Search Results (351)

The objective of this study is to explore the applicability of irregular area cartograms for the visualization of sustainable development indicator components, utilizing earth observation (EO) data. The analysis focuses on selected Sustainable Development Goals (SDG 11 ‘Make cities and human settlements inclusive, safe, resilient and sustainable’ and SDG 13 ‘Take urgent action to combat climate change and its impacts’) and specific targets and indicators related to green urban areas and air quality (targets: 13.2, 11.6, and 11.7; indicators: 11.6.2., 11.7.1., 13.2.2.). A comprehensive review of the relevant literature indicates that irregular area cartograms are employed only sporadically in the context of SDG monitoring, particularly at lower levels of territorial division (i.e., communes and counties). To address this gap, a series of thematic maps, including choropleth maps and irregular area cartograms, was developed. These visualizations are based on EO-derived datasets and supplemented with statistical information obtained from the Local Data Bank of the Statistics Poland. The analysis demonstrates that irregular area cartograms provide an effective means of visualizing spatial disparities in variables such as urban green space availability and air pollution at the commune and county levels. These visualizations enhance the interpretability of complex indicator structures and support more nuanced assessments of progress toward selected Sustainable Development Goals, especially in spatially detailed analytical frameworks. Preliminary usability testing among potential users revealed that irregular area cartograms are perceived as an interesting visualization technique that enhances data interpretation. Full article

Wildfires increasingly threaten Mediterranean landscapes, particularly in regions like Attica, Greece, where urban sprawl, agricultural abandonment, and climatic conditions heighten the risk at the Wildland–Urban Interface (WUI). The Mediterranean basin, recognized as one of the global wildfire “hotspots”, has witnessed a steady increase in both fire severity, frequency, and burned area during the last four decades, a trend amplified by urban sprawl and agricultural land abandonment. This study represents the first integrated, region-wide mapping of the WUI and associated wildfire risk in Attica, the most densely urbanized area in Greece and one of the most fire-exposed metropolitan regions in Southern Europe, utilizing advanced techniques such as Earth Observation and GIS analysis. For this purpose, various geospatial datasets were coupled, including Copernicus High Resolution Layers, multi-decadal Landsat fire history archive, UCR-STAR building footprints, and CORINE Land Cover, among others. The research delineated WUI zones into 40 interface and intermix categories, revealing that WUI encompasses 26.29% of Attica, predominantly in shrub-dominated areas. An analysis of fire frequency history from 1983 to 2023 indicated that approximately 102,366 hectares have been affected by wildfires. Risk assessments indicate that moderate hazard zones are most prevalent, covering 36.85% of the region, while approximately 25% of Attica is classified as moderate, high, or very high susceptibility zones. The integrated risk map indicates that 37.74% of Attica is situated in high- and very high-risk zones, principally concentrated in peri-urban areas. These findings underscore Attica’s designation as one of the most fire-prone metropolitan regions in Southern Europe and offer a viable methodology for enhancing land-use planning, fuel management, and civil protection efforts. Full article

Supply chain disruptions and climate shocks have exposed the fragility of food systems, highlighting the urgency of reconnecting urban areas with local food production through spatial planning. This study develops a regional-scale ecosystem service (ES)-based foodshed assessment framework, integrating agricultural capacity, ecological functionality, and infrastructure, specifically roads, food industries, and markets. The framework combines the Metropolitan Foodshed and Self-Sufficiency Scenario (MFSS) model with stakeholder-prioritized integrated ES mapping and Geographic Information System (GIS)-based multi-criteria suitability analysis. Applied to Istanbul and the Marmara Region, the assessment focuses on cereals/legumes, vegetables, and fruits/spices under four scenarios projected to 2033. Results show that integrating ESs increases the area classified as suitable by 26%, while infrastructure constraints reduce it to 9%, reflecting the spatial trade-offs between ecological potential and accessibility. Istanbul, with limited agricultural land, achieves self-sufficiency levels below 10% in all scenarios, highlighting its structural dependency. Eliminating food loss and waste reduces regional land demand by 23%. The framework offers policy-relevant insights for conservation, ecological restoration, and decentralized food system development. It remains open to further enhancement through the inclusion of livestock-based systems, updated land cover data, and climate projections, factors essential for assessing long-term resilience. Overall, the ES-based assessment can support food- and ecosystem-sensitive spatial planning in metropolitan regions. Full article

Urban heat vulnerability is an increasing public health concern, particularly in rapidly urbanizing regions of southern France. This study aims to quantify and map the Heat Vulnerability Index (HVI) for Toulouse and to analyze its temporal trends to identify high-risk zones and influencing factors. The assessment integrates recent years’ remote sensing data of pollutant emissions, land use/land cover and land surface temperature, statistical data of climate-related mortalities, and socioeconomic and demographic factors. Following a detailed analysis of recent real-time air quality and weather data from multiple monitoring stations across the city of Toulouse, it was observed that Urban Pollution Island (UPI) and Urban Heat Island (UHI) are closely interlinked phenomena. Their combined effects can significantly elevate the annual mortality risk rate by an average of 2%, as calculated using AirQ+ particularly, in densely populated urban areas. Remote sensing data was processed using Google Earth Engine and all factors were grouped into three key categories: heat exposure, heat sensitivity, and adaptive capacity to derive HVI. Temporal HVI maps were generated and analyzed to identify recent trends, revealing a persistent increase in vulnerability across the city. Comparative results show that 2022 was the most critical summer period, especially evident in areas with limited vegetation and extensive use of heat-absorptive materials in buildings and pavements. The year 2024 indicates resiliency and adaptation although some areas remain highly vulnerable. These findings highlight the urgent need for targeted mitigation strategies to improve public health, enhance urban resilience, and promote overall human well-being. This research provides valuable insights for urban planners and municipal authorities in designing greener, more heat-resilient environments. Full article

The urban heat island (UHI) effect is one of the most pressing challenges associated with rapid urbanization. It arises primarily from the replacement of natural vegetation with impervious surfaces, alterations in surface energy balance, and heat emissions from human activity. Mitigating these drivers has become a global priority, particularly in fast-growing cities. Pavements play a central role in UHI intensification due to their large surface coverage, low albedo, and capacity to retain heat. This study adopts a bibliometric approach to systematically map the knowledge structure and research trends in pavement-related UHI studies. A dataset of 834 publications from Web of Science was analyzed using VOSviewer to identify leading countries and journals, central publications, the temporal evolution of research themes, and the thematic structure of the field. The analysis revealed three dominant themes: (1) pavement materials and their properties, (2) mitigation strategies that prevent UHI, and (3) cooling interventions to mitigate UHI. This study attempts to provide a comprehensive overview of the field and to clarify its interdisciplinary connections with climate adaptation and sustainability discourse. Full article

This study investigates the influence of land use and land cover (LULC) on the distribution of extreme rainfall in the tropical coastal city of Natal, Brazil. Hourly precipitation data from eight automatic rain gauges (2014–2023) were quality-controlled, with only days containing 24 h continuous records retained. Rainfall events were classified into light (<5 mm), normal (5–10 mm), intense (40–50 mm), and extreme (>50 mm) categories, and for each category daily accumulation, duration, intensity, and maximum hourly peaks were calculated. Seasonal and spatial differences across administrative zones were assessed using multivariate analysis of variance (MANOVA). The LULC changes were evaluated from the MapBiomas Collection 9 dataset. Results show that between 1985 and 2020, the proportion of urbanized (non-vegetated) surfaces increased from 27.7% (42.3 km²) to 64.3% (99.7 km²), mainly in the North and West zones, replacing agricultural and vegetated areas. The East and North zones, the most urbanized areas, recorded higher daily averages of extreme rainfall in the dry season (85–88 mm) than in the wet season (78–82 mm), with maximum peaks up to 26 mm/h and durations exceeding 17 h. These findings demonstrate that rapid urban expansion intensifies rainfall extremes, underscoring the importance of incorporating LULC monitoring (e.g., MapBiomas) and spatial planning into climate adaptation strategies for medium-sized cities. Full article

Urban areas across the globe face increased pressures to adapt to variations in energy demands and increased impacts of urban heat islands (UHIs). Urban form links closely to both energy consumption and microclimate, with factors such as density and sky view factors having a marked impact on wind reduction, surface temperatures, and outdoor comfort. Although both relationships have been widely studied independently, emerging research highlights important trade-offs between outdoor thermal comfort and energy performance. It also shows that the impacts of urban form vary significantly by climate and context. This has led to calls for a more standardized analysis approach, with some authors advocating for multi-objective optimization implementations. In hot climates, where UHI impacts are expected to be more pronounced under climate change, identifying trade-offs is challenging due to a lack of data covering urban morphology and energy modelling. This paper presents a standardized analysis method combining key urban morphology, microclimate, outdoor comfort, and energy indicators. The method’s potential to reveal relationships between urban form and performance indicators and its suitability for integration with multi-objective optimization are evaluated. For this purpose, a comparative analysis of three hot climate case studies is conducted: Al Fahidi (Dubai, UAE), Al Balad (Jeddah, SA), and Masdar City (Abu Dhabi, UAE). The analysis integrates spatial mapping of wind and surface temperature patterns, capturing day–night variations and interactions between three-dimensional form, spatial wind, surface temperature, and outdoor comfort patterns. Full article

Urban Flooding is one of the most prevalent natural hazards worldwide, leading to substantial human and economic losses. Therefore, the assessment and mapping of flood hazard levels are essential for reducing the impact of future flood disasters. This study develops and integrates a methodology to evaluate urban flood susceptibility in Nangarhar Province, Afghanistan, a semi-arid region with limited prior research. Landsat imagery from 2004 to 2024 was used to analyze land use land cover change (LULCC), indicating that built-up areas increased from 124 to 180 km² in 2004 to 2024, respectively, while agricultural land decreased from 1978 km² to 1883 km² during the same period. Climate data exhibit increases in temperatures and intensifying rainfall, exacerbating flood hazards. Geospatial analysis of elevation, slope, drainage density, and proximity to water bodies highlights the high susceptibility of low-lying areas. The Analytical Hierarchy Process (AHP) was employed to integrate diverse flood risk factors and produce accurate flood hazard maps. The findings show that very-high flood susceptibility zones expanded from 1537 to 1699 km² in 2004 to 2024, whereas low-susceptibility zones declined from 131 km² to 110 km². Socioeconomic indicators such as population density, built-up density, and education accessibility were also incorporated into the assessment. This study underscores the need for adaptive land use planning, resilient drainage systems, and community-based flood risk reduction strategies. The findings provide actionable insights for sustainable flood management and demonstrate the value of combining GIS, remote sensing, and multi-criteria analysis in data-scarce, conflict-affected regions. Full article

Urban land-use optimization plays a vital role in mitigating the escalating carbon emissions of rapidly growing cities. This study employs advanced computational intelligence to address urban carbon reduction through optimized spatial configurations. A Deep Reinforcement Learning (DRL) framework is proposed that integrates Points of Interest (POI), Areas of Interest (AOI), and Transportation System Data (TSD) to generate fine-grained carbon emission maps guiding land-use adjustments. In the case study of Hangzhou, China, results show that a carefully designed reward function enables the DRL agent to selectively optimize land-use structures, prioritizing the centralization of residential, dining, and commercial areas to form high-density, mixed-use urban clusters. This spatial reorganization leads to notable reductions in carbon emissions and improvements in resource-use efficiency. The proposed DRL-based framework provides a scientific basis for policy development toward sustainable land-use and urban density optimization. By merging advanced AI techniques with urban planning, this research contributes to the creation of low-carbon, resilient, and environmentally sustainable cities capable of addressing global climate challenges. The optimized DRL agent achieved carbon emission reductions of up to 15% compared to baseline configurations in the Hangzhou case study. Spatial concentration analysis revealed a 23% increase in residential area clustering and 31% increase in commercial zone centralization over 400 training episodes. The PPO-based model demonstrated superior performance compared to genetic algorithm and linear regression baselines, with lower policy loss (converging to <0.01) and critic loss (converging to <0.005) after early stopping at 400 episodes. However, this study is limited by its deterministic environment model, geographic specificity to Hangzhou, and exclusive focus on carbon reduction without incorporating socioeconomic constraints. Full article

In response to the coexistence of multi-objective conflicts and environmental complexity in the renewal of contemporary urban industrial heritage, this study develops a simulation and decision-making methodology for architectural and environmental renewal based on a digital twin framework. Using the Xi’an Old Steel Plant Industrial Heritage Park as a case study, a community-scale digital twin model integrating multiple dimensions—architecture, environment, population, and energy systems—was constructed to enable dynamic integration of multi-source data and cross-scale response analysis. The proposed methodology comprises four core components: (1) integration of multi-source baseline datasets—including typical meteorological year data, industry standards, and open geospatial information—through BIM, GIS, and parametric modeling, to establish a unified data environment for methodological validation; (2) development of a high-performance dynamic simulation system integrating ENVI-met for microclimate and thermal comfort modeling, EnergyPlus for building energy and carbon emission assessment, and AnyLogic for multi-agent spatial behavior simulation; (3) establishment of a comprehensive performance evaluation model based on Multi-Criteria Decision Analysis (MCDA) and the Analytic Hierarchy Process (AHP); (4) implementation of a visual interactive platform for design feedback and scheme optimization. The results demonstrate that under parameter-calibrated simulation conditions, the digital twin system accurately reflects environmental variations and crowd behavioral dynamics within the industrial heritage site. Under the optimized renewal scheme, the annual carbon emissions of the park decrease relative to the baseline scenario, while the Universal Thermal Climate Index (UTCI) and spatial vitality index both show significant improvement. The findings confirm that digital twin-driven design interventions can substantially enhance environmental performance, energy efficiency, and social vitality in industrial heritage renewal. This approach marks a shift from experience-driven to evidence-based design, providing a replicable technological pathway and decision-support framework for the intelligent, adaptive, and sustainable renewal of post-industrial urban spaces. The digital twin framework proposed in this study establishes a validated paradigm for model coupling and decision-making processes, laying a methodological foundation for future integration of comprehensive real-world data and dynamic precision mapping. Full article

Urban flooding is a major challenge to sustainable development in rapidly urbanizing cities. This study applies an integrated approach that combines Sentinel-1 SAR data, geomorphological analysis, and the DPSIR (Drivers–Pressures–State–Impacts–Responses) framework to assess the relationship between urbanization and flooding in Hanoi during the 2010–2024 period (with Sentinel-1 time-series data for 2015–2024). A time series of Sentinel-1 images (2015–2024) was processed on Google Earth Engine to detect inundation and construct a flood frequency map, which was validated against 148 field survey points (overall accuracy = 87%, Kappa = 0.79). The results show that approximately 80% of newly urbanized areas are situated on geomorphologically sensitive units, including inside- and outside-dike floodplains, fluvio-marine plains, paleochannels, and karst terrains, characterized by low elevation and high flood susceptibility. Meanwhile, about 73% of the total inundated area occurs within newly developed urban zones, primarily in western and southwestern Hanoi, where rapid expansion on flood-prone terrain has intensified hazards. The DPSIR analysis highlights rapid population growth, land use change, and inadequate drainage infrastructure as the main pressures driving both the frequency and extent of flooding. To our knowledge, this is the first study integrating geomorphology, Sentinel-1, and DPSIR for Hanoi, thereby providing robust evidence to support sustainable urban planning and climate-resilient development. Full article

Geographic Information Systems (GIS) are central to spatial evidence in Environmental Impact Assessment (EIA). In this review, GIS is used in a broad, integrative sense to refer to an ecosystem of geospatial technologies—such as remote sensing (RS) and GPS—where GIS serves as the core platform for managing, analyzing, and communicating spatial data throughout the EIA process. GIS plays a crucial role at each stage of EIA, from baseline data collection to spatial analysis, ecological sensitivity mapping, impact prediction, scenario simulation, and landscape connectivity assessment. These capabilities support alternatives analysis, risk communication, and decision-making in EIA. This paper synthesizes thematic evidence and presents case studies to illustrate the synergies between GIS, remote sensing, GeoAI, and multisource data fusion. It highlights operational workflows and key deliverables for EIA applications, including urban expansion, transport corridors, and protected-area management. We identify persistent challenges in data quality and standardization, interoperability, model uncertainty, and policy gaps. To address them, we propose a minimum geospatial dataset with clear metadata standards, interpretable GeoAI paired with formal sensitivity analysis, IoT–GIS pipelines for real-time monitoring and adaptive management, and the systematic inclusion of cumulative effects and climate scenarios. By linking GIS methods to typical decision points and reporting standards in EIA, this review clarifies where GIS adds value, how to quantify and communicate uncertainty, and how to align analytical outputs with regulatory requirements and stakeholder expectations. The study offers a practical framework and implementation checklist for standardized, transparent, and reproducible EIA processes, contributing to evidence-based ecological governance. Full article

Currently, an active debate is underway among the academic community, urban planners, and policymakers regarding optimal models of urban development, given that the majority of the population now resides in cities. One concept under discussion is the 15 min city, which posits that all urban residents should be able to reach key, frequently used services within a 15 min walk or cycle. Although the literature suggests numerous potential benefits, debate persists about whether such cities would be optimal from the standpoint of sustainable development objectives and residents’ quality of life. The ongoing discussion also concerns the extent to which existing cities are capable of aligning with this concept. This is directly linked to the actual spatial distribution of individual services within the city. The literature indicates a research gap arising from a shortage of robust case studies that would enable a credible assessment of the practical implementation of this idea across diverse cities, countries, and regions. This issue pertains to Poland as well as to other countries. A desirable future scenario would involve comprehensive mapping of all cities, with respect to both the spatial distribution of specific services and related domains such as the quality and coherence of linear infrastructure. This article presents an analysis of the spatial accessibility of basic urban services in the context of implementing the 15 min city concept, using the city of Koszalin (Poland) as a case study. This city was selected due to its representative character as a medium-sized urban centre, both in terms of population and area, as well as its subregional functions within Poland’s settlement structure. Koszalin also exhibits a typical spatial and functional layout characteristic of many Polish cities. In light of growing challenges related to urbanisation, climate change, and the need to promote sustainable mobility, this study focuses on evaluating access to services such as education, healthcare, retail, public transport, and green spaces. The use of Geographic Information System (GIS) tools enabled the identification of spatial variations in service accessibility across the city. The results indicate that only 11% of Koszalin’s area fully meets the assumptions of the 15 min city concept, providing pedestrians with convenient access to all key services. At the same time, 92% of the city’s area offers access to at least one essential service within a 15 min walk. Excluding forested areas not intended for development increases these values to 14% and 100%, respectively. This highlights the extent to which methodological choices in assessing pedestrian accessibility can shape analytical outcomes and the interpretations drawn from them. Moreover, given this article’s objective and the adopted analytical procedure, the assumed pedestrian walking speed is the key parameter. Accordingly, a sensitivity analysis was conducted, comparing the reference scenario (4 km/h) with alternative variants (3 and 5 km/h). This approach demonstrates the extent to which a change in a single parameter affects estimates of urban-area coverage by access to individual services reachable on foot within 15 min. The analysis reveals limited integration of urban functions at the local scale, highlighting areas in need of planning intervention. This article proposes directions for action to improve pedestrian accessibility within the city. Full article

Urban CO₂ mitigation strategies typically aim at particular zones or sectors but do not account for spatial interdependencies among different components within the city. Understanding how land uses emit within and across districts can reveal systemic leverage points for climate-resilient urban planning. This study applies a bipartite spatial network approach using high-resolution Urban Atlas land-use data and a hierarchical spatial framework for emissions and sequestration estimation. The approach links urban land uses to their emissions profiles, offering a structural view of how different areas interconnect within urban carbon dynamics, moving beyond fragmented emission accounting. Using the Reggio Calabria Functional Urban Area in Italy as a case study, the analysis identifies influential areas and emission-intensive land uses. Subsequently, using centrality metrics highlights the spatial units with strong connections to emission-dense land uses, marking them as points of intervention. Results show that although 53% of districts act as net carbon sinks, their sequestration capacity is outweighed by the intensity of a smaller group of emitter districts. Among these, five central districts (IDs 94, 82, 107, 108, and 72) emit over 500 million kg CO₂ per year, making them leverage points for systemic mitigation. The integration of bipartite spatial network and multiscale territorial analysis provides a replicable, data-driven framework for urban CO₂ mitigation. Ultimately, the study demonstrates that mapping emissions through spatial interdependencies enables planners to target interventions where localized action yields the greatest network-wide climate impact. Full article

Hydropower is the primary source of electricity in several countries in Latin America. Hydropower provides approximately 80% of Ecuador’s electricity; however, it remains highly vulnerable to climate change, resulting in uncertainties in power generation due to altered precipitation patterns, runoff, and systematic failures. Consequently, Ecuadorians are becoming increasingly reliant on diesel generators during crises, resulting in public health, safety, and economic impacts, as well as social and political disruptions. This study evaluated noise pollution in the central urban area of the city of Loja for the first time during the 2024–2025 electricity crisis in Ecuador. A Type 1 integrating sound-level meter was used to monitor noise pollution (LAeq, 10min) at 20 locations during periods of generator operation and non-operation. At each location, the number of generators, the density of commercial activities along the streets, as well as traffic and other urban characteristics, were recorded. Results revealed that the presence of generators, street width, and the number of generators significantly increased the LAeq, 10min, often exceeding the limits set by the World Health Organization and Ecuador’s environmental regulations. Frequency spectrum analysis revealed that medium frequencies increased with A-weighting, while low frequencies rose with C-weighting, suggesting potential health risks to the local population. The thematic noise map during generator inactivity showed lower noise levels, averaging around 71.5 dBA. Conversely, when the generators were operational, noise levels exceeded 79.6 dBA, indicating a significant increase in environmental noise exposure associated with their use. This highlights an urgent need to implement and expand renewable energy sources, as existing options like wind power, photovoltaic energy, and biomass are insufficient to meet community demands. Full article