Search Results (230)

To solve the present housing crisis, the Support for Access to Housing Program, in the context of PRR, mainly focuses on social housing to be built or on housing of social interest to be regenerated. To approach this problem, a research question was raised: “What is the significance of the existing cooperative housing in solving the current housing crisis?” To analyze this issue, a multiple case study was adopted, comparing a collective dwelling of cooperative promotion at controlled costs in Caselas (1980s–1990s) with Expo Urbe (2000–2007) in Parque das Nações, a symbol of the new sustainable cooperative housing, which targets a population with a higher standard of living and thus is excluded from the PRR plan. These cases revealed the discrepancy created by the Cooperative Code of 1998 and its consequences for the urban regeneration of this heritage. They show that Caselas, built in a residential urban neighborhood, is strongly attached to a community, provides good social inclusion for vulnerable groups at more affordable prices, and it is eligible for urban regeneration and reuse (for renting or buying). However, the reuse of Caselcoop’s edifices cannot compromise their cultural and residential values or threaten the individual integrity. Full article

Africa’s rapid urbanization often exceeds the capacity of governments to provide essential services and infrastructure, exacerbating structural inequalities and exposing vulnerable populations to serious health risks. This paper examines the case of Douala, Cameroon, to demonstrate that health inequities in African cities are not simply the result of urban growth but are shaped by spatial inequities, historical legacies, and systemic exclusion. Disadvantaged neighborhoods are particularly impacted, becoming epicenters of health crises. Using a mixed-methods approach combining spatial analysis, household surveys and interviews, the study identifies three key findings: (1) Healthcare services in Douala are unevenly distributed and dominated by private providers, which limits access for low-income residents. (2) Inadequate infrastructure and environmental risks in informal settlements lead to a higher disease burden and an overflow of demand into better-equipped districts, which overwhelms public health centers across the city. (3) This structural mismatch fuels widespread reliance on informal and unregulated care practices. This study positions Douala as a microcosm of broader public health challenges in rapidly urbanizing African cities. It highlights the need for integrated urban planning and health system reforms that address spatial inequalities, strengthen public health infrastructure, and prioritize equity—key principles for achieving the third Sustainable Development Goal (ensuring good health and well-being for all residents) in sub-Saharan Africa. Full article

This exploratory case study examines the alignment between GIS-based displacement models and lived experiences of residents in Salt Lake City, addressing the benefits and limitations of spatial tools in capturing urban displacement complexities. By comparing the Urban Displacement Project’s Estimated Displacement Risk (EDR) model with qualitative interviews from diverse neighborhoods, the research highlights discrepancies between predictive outputs and community narratives. The findings reveal that while GIS models effectively identify displacement hotspots, they often underestimate risks in areas with high homeownership or recent development. Conversely, resident interviews provide valuable insights into emerging displacement pressures that GIS may overlook. This study underscores the importance of integrating spatial analysis with community engagement to produce more equitable land-use planning strategies. The study contributes to urban governance and sustainable development by advocating for policies that prioritize the voices of vulnerable populations, fostering more resilient and inclusive cities. Full article

Amman’s rapid population growth and sprawling urbanization have resulted in car-centric, fragmented neighborhoods that lack social cohesion and are vulnerable to the impacts of climate change. This study reframes walkability as a climate adaptation strategy, demonstrating how pedestrian-oriented spatial planning can reduce vehicle emissions, mitigate urban heat island effects, and enhance the resilience of green infrastructure in peri-urban contexts. Using Deir Ghbar, a rapidly developing marginal area on Amman’s western edge, as a case study, we combine objective walkability metrics (street connectivity and residential and retail density) with GIS-based spatial regression analysis to examine relationships with residents’ sense of community. Employing a quantitative, correlational research design, we assess walkability using a composite objective walkability index, calculated from the land-use mix, street connectivity, retail density, and residential density. Our results reveal that higher residential density and improved street connectivity significantly strengthen social cohesion, whereas low-density zones reinforce spatial and socioeconomic disparities. Furthermore, the findings highlight the potential of targeted green infrastructure interventions, such as continuous street tree canopies and permeable pavements, to enhance pedestrian comfort and urban ecological functions. By visualizing spatial patterns and correlating built-environment attributes with community outcomes, this research provides actionable insights for policymakers and urban planners. These strategies contribute directly to several Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action), by fostering more inclusive, connected, and climate-resilient neighborhoods. Deir Ghbar emerges as a model for scalable, GIS-driven spatial planning in rural and marginal peri-urban areas throughout Jordan and similar regions facing accelerated urban transitions. By correlating walkability metrics with community outcomes, this study operationalizes SDGs 11 and 13, offering a replicable framework for climate-resilient urban planning in arid regions. Full article

Property crime is a pressing issue in maintaining social order and urban sustainability, particularly in regions marked by pronounced socioeconomic disparity. While the link between socioeconomic stress and crime is well established, regional variations in Thailand have not been fully examined. Therefore, the purpose of this research was to examine spatial patterns of property crime and identify the potential associations between property crime and socioeconomic environment across Thailand. Using nationally compiled property-crime data from official sources across all provinces of Thailand, we employed geographic information system (GIS) tools to conduct a spatial cluster analysis at the sub-national level across 76 provinces. Both global and local statistical techniques were applied to identify spatial associations between property-crime rates and neighborhood-level socioeconomic conditions. The results revealed that property-crime clusters are primarily concentrated in the south, while low-crime areas dominate parts of the north and northeast regions. To analyze the spatial dynamics of property crime, we used geospatial statistical models to investigate the influence of socioeconomic variables across provinces. We found that property-crime rates were significantly associated with monthly income, areas experiencing high levels of household debt, migrant populations, working-age populations, an uneducated labor force, and population density. Identifying associated factors and mapping geographic regions with significant spatial clusters is an effective approach for determining where issues concentrate and for deepening understanding of the underlying patterns and drivers of property crime. This study offers actionable insights for enhancing safety, resilience, and urban sustainability in Thailand’s diverse regional contexts by highlighting geographies of vulnerability. Full article

Urban mobility resilience plays a central role in sustainable urban planning discussions, especially considering the challenges of extreme events, climate change, and the increasing scarcity of fossil fuels. This study evaluates urban mobility resilience in Petrópolis (RJ), incorporating socio-spatial heterogeneity and energy vulnerability. This research fills methodological gaps in the literature by proposing a composite resilience index that integrates technical, socioeconomic, and fossil fuel dependency variables within a robust multicriteria framework. We selected eleven variables relevant to urban mobility and organized them into inference blocks. We normalized the variables using Gaussian functions, respecting their maximization or minimization characteristics. We applied the Analytic Hierarchy Process (AHP) to assign weights to the criteria and then aggregated and ranked the results using multicriteria analysis. The final index represents the adaptive capacity of urban territories facing the energy crisis, and we applied it spatially to the neighborhoods of Petrópolis. The analysis identified a significant concentration of neighborhoods with low resilience, particularly in quadrants, combining deficiencies in public transportation, high dependence on fossil fuels, and socioeconomic constraints. Factors such as limited pedestrian access, insufficient motorized public transport coverage, and a high proportion of elderly residents emerged as significant constraints on urban resilience. Intervention strategies that promote active mobility, improve accessibility, and diversify transportation modes proved essential for strengthening local resilience. The results emphasize the urgent need for public policies to reduce energy vulnerability, foster active mobility, and promote equity in access to transportation infrastructure. Full article

Firmware vulnerabilities in embedded devices have caused serious security incidents, necessitating similarity analysis of binary program instruction embeddings to identify vulnerabilities. However, existing instruction embedding methods neglect program execution semantics, resulting in accuracy limitations. Furthermore, current embedding approaches utilize independent computation across models, where the lack of standardized interaction information between models makes it difficult for embedding models to efficiently detect firmware vulnerabilities. To address these challenges, this paper proposes a firmware vulnerability detection scheme based on statistical inference and code similarity fuzzy matching analysis for resource-constrained vehicular network environments, helping to balance both accuracy and efficiency. First, through dynamic programming and neighborhood search techniques, binary code is systematically partitioned into normalized segment collections according to specific rules. The binary code is then analyzed in segments to construct semantic equivalence mappings, thereby extracting similarity metrics for function execution semantics. Subsequently, Google Protocol Buffers (ProtoBuf) is introduced as a serialization format for inter-model data transmission, serving as a “translation layer” and “bridging technology” within the firmware vulnerability detection framework. Additionally, a ProtoBuf-based certificate authentication scheme is proposed to enhance vehicular network communication reliability, improve data serialization efficiency, and increase the efficiency and accuracy of the detection model. Finally, a vehicular network simulation environment is established through secondary development on the NS-3 network simulator, and the functionality and performance of this architecture were thoroughly tested. Results demonstrate that the algorithm possesses resistance capabilities against common security threats while minimizing performance impact. Experimental results show that FirmPB delivers superior accuracy with 0.044 s inference time and 0.932 AUC, outperforming current SOTA in detection performance. Full article

Background: Suicidal ideation among adolescents remains a major public health challenge. Exposure to neighborhood violence is associated with increased risk of mental health distress and school-related vulnerabilities. This study investigates the predictors of suicidal ideation among U.S. adolescents who have witnessed neighborhood violence. Methods: Data were drawn from the 2023 Youth Risk Behavior Survey (YRBS), a nationally representative survey of high school students in the United States. A subsample of 3495 adolescents who reported witnessing neighborhood violence was analyzed. Key variables included sociodemographic characteristics, mental health symptoms, perceived school safety, and experiences of victimization. Multivariable logistic regression was used to identify factors associated with suicidal ideation, defined as seriously considering suicide in the past year. Analyses were conducted using Jamovi (version 2.6), with statistical significance set at p < 0.05. Results: The prevalence of suicidal ideation in the sample was 34.2%. Bisexual adolescents had significantly higher odds of suicidal ideation compared to heterosexual peers (OR = 2.34, p < 0.001). Depressive symptoms were the strongest predictor (OR = 7.51, p < 0.001). Both perceived lack of safety at school and differences in ethnic and population backgrounds were significant. Black and Hispanic/Latino adolescents had lower odds compared to White peers. Conclusions: Findings highlight sexual identity, depressive symptoms, school safety concerns, and ethnic and population background differences as key correlates of suicidal ideation. Culturally responsive, trauma-informed interventions are urgently needed for youth exposed to community violence. Full article

Urban growth has intensified the generation of solid waste, particularly in densely populated and vulnerable neighborhoods, leading to environmental degradation and public health risks. This study presents a multidisciplinary methodology to estimate the mass of macroplastic litter mobilized from urban surfaces into nearby watercourses during storm events. Focusing on the Villa Páez neighborhood in Cordoba, Argentina—a data-scarce and flood-prone urban basin—the approach integrates socio-environmental surveys, field observations, Google Street View analysis, and hydrologic modeling using EPA SWMM 5.2. Macroplastic accumulation on streets was estimated based on observed waste density, and its transport under varying garbage collection intervals and rainfall intensities was simulated using a conceptual pollutant model. Results indicate that plastic mobilization increases substantially with storm intensity and accumulation duration, with the majority of macroplastic mass transported during high-return-period rainfall events. The study highlights the need for frequent waste collection, improved monitoring in vulnerable urban areas, and scenario-based modeling tools to support more effective waste and stormwater management. Full article

Agricultural terraces are critical landscape elements that promote sustainable rural development by enhancing water retention, mitigating soil erosion, and conserving cultural heritage. In northeastern Türkiye, particularly in the mountainous Erikli neighborhood of Uzundere, traditional terraces face growing threats due to land abandonment, topographic fragility, and socio–economic decline. This study applies a spatial–functional assessment framework that integrates UAV–based photogrammetry, GIS analysis, terrain modeling, and DBSCAN clustering to evaluate terrace conditions. UAVs provided high–resolution topographic data, which supported the delineation of terrace boundaries and morphometric classification using an adapted ALPTER model. A combined Terrace Density Index (TDI) and Functional Status Index (FSI) approach identified zones where terraces are structurally intact but functionally degraded. Results indicate that 76.4% of terraces fall within the meso and macro classes, yet 58% show partial or complete degradation. Cohesive terrace clusters are located near settlements, while isolated units in peripheral zones display higher vulnerability. This integrated approach demonstrates the analytical potential of drone–supported spatial diagnostics for monitoring landscape degradation. The method is scalable and adaptable to other terraced regions, offering practical tools for site–specific land use planning, heritage conservation, and resilience–based restoration strategies. Full article

This study integrates socio-demographic factors and local sustainability indicators to assess their implications for public health and social vulnerability in the Henequén neighborhood of Cartagena, Colombia. This historically marginalized community, primarily composed of women and displaced families, faces chronic exposure to environmental contaminants due to its past as a municipal landfill. Poor housing conditions, overcrowding, and inadequate access to water and sanitation services exacerbate health risks. Additionally, low educational attainment and limited economic opportunities contribute to cycles of poverty and illicit activities, disproportionately affecting children’s development. Using a cross-sectional and correlational approach, the study identifies key variables, such as housing conditions, access to basic services, and marital status, that shape social vulnerability. The findings are analyzed in the context of the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being), SDG 6 (Clean Water and Sanitation), and SDG 11 (Sustainable Cities and Communities). The study highlights critical gaps in sustainability efforts and provides a framework for assessing local progress toward achieving these global development objectives. Full article

Practical large-scale multiple unmanned aerial vehicle (multi-UAV) networks are susceptible to multiple potential points of vulnerability, such as hardware failures or adversarial attacks. Existing resilient multi-dimensional coordination control algorithms in multi-UAV networks are rather costly in the computation of a safe point and rely on an assumption of the maximum number of adversarial nodes in the multi-UAV network or neighborhood. In this paper, a dynamic trusted convex hull method is proposed to filter received states in multi-dimensional space without requiring assumptions about the maximum adversaries. Based on the proposed method, a distributed local control protocol is designed with lower computational complexity and higher tolerance of adversarial nodes. Sufficient and necessary graph-theoretic conditions are obtained to achieve resilient multi-dimensional consensus and containment control despite adversarial nodes’ behaviors. The theoretical results are validated through simulations. Full article

Climate-amplified extreme heat events are particularly dangerous for city dwellers. Nature-based solutions such as urban greening may serve as an effective preventative strategy against extreme heat. Driven by historical injustices such as redlining, disadvantaged communities often face limited green space and a heightened risk of vulnerability to extreme heat in urban environments. This paper investigates community engagement strategies for heat-vulnerable community participation in urban greening research as a part of a broader transdisciplinary environmental research praxis focused on multistakeholder co-creation. We conducted semi-structured interviews with community leaders in heat-vulnerable neighborhoods in New York City to explore community co-creation in the design and implementation of tree planting, and compared these themes with interviews with urban tree professionals and other community groups. Overall, the participants agreed on broad themes of environmental justice, intergenerational engagement, community building, and socioecological relationships, although community leaders differed in both a greater emphasis of experiential knowledge and reduced focus on volunteer community stewardship. The findings inform our research process and associated community engagement, including building online resources and addressing community-specific concerns during the research process. We conclude by recommending future steps for facilitating multistakeholder conversations to build inclusive and equitable urban greening heat-adaptive strategies. Full article

Analyzing the population’s access to ecosystem services offered by urban greening constitutes a measure of environmental justice, as it directly affects the quality of life and health of the population living in cities. This article is committed to proposing a geoenvironmental model in a geographic information system (GIS), envisaged to estimate the share of urban forests and green spaces in territorial planning units (TPUs), corresponding to neighborhoods of a pilot city, using high-spatial-resolution images of the China–Brazil Earth Resources Satellite (CBERS-4A) and the normalized difference vegetation index (NDVI). These data were combined by means of a Boolean analysis with social vulnerability indicators assessed from census data related to income, education, housing, and sanitation. This model ultimately aims to identify priority areas for urban afforestation in the context of environmental justice and is thus targeted to improve the inhabitants’ quality of life. The municipality of Goiânia, the capital of Goiás state, located in the Brazilian Central–West Region, was chosen as the study area for this experiment. Goiânia presents 19.5% of its urban territory (82.36 km²) covered by vegetation. The analyses indicate an inequity in the distribution of urban forest patches and green areas in this town, where 7.8% of the total TPUs have low priority, 28.2% have moderate to low priority, 42.2% have moderate to high priority, and 21.8% have high priority for urban afforestation. This urban greening imbalance is particularly observed in its most urbanized central nuclei, associated with a peripheralization of social vulnerability. These findings are meant to support initiatives towards sound territorial planning processes designed to promote more sustainable and equal development to ensure environmental justice and combat climate change. Full article

Urban vulnerability creates structural imbalances, leading to unsafe conditions and urban decline. One of the key root causes of urban vulnerability is significant changes in urban layout morphology, which significantly influences the determination of accessibility potential, causing some areas to grow while others decline. This study aims to examine the morphological structural factors that influenced physical vulnerability, with a focus on commercial buildings, which were affected by the transformation of urban structure resulting from the layout and connectivity of the transportation network at the global, local, and community levels, depending on their location; these factors contribute to spatial vulnerability in varying degrees. This study applied an indicator-based quantitative research methodology, constructing a Physical Vulnerability Index (PVI) by using Principal Component Analysis (PCA) to create new factors or components and compare physical vulnerability levels across different areas. The research findings found that the most influential morphological structural factor on physical vulnerability was micro-level morphology, primarily due to the relationship between the configuration of space and the level of usage popularity. The second most influential factor is macro-level morphology, resulting from the relationship between the accessibility potential of urban-level and neighborhood-level transportation networks. Full article