Study of Spatiotemporal Variations of Summer Land Surface Temperature in Kyiv, Ukraine Using Landsat Time Series
Abstract
The aim of this study was to investigate long-term changes in the summer thermal regime of surface for the city of Kyiv (Ukraine) using Landsat time series. The overall data subset included 572 Landsat 4– 8 Collection 1 Level 2 scenes for the area of Kyiv and its surroundings for June-August 1984– 2019. Trend analysis was based on the Mann-Kendall test for trend using Theil-Sen slope estimator to quantify the direction and magnitude of change over time accompanied by statistical metrics to assess the strength and significance of the association between the variables of land surface temperature (LST) and time. Between 1984 and 2019, for the entire study area LSTs demonstrate a mean annual increase of 0.17 $±$ 0.06 ° C with prevailing positive trends of various magnitudes. The developed workflow allows for a spatially flexible retrieval of LSTs and the calculation of long-term means to characterize the surface thermal regime at high spatial detail.
Daria Svidzinska
Postdoctoral fellow / Earth System Data Science
My research interests focus on the spatio-temporal patterns of environmental change. To unravel these patterns I analyze the time series of remote sensing environmental variables. This information is then applied to inform and support data-driven strategies for sustainable and resilient development. My current research project seeks to reveal the impacts of war actions on protected ecosystems in Ukraine through remote sensing data analysis to guide future monitoring and restoration practices.