitable adaptation strategies. The results will contribute to the development of a transferable methodological framework for urban heat assessment, strengthening the role of Earth observation in evidence-based urban climate adaptation and planning.
prof. Mgr. Jaroslav Hofierka, PhD.
Mgr. Katarína Onačillová, PhD.
Geoinformatics and Remote Sensing (GId)
Multiscale assessment of divergent and convergent trends in the spatial social-economic stratification of population
SK
doc. Mgr. Ladislav Novotný, PhD.
prof. Mgr. Jaroslav Hofierka, PhD.
Geoinformatics and Remote Sensing (GIdAj)
Multiscale assessment of divergent and convergent trends in the spatial social-economic stratification of population
EN
The aim of the dissertation is to examine the development trends in the spatial social-economic stratification of population at various spatial levels – from global to intra-urban using various geospatial data and tools. In the thesis, it will be necessary to identify appropriate indicators for different spatial scales and evaluate the appropriateness, availability and reliability of particular data. The data will be applied to the required spatial units using areal transformation methods and similar data used at the international level for comparison of urban areas such as the data from European Land Monitoring Services (Urban Atlas). Subsequently, the analysis and modelling of the spatial arrangement of social-economic stratification will be carried out with an emphasis on the chronological aspect and identification of factors leading to this stratification. Advanced statistical methods and tools of geographic information systems will be used. The thesis will also identify regularities of the spatial arrangement at various scales and with an emphasis on their evaluation in causal contexts.
To examine the development trends in the spatial social-economic stratification of population at various spatial levels – from global to intra-urban using various geospatial data and tools.
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doc. Mgr. Ladislav Novotný, PhD.
prof. Mgr. Jaroslav Hofierka, PhD.
Geoinformatics and Remote Sensing (GIdAj)
Multisensor fusion of UAV and satellite data for vegetation mapping in heterogeneous agricultural landscapes
EN
The aim of the dissertation is to develop a methodology for linking hyperspectral and 3D UAV data with multispectral and hyperspectral satellite imagery in order to improve vegetation and land cover mapping in heterogeneous agricultural landscapes. The research will be based on the use of UAV hyperspectral imagery in the 400–1000 nm range and laser scanning data as a reference source of information on vegetation structure and condition at very high spatial resolution. The detailed UAV data will be aggregated to the level of satellite pixels and used as training and validation data for the interpretation of Sentinel-2 imagery and selected hyperspectral satellite missions. The study will focus on vegetation types characterized by pronounced spatial heterogeneity, such as agricultural crops, vineyards, permanent grasslands, and wetland transition zones. The outcome will be a methodology for integrating UAV hyperspectral and 3D data with satellite imagery to improve the classification of vegetation and land cover, complemented by the estimation of selected structural vegetation indicators at the satellite pixel level for selected land cover types.
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doc. Mgr. Michal Gallay, PhD.
Geoinformatics and Remote Sensing (GId)
Multisensor fusion of UAV and satellite data for vegetation mapping in heterogeneous agricultural landscapes
SK
The aim of the dissertation is to develop a methodology for linking hyperspectral and 3D UAV data with multispectral and hyperspectral satellite imagery in order to improve vegetation and land cover mapping in heterogeneous agricultural landscapes. The research will be based on the use of UAV hyperspectral imagery in the 400–1000 nm range and laser scanning data as a reference source of information on vegetation structure and condition at very high spatial resolution. The detailed UAV data will be aggregated to the level of satellite pixels and used as training and validation data for the interpretation of Sentinel-2 imagery and selected hyperspectral satellite missions. The study will focus on vegetation types characterized by pronounced spatial heterogeneity, such as agricultural crops, vineyards, permanent grasslands, and wetland transition zones. The outcome will be a methodology for integrating UAV hyperspectral and 3D data with satellite imagery to improve the classification of vegetation and land cover, complemented by the estimation of selected structural vegetation indicators at the satellite pixel level for selected land cover types.
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doc. Mgr. Michal Gallay, PhD.
Geoinformatics and Remote Sensing (GId)
The Urban Spatial Differentiation of Heat Stress in Cities and Its Relationship with Socio-Economic Factors
SK
The aim of this doctoral dissertation is to analyse the spatial differentiation of heat stress within a city and to investigate its relationship with selected socio-economic characteristics of the population. The research focuses on identifying spatial patterns of heat stress and evaluating unequal exposure of residents depending on urban structure, environmental conditions, and socio-economic factors. Heat stress will be quantified using biometeorological indices (e.g., PET, UTCI) derived from a combination of Earth observation data, meteorological measurements, and microclimate modelling. The spatial distribution of heat stress indices will be analysed under different meteorological conditions, with particular emphasis on extreme heat events. Socio-economic data, such as age structure, population density, socio-economic status, and housing characteristics, will be integrated into geographic information systems to identify vulnerable population groups and areas with cumulative environmental and social risks. The study will apply spatial statistical methods to assess relationships between heat stress and socio-economic factors and to identify areas with pronounced inequalities in thermal exposure. The results will enhance understanding of the socio-spatial dimensions of urban heat and provide a scientific basis for targeted and socially equitable heat mitigation and adaptation strategies in urban environments.
prof. Mgr. Jaroslav Hofierka, PhD.
RNDr. Janetta Nestorová-Dická, PhD., univerzitná docentka
Geoinformatics and Remote Sensing (GId)
Spatial relationships between modelled and perceived heat stress in the urban environment
SK
doc. Mgr. Ladislav Novotný, PhD.
prof. Mgr. Jaroslav Hofierka, PhD.
Geoinformatics and Remote Sensing (GIdAj)
Spatial relationships between modelled and perceived heat stress in the urban environment
EN
This doctoral thesis focuses on the analysis of spatial relationships between modeled and perceived heat stress in the urban environment. In the context of ongoing climate change and the increasing frequency and intensity of extreme temperature events, urban heat stress has become a critical issue in terms of quality of life, public health, and sustainable urban planning. The main objective of the thesis is to identify spatial patterns, discrepancies, and geographical determinants of heat stress perception by comparing modeled indicators of thermal load with the subjective perceptions of urban residents. The research integrates quantitative modeling of bioclimatic heat stress indices with qualitative and quantitative data obtained through questionnaire surveys. The methodological framework is based on the application of geoinformatics tools, spatial analysis techniques, and statistical methods that enable the assessment of agreement and divergence between objectively modeled heat stress indicators and residents’ subjective experiences across different urban areas. Particular attention is given to identifying influencing factors such as urban morphology, building density, green infrastructure, terrain characteristics, and socio-demographic attributes that may shape the differences between physically determined and perceived heat stress. The results contribute to a deeper understanding of the complex interactions between the physical characteristics of urban environments and human thermal perception. Furthermore, the findings provide a valuable basis for the design of effective climate adaptation strategies, climate-sensitive urban planning, and the enhancement of urban resilience to extreme heat conditions.
To identify spatial patterns, discrepancies, and geographical determinants of heat stress perception by comparing modeled indicators of thermal load with the subjective perceptions of urban residents.
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doc. Mgr. Ladislav Novotný, PhD.
prof. Mgr. Jaroslav Hofierka, PhD.
Geoinformatics and Remote Sensing (GIdAj)
The Urban Spatial Differentiation of Heat Stress in Cities and Its Relationship with Socio-Economic Factors
EN
The aim of this doctoral dissertation is to analyse the spatial differentiation of heat stress within a city and to investigate its relationship with selected socio-economic characteristics of the population. The research focuses on identifying spatial patterns of heat stress and evaluating unequal exposure of residents depending on urban structure, environmental conditions, and socio-economic factors. Heat stress will be quantified using biometeorological indices (e.g., PET, UTCI) derived from a combination of Earth observation data, meteorological measurements, and microclimate modelling. The spatial distribution of heat stress indices will be analysed under different meteorological conditions, with particular emphasis on extreme heat events. Socio-economic data, such as age structure, population density, socio-economic status, and housing characteristics, will be integrated into geographic information systems to identify vulnerable population groups and areas with cumulative environmental and social risks. The study will apply spatial statistical methods to assess relationships between heat stress and socio-economic factors and to identify areas with pronounced inequalities in thermal exposure. The results will enhance understanding of the socio-spatial dimensions of urban heat and provide a scientific basis for targeted and socially equitable heat mitigation and adaptation strategies in urban environments.
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prof. Mgr. Jaroslav Hofierka, PhD.
RNDr. Janetta Nestorová-Dická, PhD., univerzitná docentka