# Assessing Spatiotemporal LST Variations in Urban Landscapes Using Diurnal UAV Thermography
## 1 Introduction  
Understanding land surface temperature (LST) variations is critical for analyzing thermal dynamics in urban and natural environments, particularly in the context of climate change and urban planning. LST influences energy balance, urban heat island effects,and local climate resilience, making its accurate assessment essential for sustainable development and environmental management. Local climate resilience refers to the capacity of urban and natural environments to withstand, adapt to, and recover from climate-related stresses while maintaining essential functions and services. In the context of thermal dynamics, it encompasses the ability of different landscapes to moderate temperature extremes and mitigate heat-related impacts through their surface properties and cooling mechanisms [1]. This concept is increasingly crucial as cities face growing challenges from urban heat islands, extreme heat events, and changing precipitation patterns that directly impact human health, energy consumption, and ecosystem functioning [2; 3]. The increasing urbanization and alteration of land cover types significantly affect surface heat retention, leading to localized temperature variations that influence microclimate conditions and energy balance [4]. Traditional satellite-based remote sensing methods, such as Landsat (16-day revisit cycle) or MODIS thermal infrared sensors (with up to four observations per day combining Terra and Aqua platforms), have been widely used to assess LST; however, these approaches are often limited by their low spatial resolution (100 m for MODIS thermal bands, 30-100 m for Landsat) and constrained temporal flexibility for capturing complete diurnal cycles, which restrict their ability to detect fine-scale temperature variations and rapid thermal transitions within urban environments [5]. As an alternative, unmanned aerial vehicles (UAVs) equipped with thermal infrared cameras provide high-resolution, on-demand thermal data collection at user-defined intervals throughout the day, allowing for more detailed temporal and spatial monitoring of temperature dynamics across different land cover types [6]. The high temporal flexibility and spatial resolution of UAV-based thermal imaging directly enables this study's core methodological approach. While satellite platforms are limited to fixed overpass times and coarser resolutions (typically 30-100 m for Landsat/MODIS), our UAV deployment captures critical diurnal transitions (morning, afternoon, evening, and midnight) at centimeter-scale resolution. This capability is essential for detecting fine-scale thermal variations across our five target LULC classes and capturing the complete diurnal cycle of heat absorption and dissipation, which would be impossible using traditional satellite methods. The temporal granularity afforded by UAV platforms is particularly crucial for quantifying nocturnal cooling rates and heat retention differences among urban materials--key processes in understanding urban microclimate dynamics that satellite-based approaches cannot adequately resolve. UAV-based thermal imaging has been particularly effective in studying small-scale surface temperature variations, detecting urban heat island effects, and evaluating surface heat retention across various land uses [7]. Different land cover types exhibit distinct thermal responses due to their surface material properties. Impervious surfaces, such as asphalt and concrete, typically absorb and retain more heat than permeable surfaces like grass or water bodies, leading to significant temperature differences during the day [8]. UAV-based studies have documented temperature variations of up to 25 \({}^{\circ}\)C between urban and vegetated surfaces, highlighting the importance of land cover in modulating heat accumulation [9]. Moreover, natural surfaces, such as grasslands and water bodies, exhibit lower thermal fluctuations due to evapotranspiration and higher specific heat capacity, which contribute to effective heat dissipation [10].