Urban green spaces provide measurable cooling that can mitigate urban heat islands, yet few studies have quantified these effects over multiple decades. This study analyzed Landsat imagery from four epochs (1990, 2000, 2013, 2018) to derive land surface temperature (LST) and vegetation indices—NDVI for greenness and NDMI for moisture content—for four large urban parks in Krakow. Late spring/summer LST in parks was compared with that of urban areas within 0–150 m and 150–300 m of park boundaries. Statistical significance was evaluated using bootstrapped confidence intervals, long-term trends were assessed via the Mann–Kendall test, and correlation analysis was used to examine relationships between LST and each vegetation index. Results show a persistent park cooling effect, with park interiors ~2–3 °C cooler than adjacent urban areas in all years. Despite an overall city-wide LST rise of ~5–6 °C from 1990 to 2018, the park cool island intensity (temperature difference between park and city) remained stable (no significant long-term trend, p > 0.7). Bootstrapped 95% confidence intervals confirmed that each park’s cooling effect was statistically significant in each year analyzed. NDMI (vegetation moisture content) correlated more strongly with LST (r ~ −0.90) than NDVI (r ~ −0.7 to −0.9), highlighting the importance of vegetation moisture in park cooling. These findings demonstrate that well-watered urban parks can sustain substantial cooling benefits over decades of urban development. The persistent ~2–3 °C daytime cooling observed underscores the value of water-sensitive green space planning as a long-term urban heat mitigation strategy.

Estimating land surface temperature (LST) in urban environments remains a complex task due to high surface heterogeneity and variations in material emissivity. This study compares LST products from four satellite sensors (Landsat 8 TIRS, ECOSTRESS, MODIS Terra, and Sentinel-3 SLSTR) with in-situ temperature measurements recorded by 27 ground-based sensors placed across diverse urban surface types in Kraków, Poland.To minimize cross-platform discrepancies, a harmonization workflow was applied, including spatial reprojection, temporal alignment within a ±15-minute window, and emissivity normalization. Residuals were assessed using standard validation metrics: RMSE, MAE, bias, and Pearson’s correlation coefficient. Among the examined datasets, Landsat 8 delivered the most consistent results (RMSE ≈ 7.7°C), while ECOSTRESS exhibited the highest positive bias and spatial variability. Residual errors were notably larger over vegetated areas, reflecting the effects of variable emissivity and canopy shading.Despite the observed errors, the harmonized dataset enables consistent comparisons between sensors and an effective thermal assessment of urban areas. The results highlight the methodological relevance of harmonization in thermal remote sensing, particularly in heterogeneous urban areas.

Park cooling in Krakow was quantified with archival Landsat imagery from 1990, 2000, 2013, and 2018. A linear mixed effects model with random intercepts for Area and PointID was applied to 33,949 locations and about 136,000 samples. Land surface temperature (LST) was retrieved with Landsat Collection 2 Level‑2 Surface Temperature product. Cooling was defined as the within scene difference in LST between park cores at 0 m and fixed buffers at 150 and 300 m. NDVI and NDMI were included as standardized predictors. Between 1990 and 2018, mean LST rose by about 4°C. Park cores were cooler than the 150 m buffer by about ∼2.1–2.6°C, and cooler than the 300 m buffer by about ∼2.6–3.3°C. The distance decay changed over time. The core to edge contrast peaked around 2000. Relative to 1990, the contrast in 2000 was larger by 0.50°C at 150 m and by 0.67°C at 300 m. It weakened by 2013 and partly recovered in 2018. NDMI showed a stronger association with LST than NDVI (−1.25°C per one standard deviation; p < 0.001 versus NDVI non‑significant (p = 0.846)). Fixed effects explained about 37.5% of variance and the full model about 95.6%. The results show persistent mitigation of surface heat by urban forests and point to the importance of canopy moisture and the protection of near park buffers. The study provides reference values that can be compared across cities and years to guide evaluation of urban heat mitigation.

The study evaluated whether simple site-specific empirical corrections can improve the agreement between Landsat 8 and ECOSTRESS thermal products and ground-based surface temperature logger observations acquired in Kraków, Poland. Three field campaigns conducted in 2023–2024 were paired with Landsat 8 and, when available, ECOSTRESS acquisitions. Two correction approaches, linear regression and additive bias correction, were tested for eight calibration subset configurations representing different urban surface contexts, including paved surfaces, urban parks, heterogeneous urban sites, waterfront locations, spatially dispersed sites, vegetation-covered sites, and a subset defined by low initial mismatch. Performance was assessed using RMSE and the standard deviation of residuals relative to the reference measurements. Both correction approaches reduced disagreement relative to the uncorrected data, but the magnitude of improvement depended strongly on acquisition date, product type, and calibration subset composition. The results show that simple local correction can increase the practical utility of satellite thermal data in a heterogeneous urban setting; however, the findings should be interpreted with caution because contact-based logger measurements are not strictly equivalent to radiometric land surface temperature, and some satellite ground pairs were not fully synchronous.