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	<title>Future cities &#8211; Gate</title>
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	<description>Big Data for Smart Society</description>
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		<title>A New Railway-Driven Urban Expansion: A Numerical Study of Thermal Conditions in Neighborhood Environments</title>
		<link>https://www.gate-ai.eu/en/research/a-new-railway-driven-urban-expansion-a-numerical-study-of-thermal-conditions-in-neighborhood-environments/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Fri, 24 Oct 2025 09:28:21 +0000</pubDate>
				<guid isPermaLink="false">https://www.gate-ai.eu/?post_type=research&#038;p=10156</guid>

					<description><![CDATA[This study numerically assesses the impact of a new railway on urban development and thermal comfort, specifically the Tsukuba Express (TX) railway in the Tokyo Metropolitan area, Japan. The railway was chosen because it connects high-, mid-urbanized, and suburban areas in the Tokyo Metropolitan region, Japan, allowing for a distinct evaluation of its impact on [&#8230;]]]></description>
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<p id="artAbst" class="collapse-blocked">This study numerically assesses the impact of a new railway on urban development and thermal comfort, specifically the Tsukuba Express (TX) railway in the Tokyo Metropolitan area, Japan. The railway was chosen because it connects high-, mid-urbanized, and suburban areas in the Tokyo Metropolitan region, Japan, allowing for a distinct evaluation of its impact on each urban area type. Consequently, four representative stations were selected: one in a high-urbanized area, two in mid-urbanized areas, and one in a suburban area. A numerical atmospheric model, the Weather Research and Forecasting (WRF), with a horizontal resolution of 250 m, was used to simulate the areas along the entire railway, including the stations. The study includes two simulation cases: before (2005) and after (2015) the construction of the TX. The impact of urbanization on surface air temperature distribution along the TX railway is initially assessed. The results indicate that the most significant temperature increase (1.7 °C) occurred in suburban stations between 2005 and 2015 at 1800 JST compared to other areas. Following the development of the TX railway in 2005, anthropogenic heat (AH) release from buildings and traffic increased rapidly by approximately 80 W/m2. The study highlights that areas experiencing significant increases in air temperature and energy consumption need careful attention and the implementation of feasible environmentally friendly measures.</p>
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		<title>Metro-Driven Urban Sprawl: Analysing the Impact of Sofia’s Metro-Expansion on Urban Transformation</title>
		<link>https://www.gate-ai.eu/en/research/metro-driven-urban-sprawl-analysing-the-impact-of-sofias-metro-expansion-on-urban-transformation/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Tue, 30 Sep 2025 12:37:30 +0000</pubDate>
				<guid isPermaLink="false">https://www.gate-ai.eu/?post_type=research&#038;p=10080</guid>

					<description><![CDATA[Urban sprawl involves population expansion, rising energy demand, land use changes, and transport infrastructure advancements. This research proposes a comprehensive framework to evaluate the impact of the metro in Sofia, Bulgaria, on urban transformation by combining the Geographic Information Systems (GIS) analysis and high-resolution, large-scale simulations based on the state-of-the-art Weather Research and Forecasting (WRF) [&#8230;]]]></description>
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<p id="artAbst" class="collapse-blocked"><span style="font-size: 16px;">Urban sprawl involves population expansion, rising energy demand, land use changes, and transport infrastructure advancements. This research proposes a comprehensive framework to evaluate the impact of the metro in Sofia, Bulgaria, on urban transformation by combining the Geographic Information Systems (GIS) analysis and high-resolution, large-scale simulations based on the state-of-the-art Weather Research and Forecasting (WRF) model. The urban transformation encompasses land use shifts, changes in building typology, energy consumption increases, and thermal effects from 2009 to 2024 across 45 metro stations within 800-meter buffer zones. Results show that 15.6% of metro-adjacent areas shifted to high-density developments, replacing green and lower-density zones. This densification is associated with increased gross floor area (GFA), higher energy demand, and partly exacerbated Urban Heat Island (UHI) effects. The findings reveal the impact of metro expansion on urban transformation, offering a scalable framework for cities experiencing rapid urbanisation and transit development.</span></p>
<p>https://iopscience.iop.org/article/10.1088/2515-7620/ae0f8e</p>
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		<title>Assessing Walkability in Sofia: A Multi-Metric Index for Pedestrian-Friendly Cities</title>
		<link>https://www.gate-ai.eu/en/research/assessing-walkability-in-sofia-a-multi-metric-index-for-pedestrian-friendly-cities/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Tue, 30 Sep 2025 12:33:18 +0000</pubDate>
				<guid isPermaLink="false">https://www.gate-ai.eu/?post_type=research&#038;p=10075</guid>

					<description><![CDATA[Despite the growing interest in urban walkability, a significant gap remains in assessing pedestrian accessibility at the neighbourhood level in Sofia, Bulgaria. This study aims to bridge this gap by developing a comprehensive walkability index tailored to Sofia’s urban environment. The index is constructed using ten key metrics that reflect six core aspects of pedestrian [&#8230;]]]></description>
										<content:encoded><![CDATA[<p>Despite the growing interest in urban walkability, a significant gap remains in assessing pedestrian accessibility at the neighbourhood level in Sofia, Bulgaria. This study aims to bridge this gap by developing a comprehensive walkability index tailored to Sofia’s urban environment. The index is constructed using ten key metrics that reflect six core aspects of pedestrian experience: connectivity, convenience, comfort, conviviality, coexistence, and commitment. The methodology employs geospatial analysis and computational modelling implemented in Python, leveraging libraries such as GeoPandas, Shapely, and NetworkX. The study assesses street connectivity using a link-to-node ratio, public transport coverage via shortest-path analysis, and network integration through the Pedestrian Route Directness Indicator (PRDI). Land use mix is evaluated using entropy-based calculations, while residential density considers household distribution within the built environment. Essential activities, pedestrian infrastructure, and convivial points are analysed based on proximity and spatial coverage. Traffic conditions are quantified through lane density, and the pedestrian-friendly network is assessed by mapping designated pedestrian-prioritized areas.<br />
Results reveal spatial disparities in walkability across Sofia’s neighbourhoods, with variations influenced by infrastructure availability, land use diversity, and traffic conditions. By visualizing normalized scores, the study identifies areas with inadequate pedestrian conditions, providing a framework for targeted infrastructure improvements. The findings contribute to urban planning by offering actionable insights to enhance pedestrian accessibility and promote sustainable mobility. This methodology is adaptable to other urban contexts, further advancing walkability research and policy development.</p>
<p>https://isprs-archives.copernicus.org/articles/XLVIII-4-W16-2025/75/2025/</p>
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		<title>Urban Land Use Classification of High-Resolution Aerial Imagery Using RemoteCLIP: A Case Study of Sofia</title>
		<link>https://www.gate-ai.eu/en/research/urban-land-use-classification-of-high-resolution-aerial-imagery-using-remoteclip-a-case-study-of-sofia/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Tue, 30 Sep 2025 11:54:33 +0000</pubDate>
				<guid isPermaLink="false">https://www.gate-ai.eu/?post_type=research&#038;p=10050</guid>

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		<title>Advancing Urban Air Quality Forecasting: A Deep Learning Approach for Real-Time Monitoring in Sofia</title>
		<link>https://www.gate-ai.eu/en/research/advancing-urban-air-quality-forecasting-a-deep-learning-approach-for-real-time-monitoring-in-sofia/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Tue, 30 Sep 2025 11:50:16 +0000</pubDate>
				<guid isPermaLink="false">https://www.gate-ai.eu/?post_type=research&#038;p=10046</guid>

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		<title>Pedestrian Movement Prediction and Pattern Analysis</title>
		<link>https://www.gate-ai.eu/en/research/pedestrian-movement-prediction-and-pattern-analysis/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Tue, 30 Sep 2025 11:35:36 +0000</pubDate>
				<guid isPermaLink="false">https://www.gate-ai.eu/?post_type=research&#038;p=10041</guid>

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		<title>Evaluation of the Compliance of Urban Functions in Sofia City with the 15-minute City Concept</title>
		<link>https://www.gate-ai.eu/en/research/evaluation-of-the-compliance-of-urban-functions-in-sofia-city-with-the-15-minute-city-concept/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Tue, 30 Sep 2025 11:29:53 +0000</pubDate>
				<guid isPermaLink="false">https://www.gate-ai.eu/?post_type=research&#038;p=10037</guid>

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		<title>3D Solar Analysis of the Street Network and Impact Estimation of the Shade of Trees at the District Scale.</title>
		<link>https://www.gate-ai.eu/en/research/3d-solar-analysis-of-the-street-network-and-impact-estimation-of-the-shade-of-trees-at-the-district-scale/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Tue, 30 Sep 2025 11:16:06 +0000</pubDate>
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		<title>Location-Allocation of Social Amenities Based on Constraint Programming</title>
		<link>https://www.gate-ai.eu/en/research/location-allocation-of-social-amenities-based-on-constraint-programming/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Tue, 30 Sep 2025 11:09:22 +0000</pubDate>
				<guid isPermaLink="false">https://www.gate-ai.eu/?post_type=research&#038;p=10029</guid>

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		<title>Walkability analysis of Sofia’s neighborhoods powered by 15-minute city concept</title>
		<link>https://www.gate-ai.eu/en/research/walkability-analysis-of-sofias-neighborhoods-powered-by-15-minute-city-concept/</link>
		
		<dc:creator><![CDATA[Eleonora Getsova]]></dc:creator>
		<pubDate>Tue, 30 Sep 2025 11:00:46 +0000</pubDate>
				<guid isPermaLink="false">https://www.gate-ai.eu/?post_type=research&#038;p=10024</guid>

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