Using MODIS and Landsat LST images, the present paper advances a series of results on the characteristics of the surface heat island (SUHI) of Bacău City (Romania) during the warm season (April to September) for a period of 20 years (2001–2020). At the same time, given their higher temporal resolution and their availability for both day and night, MODIS LST was used to understand the spatial features of the SUHI in relation to land use. In this way, a total of 946 MODIS Terra and 483 Landsat satellite images were used to outline the main LST characteristics of the days with clear sky in this middle-sized city in northeast Romania. In order to analyze MODIS LST changes in relation to land use changes in the period 2001–2018, we used the standardized CORINE Land Cover datasets. With the help of the Rodionov test, we were able to determine the geometry and intensity of the SUHI. During the day, the spatial extension of the SUHI reaches its maximum level and is delimited by the isotherm of 31.0 °C, which is 1.5–2.0 °C warmer than the neighboring non-urban areas. During the night, the SUHI has a more regulated spatial extension around the central area of the city, delimited by the 15.5 °C isotherm with LST values that are 1.0–1.5 °C warmer than the surrounding non-urban areas. Additionally, from a methodological point of view, we highlight that resampled MODIS and Landsat images at a spatial resolution of 500 m can be used with confidence to understand the detailed spatial features of the SUHI. The results of this study could help the elaboration of future policies meant to mitigate the effects of urbanization on the SUHI in an era of increasing air temperatures during summer.

The current study brings detailed Land Surface Temperature (LST) information on 6 medium and small cities located in north-eastern Romania, with urban features that are specific to eastern Europe. In this analysis 2273 Landsat images have been used, outlining the LST spatial distribution and its long term (1984–2022) evolution for the analyzed cities at LCZs level, but also enabling a sound spatial hot/cold spots identification. The methodological approach included LST products investigation, LCZ classification, trend analysis and cold/hot spots analysis using Getis-Ord Gi* statistic. The results indicate that for the warm season the highest LST values correspond to industrial areas (32–34 °C), while the tree-based green areas and the water bodies are the coldest (26–28 °C). Moreover, the built-up LCZ types are subject to a higher positive trend of LST, capable to determine an intensification of SUHI in most of the analyzed cities. Consequently, the industrial areas and the high densely built LCZs contribute mostly to urban hot spots development, while forests and water bodies around the cities are overlapping the cold spots. Hot/cold spots identification besides the understanding of their LCZ features serve as a useful tool for urban stakeholders in their effort to advance concrete measures to mitigate temperature extremes inside the urban areas.

The study investigates the thermal characteristics of the urban area of Bârlad city, Romania, in relation with urban land use (LU) and land cover (LC). This was done using Land Surface Temperature (LST) data provided by Moderate Resolution Imaging Spectroradiometer (MODIS) and mobile measurements conducted during stable atmospheric conditions. To identify important factors that influence Surface Urban Heat Island (SUHI) and Canopy Layer Urban Heat Island (CLUHI) two types of LU/LC classifications were used. At the annual level, during the day, the highest LST values are observed in the most densely built-up areas of the city, with values exceeding 18°C. The lowest LST instead are observed in the northern area of the city, with prevailing natural areas, where LST values reach 17.4°C. During the night, the urban area maintains constantly high LST above 4°C, while the lowest LST values are observed in the forested area in the eastern part of the city, where mean LST drops close to 3°C. The results of this study highlight the significant impact that LU/LC has on the inception of SUHI in small cities. Generally, built-up surfaces from Urban Atlas (UA) and Local Climate Zones (LCZ) classifications, are warmer than natural land cover types, both during day and night, with at least 0.5 to 1.5°C, which is enough to outline a clearly delimited SUHI especially during summer days. During stable atmospheric conditions the CLUHI exhibits large intensities emphasized by local cooling processes manifested especially during thermal inversion conditions.

Urban Heat Island (UHI) is caused by inadvertent climate modification due to human spatial concentration, being generally defined as the difference in temperature between urban areas and their rural surroundings. However, seen at fine spatial resolution, the heat island seems rather to look like an archipelago of hot spots delimited by colder areas. This study analyses the Surface Urban Heat Islands (UHISurf) of 16 cities located in Romania’s North-East Development Region for the identification of these hot and cold spots.For each city, in order to identify UHISurf’s hot and cold-spots, Landsat series of satellites were used due to their potential to provide Land Surface Temperature (LST) product at a high spatial resolution, which is commonly required for micro or local scale studies. For this purpose, LST is derived from the Landsat 4, 5, 7, and 8 (1988-2021), collection 1 (using the Statistical Mono-Window algorithm), implemented in Google Earth Engine platform.For hot /cold spots identification, Hot Spot Analysis (Getis-Ord Gi*) tool from ArcGIS Pro 3.0 was used. This tool calculates the Getis-Ord Gi* statistic for each feature in a dataset by looking at each feature within the context of neighboring features. To be classified as a statistically significant hot spot, a feature will have a high value and has to be surrounded by other features with high values. The local sum for a feature and its neighbors is compared proportionally to the sum of all features and a statistically significant z-score results. The larger the z-score is (positive), the more intense the clustering of high values defined as hot spots. The smaller the z-score is (negative), the more intense the clustering of cold spots. When the False Discovery Rate (FDR) correction is applied, statistical significance is adjusted to account for multiple testing and spatial dependency.This procedure was applied for each of 16th cities, summing up 10900 images which cover an area of 2526,8 km2. LST is strongly controlled by surface properties (radiative, thermal, geometric, moisture and aerodynamic), these giving a greater surface temperature variability compared to air temperature, particularly during the day. Inside the identified hot spots, the LST is with 8-10C higher than the mean of UHISurf LST. Generally, light industrial, warehouses and transportation infrastructure (airports) are often relatively hot-spots, while cold-spots, are obviously more heavily vegetated areas, water bodies and areas of well-watered vegetation, but their futures are related to each city characteristics. The obtained results are designated to be used as the main assessment of urban heat island, delivering for stakeholder a clear image of the target regions inside the cities for the policies dedicated to the mitigation of the urban heat island effect.

In this research, we outline the main thermo-hygrometric characteristics of local climate zones (LCZs) identified in four of the largest cities in north-eastern Romania (Iași, Bacău, Botoșani, and Suceava), which together have a population of over 1 million inhabitants. The urban structure of these cities could be considered typical for medium size cities in Eastern Europe, being characterized by their recent development, with residential and industrial areas developed intensively in the communist period, followed nowadays by the conversion of decaying industrial areas in commercial units and a new phase of largely unorganized residential expansion. We used the LCZ Generator to assess local climate zones in these cities, resulting in the identification of eight LCZs, with the largest extension being specific to compact midrise and open midrise, covering approximately 40% of the cities' surface. The accuracy of the LCZ delimitation ranges from 0.80 to 0.90. We described the thermo-hygrometric features within the identified LCZs using in-situ observations, mobile measurements, and LANDSAT LST products. We used 30 in-situ observation points for air temperature and humidity with hourly temporal resolution to describe the major features of LCZs. We also made two mobile measurements monthly between May 2022 and April 2023 for each city, during clear sky conditions, in the early morning and the first part of the night, in order to spatially cover the diversity of LCZs. The thermo-hygrometric profile of LCZs was completed with LANDSAT LST data analyzed for 1983-2021, enabling a multiannual trend analysis of the two main LCZs in the analyzed cities. We grouped the study results by advective and radiative conditions using a Self-Organizing Maps method for atmospheric circulation. We also explored the thermo-hygrometric features of the two main LCZs using EUROCORDEX data for 2025-2100. The main output of this analysis indicates that the magnitude of changes identified in either moderate or extreme climate scenarios overwhelms the differences observed nowadays between the current conditions imposed by each local climate zone. The results of this study synthesize the progress made in assessing urban climate conditions in the cities of North-Eastern Romania, in the framework of UCLAR project, and are intended to serve as a basis for mitigation policies to be developed by local and regional stakeholders for the sustainable development of these cities in the actual context of climate change. Acknowledgement: This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS - UEFISCDI, project number PN-III-P1-1.1-TE-2021-0882, within PNCDI III.