Assessment of urban heat Island for Craiova from satellite-based LST

Udriștioiu, Mihaela Tinca; Velea, Liliana; Bojariu, Roxana; Sararu, S. C.

doi:10.1063/1.5017443

Cited by 6 publications

(3 citation statements)

References 19 publications

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“…Extensive research has been dedicated to studying these variations with different approaches, at different scales, and with different tools. Udristioiu et al [16] and Sassi and Fourri [17] are recent examples on how to study the satellite remote sensing data, gathering information on Land Surface Temperature (LST) from infrared radiation measures. Other case studies, such as the one presented by Khamchiangta et al [18], have used large geographical data to study the land use land coverage and correlated these conditions to estimate the possible response to undisturbed climatic readings (e.g., weather data); also, these databases have been combined with geographical tools (e.g., Geographic information Systems (GISs)) and small-scale on-site measurements to communicate actual point-in-time conditions [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

A New Approach to Assess the Built Environment Risk under the Conjunct Effect of Critical Slow Onset Disasters: A Case Study in Milan, Italy

et al. 2021

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Citizens in dense built environments are susceptible to the simultaneous occurrence of Slow Onset Disaster (SLOD) events, being particularly prone to increasing temperatures and air pollution. Previous research works have assessed these events’ arousal separately and have identified when their intensity is critical. However, few have integrated their analysis, possibly limited by the quality and granularity of available data, the accessibility and distribution of sensors, and measurements not emulating the surroundings of a pedestrian. Thus, this work performed an outdoor meso-scale multi-hazard-based risk analysis to study the aggregated effects of the SLODs mentioned above. The study was carried out to narrow down the time-frames within 2019 in which these two events could have affected citizens’ health the most. A weighted fuzzy logic was applied to superimpose climatic (temperature, humidity, wind speed, and solar irradiance) and air quality (particulate matter, ozone, and ammonium) distress (true risk) on an hourly basis, allocated using set healthy and comfortable ranges for a specific dense urban climate context within Milan (Italy), processing data from Milano via Juvara station. The findings show that sensitive groups were at risk of high temperature and pollution separately during 26% and 29% of summer and mid-season hours, respectively; while multi-hazard risk would arise during 10.93% of summer and mid-season hours, concentrated mainly between 14:00 and 20:00.

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Section: Introductionmentioning

confidence: 99%

A New Approach to Assess the Built Environment Risk under the Conjunct Effect of Critical Slow Onset Disasters: A Case Study in Milan, Italy

et al. 2021

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“…Climate change creates difficulties for the cardiopulmonary and gastrointestinal systems and increases the risk of infectious and allergic diseases [ 1 ]. Within climate change, urban heat and air pollution contribute to the rise in temperature [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey

Pekdogan,

Udriștioiu,

Yildizhan

et al. 2024

Sensors

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Air pollution significantly threatens human health and natural ecosystems and requires urgent attention from decision makers. The fight against air pollution begins with the rigorous monitoring of its levels, followed by intelligent statistical analysis and the application of advanced machine learning algorithms. To effectively reduce air pollution, decision makers must focus on reducing primary sources such as industrial plants and obsolete vehicles, as well as policies that encourage the adoption of clean energy sources. In this study, data analysis was performed for the first time to evaluate air pollution based on the SPSS program. Correlation coefficients between meteorological parameters and particulate matter concentrations (PM1, PM2.5, PM10) were calculated in two urban regions of Romania (Craiova and Drobeta-Turnu Severin) and Turkey (Adana). This study establishes strong relationships between PM concentrations and meteorological parameters with correlation coefficients ranging from −0.617 (between temperature and relative humidity) to 0.998 (between PMs). It shows negative correlations between temperature and particulate matter (−0.241 in Romania and −0.173 in Turkey) and the effects of humidity ranging from moderately positive correlations with PMs (up to 0.360 in Turkey), highlighting the valuable insights offered by independent PM sensor networks in assessing and improving air quality.

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“…For Romania, some studies were performed aiming to analyze the UHI for some of the main cities mainly based on MODIS satellite products [16,[23][24][25][26][27], but Landsat has also been used [28].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Features of the Surface Urban Heat Island of Bacău City (Romania) during the Warm Season and Local Trends of LST Imposed by Land Use Changes during the Last 20 Years

Sfîcă,

Corocăescu,

Crețu

et al. 2023

Remote Sensing

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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.

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Assessment of urban heat Island for Craiova from satellite-based LST

Cited by 6 publications

References 19 publications

A New Approach to Assess the Built Environment Risk under the Conjunct Effect of Critical Slow Onset Disasters: A Case Study in Milan, Italy

A New Approach to Assess the Built Environment Risk under the Conjunct Effect of Critical Slow Onset Disasters: A Case Study in Milan, Italy

From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey

Spatiotemporal Features of the Surface Urban Heat Island of Bacău City (Romania) during the Warm Season and Local Trends of LST Imposed by Land Use Changes during the Last 20 Years

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