Search Results (167)

Urban regeneration projects offer critical insights into contemporary urban land-use planning, particularly through high-profile interventions that reflect distinct planning visions and strategic approaches. This study examines two major regeneration initiatives in Athens: the redevelopment of Faliro Bay along the southern waterfront and the regeneration of Akademia Platonos in the northwest. Faliro Bay, designated as a metropolitan hub in the revised Athens Master Plan, is currently the focus of a regeneration project aiming to transform a predominantly state-owned area—including former Olympic facilities and a degraded waterfront—into a major cultural and recreational destination, combining extensive green public spaces with landmark developments through public–private collaboration. In contrast, the Akademia Platonos project is a public-led intervention within a dense urban setting, encompassing an archaeological site, former industrial premises, and mixed-use neighborhoods. Its objective is to reorganize land uses, reduce building intensity, and enhance open space and public amenities. These cases are comparatively assessed in terms of strategic orientation, governance structure, planning practices, and outcomes; this analysis highlights divergent planning trajectories and underscores the institutional, spatial, and governance challenges shaping the implementation of urban regeneration policies in contemporary Athens. Full article

Urban regeneration is critical for addressing contemporary urban challenges, yet its complexity arises from the dynamic interactions among different participants’ preference and strategic behavior factors, making it a multi-agent system driven by strategic behaviors. This study, based on a Chinese urban regeneration case, develops a dynamic evolutionary game model for industrial park renewal to explore the strategic interactions among three key stakeholders: government, social capital, and property owners. The findings reveal three insights: Firstly, the probabilities of social capital participation and property owner cooperation exhibit opposing trends, highlighting conflicting incentives. Secondly, social capital participation follows an inverted U-shaped trajectory with investment ratios, reflecting a strategic trade-off between risk and control; further robustness checks incorporating time delays and phased investments confirm that the curvature of this trajectory is highly sensitive to the project’s development cycle. Thirdly, lower land repayment costs, higher rental income, greater project returns, and a higher profit-sharing ratio promote cooperative strategies among property owners, though this effect remains marginal. The study further demonstrates that non-cooperative behavior among property owners results in a single evolutionary stable strategy (1, 1, 0) where the government repurchases land property rights, and social capital acquires these rights for redevelopment. The findings suggest that this conclusion applies specifically to industrial park renewal in urban centers held by property owners in cities, where it is government-led facilitation, with property owners exiting and social capital entering simultaneously, thereby ensuring alignment of multi-agent strategic behavior in China. Full article

In Ulaanbaatar, Mongolia, a 2023 law allowing compulsory land expropriation for Ger area redevelopment once 70% of residents consent has raised concerns about procedural legitimacy and social acceptability. This study examines determinants of residents’ acceptance of the policy using a survey of 407 adult Ger area residents. Drawing on procedural and distributive justice, government trust, and policy acceptance theories, we estimated a structural equation model and assessed robustness using 5000 bootstrap resamples and 95% confidence intervals (CIs). Trust in government was low (mean = 2.85), whereas policy acceptance was neutral to positive (mean = 3.20). Procedural justice showed the strongest positive direct association with acceptance (b = 0.401, 95% CI [0.135, 0.676]), while housing satisfaction was negatively associated with acceptance (b = −0.112, 95% CI [−0.207, −0.017]). Government trust was not significantly related to acceptance (b = 0.105, 95% CI [−0.025, 0.235]), and the indirect effect of procedural justice via trust was not significant (CI included zero). Participation was negatively associated with acceptance (b = −0.156, 95% CI [−0.268, −0.032]), contrary to the hypothesized positive relationship. These findings suggest that, in transitional contexts, perceived process fairness may be more consequential for policy acceptance than generalized institutional trust. Full article

Waterfront brownfield urban public parks (WBUPPs) are complex regeneration projects that require comprehensive assessment of environmental remediation, climate resilience, urban connectivity, and social well-being. This study proposes a structured GIS-based spatial analysis protocol that operationalizes key attributes of brownfields, waterfronts, public parks, and sustainability, with the aim of examining how digital tools can support WBUPP planning processes. Using free and open source resources and datasets (QGIS and OpenStreetMap), the approach produces eight core thematic maps that spatially organize 39 of 50 criteria identified from the literature and classified under economic, environmental, and social sustainability dimensions. This mapping protocol streamlines navigation for planners through complex datasets and offers researchers a foundation for thematic spatial analyses aligned with these literature-based criteria. The protocol is illustrated with Brooklyn Bridge Park in New York City—an 85-acre waterfront redevelopment that demonstrates heritage conservation, ecological restoration, and financial viability. The results highlight identifiable spatial patterns such as dual zones (urban buffer and recreation), winding pathways, and clustered amenities. At the same time, the analysis underscores the importance of data validation, as inconsistencies in volunteered geographic information require cross-referencing with multiple sources and field verification. The analysis shows that WBUPPs require tailored approaches that integrate land–water mobility, heritage adaptation, nature-based solutions, and equitable service distribution. This criteria-driven protocol offers adaptable guidance for future waterfront brownfield regeneration, while emphasizing that digitalization enhances the process, but it cannot replace hybrid analytical methods that combine quantitative spatial analysis with qualitative evaluations. Full article

As China’s urbanization transitions from incremental expansion to stock-based renewal, industrial land redevelopment has become a key pathway for promoting high-quality urban development. However, existing studies mostly assess redevelopment potential from a single dimension and lack a systematic framework integrating ecological function (E), spatial structure (S), economic conditions (C), and building foundations (B). Taking the built-up area of Xi’an as a case study, this study adopts a functional–structural optimization perspective and constructs a four-dimensional ESCB assessment framework based on 13 indicators covering ecological function, spatial structure, economic conditions, and building foundations. GIS-based spatial quantification, MiniBatchKMeans clustering, and the XGBoost algorithm were employed to identify the redevelopment potential of industrial land, while SHAP analysis was used to interpret indicator contributions and determine the core influencing factors. The results show that industrial land in the study area can be classified into four types: vitality–density dominant, transport–scale coordinated, scale–facility lagging, and topography–vegetation sensitive, with significant differences in spatial distribution and indicator characteristics. The interpretable machine learning model further identifies road network density, block-level economic vitality, and land-use suitability as the three principal drivers of redevelopment potential, among which road network density plays the most critical role. By integrating clustering analysis with interpretable machine learning, the ESCB framework effectively reveals the synergies and trade-offs among multidimensional indicators and provides differentiated and precise support for industrial land redevelopment strategies. Full article

Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), is transforming the modeling of complex spatiotemporal urban processes such as urban growth, sprawl, shrinkage, redevelopment, and Land Use/Land Cover Change (LULCC). However, despite rapid methodological innovation, applications remain fragmented, and there is limited synthesis of how AI-based models complement, extend, or supersede conventional approaches. This study addresses this gap through a systematic review of 6356 records, from which 120 articles were selected for detailed analysis. It investigates: (i) how ML/DL techniques are embedded within spatiotemporal modeling frameworks; (ii) their use in simulating urbanization dynamics and land-use (LU) transitions; (iii) methodological and performance gains relative to traditional statistical and rule-based models; and (iv) emerging research frontiers and limitations. The review shows that LULCC dominates current applications, with Artificial Neural Networks (ANNs) as the most prevalent ML method, increasingly complemented by DL architectures. Across cases, AI is primarily used to learn non-linear transition dynamics, represent spatial and temporal dependencies, identify influential drivers, and improve classification performance and computational efficiency. Building on these insights, the paper synthesizes the roles of AI in spatiotemporal urban modeling and outlines forward-looking research directions to support more robust, transparent, and policy-relevant applications for urban sustainability. Full article

Urban districts along major rivers are undergoing rapid transformation, yet long-term evidence on how redevelopment reshapes land cover and vegetation structure remains limited in post-socialist cities. This study examines the spatio-temporal evolution of land use and land cover (LULC) and vegetation dynamics along the Sava River corridor in Belgrade from 1990 to 2024. CORINE Land Cover (CLC) datasets were combined with Landsat-derived NDVI and MSAVI time series, while high-resolution Esri Wayback imagery was used for visual interpretation and qualitative corroboration of the detected land-cover and vegetation patterns. Beyond conventional NDVI/LULC assessments, the study integrates multi-decadal spectral trends with functional vegetation structure classification to evaluate canopy continuity and ecological configuration under contrasting redevelopment models. Results reveal a pronounced divergence between the two riverbanks. The left bank (New Belgrade) maintains stable land-cover composition and consistently higher NDVI and MSAVI values, indicating preserved green infrastructure and sustained canopy continuity. In contrast, the right bank (Belgrade Waterfront) experienced substantial land-cover conversion after 2006, with a statistically significant decline in vegetation greenness (NDVI −0.020 dec⁻¹, p < 0.001) and a marked increase in impervious surfaces. MSAVI-based functional classes indicate a shift from mixed low vegetation to predominantly sealed land, while tree canopy remained persistently low throughout redevelopment. The findings demonstrate measurable ecological simplification and canopy loss, even where nominal green areas remain present. By providing a rare multi-decadal, spatially explicit comparison of two contrasting planning paradigms within the same river corridor, the study contributes new empirical evidence on how governance and redevelopment models shape riparian ecological trajectories and sustainable urbanism in post-socialist cities. Strengthening blue-green infrastructure and restoring native riparian vegetation are essential for enhancing climate resilience and ensuring long-term riverfront sustainability. Full article

Urban soil contamination poses persistent risks to redevelopment, public health, and ecological restoration, yet actionable evidence is scattered across site investigation reports, monitoring databases, and regulatory documents. Existing decision-support tools often depend on manual searches and provide limited structured reasoning. This study develops a domain knowledge graph (KG) and a KG-powered question-answering (KBQA) system for urban soil management to organize multi-source evidence and deliver precise, auditable answers to parcel- and pollutant-specific queries. The approach (1) defines an urban soil ontology covering parcels, land uses, pollutants, measurements, pathways, and regulatory thresholds; (2) extracts and links entities and relations from textual and tabular sources; (3) constructs a graph database with provenance; and (4) implements a KBQA pipeline that maps natural-language questions to constrained graph queries and verbalizes results with citations. The resulting system supports source identification, land-use-specific exceedance checks, affected-parcel listing, and remediation reference retrieval. Experiments on a curated QA set and a South China case study show higher answer accuracy and lower latency than text-only baselines, while consistently returning traceable evidence and reducing cross-document lookup effort. Compared to text-only RAG baselines, the KG-powered system achieved a 0.14 improvement in Exact Match scores (e.g., 0.81 vs. 0.58 for Threshold tasks) and maintained a competitive median latency of 0.75 s. The pipeline utilizes a 13B-parameter instruction-tuned LLM. The ontology, schema, benchmark QA sets, and sample queries are publicly released to support transfer to other regions. Full article

Urban areas across Europe are undergoing rapid morphological transformations driven by densification, redevelopment, and infrastructure expansion. Monitoring these urban changes requires operational, harmonized, and reproducible approaches grounded in Earth Observation. This study presents a Copernicus use case demonstrating how the High-Resolution Layer Imperviousness Change (2015–2018) and Urban Atlas datasets can be integrated with the Guidos Toolbox (GTB) to quantify structural urban change across six metropolitan areas (Milan, Sofia, Riga, Warsaw, Viseu, Santander). Morphological Spatial Pattern Analysis (MSPA) and entropy-based indicators were applied to characterize land take, fragmentation, compaction, and internal reorganization of impervious surfaces. The combined framework captured both configurational morphology and spatial disorder, revealing divergent development patterns: pronounced heterogeneity and fragmentation in Sofia, stabilization or compact growth in Milan, Warsaw, and Santander, controlled densification in Riga, and localized intensification without outward expansion in Viseu. All analyses rely on openly accessible Copernicus data and open-source tools, ensuring full reproducibility and transferability. Outputs were disseminated through a FAIR-compliant geoportal developed within a Copernicus FPCUP project, supporting transparency and reuse. The findings underscore the value of Copernicus services for operational urban monitoring and provide a scalable methodology to support European land-use policies, including the Zero Net Land Take 2050 target and the EU Soil Strategy. Full article

In an era of rapid urbanisation and climate challenges, understanding how urban land patterns contribute to resilience is crucial for sustainable development. This theoretical review introduces a novel framework positing that greater heterogeneity in plot sizes and land uses enhances urban resilience by promoting the long-term preservation of built environments, multifunctional spaces, and socio-cultural adaptability. Drawing on urban morphology, assemblage theory, and resilience science, we argue that fragmented ownership in small-plot fabrics acts as a barrier to large-scale redevelopment, fostering diversity that buffers against shocks. Through comparative case studies of Venice (Italy), Tokyo (Japan), Hong Kong, Mexico City (Mexico), and York (UK), we illustrate how historical small-plot subdivisions have endured centuries, supporting ecological, economic, and social sustainability. The analysis reveals common patterns: ownership fragmentation preserves fine-grained urban forms, enabling adaptive reuse (exaptation) and inclusivity. The five case studies serve an illustrative function, demonstrating how the theoretical linkages between plot heterogeneity, institutional friction, incremental transformation, and long-term resilience outcomes can plausibly operate in real-world historic urban fabrics. This paper addresses a gap in the literature by synthesising plot-level heterogeneity with broader resilience outcomes, offering policy implications for protecting such fabrics amid global urbanisation pressures. The findings align with land system science, emphasising multifunctionality for regenerative urbanism. Full article

This study examines the ripple effects of parkification, the transformation of post-industrial landscapes into public parks and green infrastructure, in Greenville at the Upper State region of South Carolina. As many Southern mill towns contend with industrial decline, environmental degradation, and complex land-use legacies, parkification has emerged as a pragmatic response to constraint rather than a conventional redevelopment strategy. Framed as a process rather than an isolated design outcome, parkification is understood here as a generative mechanism that produces cumulative spatial, ecological, and institutional change beyond individual project boundaries. Using a mixed-methods approach that integrates spatial and temporal mapping, archival research, site analysis, and semi-structured interviews with key stakeholders and decision-makers, this study traces how parkification unfolds across time and scale. Three interconnected case studies in Greenville, Falls Park on the Reedy, Conestee Nature Preserve, and the Swamp Rabbit Trail, are examined to address how post-industrial parkification contributes to greenway network formation and broader urban–regional transformation in the American South. The findings reveal that parkification consistently emerged from conditions of environmental constraint, including contamination, flooding, infrastructural legacies, and limited redevelopment feasibility. Early parkification projects functioned as generative landscape nodes that catalyzed the expansion of green space and connectivity rather than remaining isolated amenities. By establishing visible, accessible, and publicly valued landscapes, these projects enabled the extension of trails, river corridors, and preserved infrastructures, contributing to the formation of an interconnected regional greenway system. Institutional alignment among civic organizations, public agencies, and landscape professionals further supported the scaling and replication of parkification. Together, these findings position parkification as a process-based landscape strategy capable of driving the spread of green areas and long-term urban connectivity in post-industrial regions. Full article

Soil monitoring is increasingly important for environmental sustainability and biodiversity protection, as urbanization and industrial development expose fertile land to pollution risks. Soil quality can be assessed through physical–chemical parameters and by analyzing land use evolution, highlighting the need for integrated procedures that jointly address land use transitions and soil health. This study assesses temporal soil changes (2004–2019) in an area affected by impactful industrial activities (Tito Scalo, Southern Italy), alongside major land use transformations. We explore the potential of a procedure based on a combination of standard techniques: analysis of land use/cover changes, magnetic susceptibility measurements from two field surveys (2004 and 2019) as a proxy for heavy metal concentrations, and ²²⁶Ra soil concentration measurements, proving to be a decisive factor in better interpreting the evolution of magnetic susceptibility values. Results show that, despite increased industrial activities and expanded sealed areas, magnetic susceptibility values decrease in the second survey. This suggests that policy measures, including temporary suspension of certain industrial activities and remediation efforts, positively influenced environmental quality. The proposed procedure is low-cost, time-efficient, and independent of local geological, bioclimatic, or socio-economic conditions, making it suitable for monitoring areas under high anthropogenic pressure and for evaluating the effectiveness of remediation and recovery strategies supporting mitigation or remediation actions and enabling functional redevelopment of remediated sites. Full article

Land use change driven by accelerated urbanization in Mongolia has precipitated significant degradation of urban riverine ecosystems over the past two decades. This study investigates hydrological transformations in the Selbe River Catchment of Ulaanbaatar, a cold semi-arid urban system undergoing intensive densification. Using the Site-scale Urban Water Mass Balance Assessment (SUWMBA) framework, we quantified water cycle dynamics across four temporal intervals (2008, 2010, 2018, and 2023), capturing shifts in surface runoff, infiltration, and evapotranspiration associated with land use transitions. Calibration and validation employed discharge records from the Selbe-Dambadarjaa gauging station. Results show that total inflows increased from 223 to 312 mm between 2008 and 2023, driven by a more than twentyfold rise in imported water (from 1 to 22 mm). Evapotranspiration declined by roughly one-third, while infiltration displayed a threshold-type non-linear response—rising sharply between 2010 and 2018 before decreasing again in 2023 as imperviousness intensified. Model performance weakened after 2018, underscoring the limitations of conventional hydrological frameworks in rapidly urbanizing contexts. A redevelopment scenario for the Selbe Sub-Center, aligned with the Ulaanbaatar City Master Plan 2040, projected substantially reduced evapotranspiration (132 mm) and markedly increased stormwater runoff (270 mm), reflecting expanded impervious cover and diminished vegetation. Imported water and wastewater flows (each 386 mm) also increased due to full connection to centralized supply and sewerage infrastructure, indicating a shift toward engineered water pathways and reduced hydrological connectivity to the Selbe River. These findings highlight the urgency of water-sensitive urban design and provide evidence directly informing Mongolia’s 2040 Urban Master Plan and decentralization strategy. The study establishes methodological precedent for applying SUWMBA to cold, semi-arid catchments and contributes quantitative insights for integrated land–water management policies. Full article

As former chemical sites, especially retired pesticide plants, the redevelopment of “brownfield” land imposes urgent demands for detailed environmental investigation and remediation. Addressing the current limitations in pollution characterization, which often remain confined to two-dimensional representations and lack research on the vertical migration mechanisms of heavy metals and their integration with three-dimensional remediation and management strategies, this study focuses on a typical retired pesticide plant site in Southeastern Zhejiang, China. Through systematic analysis of 916 soil borehole samples collected from 92 sampling points, the study integrates three-dimensional visualization technology and three-dimensional ordinary kriging interpolation to establish a high-precision three-dimensional characterization system covering stratigraphy, pollution plumes, and composite risks. The findings reveal that the As and Ni pollution plumes have volumes of 5.35 × 10⁴ m³ and 2.78 × 10⁵ m³, respectively. Furthermore, As and Ni exhibit significant vertical migration capabilities within sandy and silty soil layers, while elements such as Hg, Cd, and Pb are primarily concentrated in the surface fill layer. By combining three-dimensional risk modeling based on the single-factor pollution index, Nemerow comprehensive index, and potential ecological risk index, the study precisely classifies the site into four graded zones: safe use zone, basically safe use zone, low-risk control zone, and high-risk control zone. This approach enables the visualization and quantification of pollution levels. The research constructs a comprehensive methodological framework that extends from three-dimensional pollution characterization to zonal management decision-making, providing scientific evidence and technical support for the precise remediation and sustainable redevelopment of similar retired industrial sites. Full article

Chinese local governments have long financed public services through land-sale revenues. The shift from selling undeveloped land to redeveloping existing urban areas has disrupted this traditional financing model, exposing a critical tension between the pursuit of immediate revenue and the assurance of long-term fiscal health. The continued dependence on land-based finance has led many local governments to overlook long-term public service obligations and the long-term operating deficits associated with intensive urban development. Thus, by examining the relationship between the development rights allocation and the sustainable fiscal capacity of the government, the study evaluates both short-term revenue generation and long-term expenditure commitments in urban redevelopment contexts. However, existing research has yet to provide actionable tools to reconcile this structural mismatch between short-term revenues and long-term liabilities. We employ a comprehensive analytical framework that integrates fiscal impact modeling with the optimization of development rights allocation. Based on this framework, we construct a quantitative, dual-period fiscal balance model using mathematical programming to analyze various combinations of land development rights supply strategies for achieving fiscal equilibrium. Our results identify multiple feasible supply combinations that can maintain fiscal balance while supporting sustainable urban development. The findings demonstrate that strategic development rights allocation functions as an effective tool for balancing short-term revenue needs with long-term obligations in local land finance systems. Our study contributes to establishing a sustainable land finance framework, particularly for jurisdictions lacking comprehensive land value capture mechanisms. The proposed approach offers an alternative to traditional land rights transfer models and provides guidance for avoiding long-term fiscal distress caused by excessive land transfer. The framework supports more sustainable urban redevelopment financing while maintaining fiscal responsibility across temporal horizons. Full article