Search Results (880)

Active mobility in peri-urban areas is influenced by sprawl, limited public transportation, and reliance on private vehicles. This study redefines active mobility in peri-urban and low-density contexts from a territorial perspective and reframes micro-hubs as socially oriented, network-integrated elements rather than scaled-down urban hubs. This study adopts a qualitative, theory-driven methodology combining a multidisciplinary review of the active mobility concept with thematic analysis to identify mobility hub characteristics, followed by analytical synthesis, the classification of mobility hub types, and a set of social indicators for analyzing their performance. These methods are used to develop a framework for understanding micro-hubs as socio-spatial components of active mobility networks. Results indicate that a network of minor roads and micro-hubs can support shifts toward active mobility when aligned with daily mobility patterns and supported by multi-level governance. This study conceptualizes micro-hubs as socio-spatial nodes embedded within dispersed mobility networks and, drawing on the Veneto region as an analytical context, employs an existing typological classification—network, welfare, and civic—to interpret their roles in shaping a context-sensitive framework for active mobility in peri-urban and low-density areas. Micro-hubs become socially integrated spaces that may contribute to strategies for reducing car dependency while providing transferable policy-oriented actions for similar peri-urban and low-density areas. Full article

This research presents a comprehensive spatial–temporal analysis of urban form and growth in Charlotte and Mecklenburg County, North Carolina, USA, from 1900 to 2017 at the land parcel level. Employing a data fusion framework, we integrate diverse datasets—including historical cadastral records, census data, remote sensing imagery, and infrastructure maps—to examine urban morphology through Euclidean and fractal geometries. Urban growth was reconstructed and visualized by decade and cumulatively, revealing dynamic patterns of expansion, densification, and fragmentation. Using scatterplot matrices and the Hausdorff box-counting algorithm, we quantified urban form across major land use types and temporal intervals. The fusion of socio-physical variables with mathematical functions enabled multi-scale modeling of urban transitions, aligning spatial, temporal, and thematic dimensions. Key findings include: (1) multidirectional spatial expansion resulting in a sprawling urban footprint at different rates over 117 years; (2) exponential growth between 1950 and 2000 with slower rates before and after manifesting a classic S-curve urban development by Northam; (3) a pivotal moment in 1993 when urbanized and rural lands reached parity, reflecting balanced urbanization in terms of population and land area for cities and rural areas for Mecklenburg; and (4) consistent quantitative relationships—linear, polynomial, exponential, logarithmic, and proportional—between urban form and growth metrics. This study’s novelty lies in its integrated spatial–temporal framework not only for combining both Euclidean and fractal geometric analyses with fused multi-source data to uncover the evolving structure of urban landscapes, but also for offering valuable insights into efficient land uses to assess equitable land and population dynamics, all aiming to achieve a good understanding of and sound policies for Charlotte, Mecklenburg and beyond. Full article

This research examines how the relationship between cities and rural areas has evolved in light of the profound transformation affecting rural areas of high landscape value, which has been driven by the expansion opportunities granted to the real estate sector by urban planning regulations. The role of the landscape dimension in interpreting the relationship between territorial wealth and landscape value is considered, based on the convergence of two complementary disciplinary perspectives on territory: land planning and valuation science. Against this backdrop, and with a view to containing the progressive contamination of rural and agricultural heritage by the real estate sector, this study proposes a structured observation, valuation, interpretation, and regulatory tool to support the development of territorial planning in areas significantly characterized in terms of rural landscape value. The proposed tool is based on evidence regarding the phenomenon of building expansion in the agricultural territory of a municipality in southeastern Sicily, where favorable conditions for the development of the building sector exist, such as the vastness of the municipal territory and extensive farming as the mainstay of agricultural activity. This wider sub-regional area has also received attention due to the over-tourism phenomenon that has occurred in its cities of art. The evaluation approach experienced is a value-based representation of the evolution of this process over three observation periods: 2000, 2007, and 2012, relating the quantitative observation of the building expansion to the connected qualitative impact on rural landscape. It is the result of coordinating a large set of data in a hierarchical model of indices that converge to construct a synthetic index of rural landscape resilience. This achievement is based on the linguistic progression of “lexicon”, “semantics”, “syntax”, and “pragmatics”, each of which robustly supports “observation”, “valuation”, “interpretation”, and “planning”, respectively. The final stage is based on the convergence of explanatory indices, which are developed by coordinating evidence and assessments (factual and value judgements). This stage enables the proposal of a constraints system that supports a modus vivendi between the interests of the real estate sector and the values of the rural landscape in such a rich and fragile area. Full article

SDG Indicator 11.3.1, defined as the ratio of land consumption rate (LCR) to population growth rate (PGR), is widely used to assess the efficiency of urban land use. However, its applicability becomes increasingly uncertain in regions characterized by population decline, dispersed settlement structures, and mixed urban–rural land systems. This study examines the applicability and interpretive limitations of SDG Indicator 11.3.1 in Yunlin and Chiayi, two non-metropolitan agricultural prefectures in Taiwan, over 2010–2025. Using county-level population data, GHSL-based built-up area estimates, and supplementary land-use and household statistics, it calculates LCR, PGR, and LCRPGR. The results are then interpreted with supplementary indicators, including per capita built-up area (PBUA), absolute built-up area change (∆Urb), and population density within built-up areas (DBU). The results show that both prefectures experienced continued built-up expansion despite population decline, resulting in negative LCRPGR values at the prefecture level and predominantly negative values at the county level. When interpreted together with rising PBUA and declining DBU, these results indicate a process of land dilution associated with diseconomies of density and shrinkage-related sprawl, rather than compact or efficient spatial adjustment. The findings suggest that negative LCRPGR values in shrinking regions should not be interpreted as evidence of efficient land use. Instead, SDG Indicator 11.3.1 should be treated as a diagnostic starting point whose interpretation requires supplementary indicators and territorial context. By focusing on non-metropolitan agricultural prefectures, this study extends the discussion of SDG Indicator 11.3.1 beyond rapidly growing metropolitan areas and demonstrates the need for a more context-sensitive framework for evaluating land-use efficiency in low-growth and shrinking regions. Full article

Urban expansion is a major cause of the loss of fertile soil, biodiversity and ecosystem services at the rural–urban fringe. Different patterns of urban development need to be considered to protect and integrate a green space that supports these functions. The Compact City has become the paradigmatic counterpoint to urban sprawl, but many critics highlight the challenges of integrating green space within the densifying city, as well as protecting green space outside the city. This research uses a qualitative case study to explore perspectives on the protection and integration of green space at the rural–urban fringe. Using theorisations of urban spatial form to interpret public submissions and semi-structured interviews, four city ideals are conceptualised: Arcadian City, Compact Green City, Neoliberal City, and Biophilic City. While there is no consensus on a preferred model, pathways towards the protection and integration of green space for food production and ecological function are explored. Full article

Efficient storm drainage systems (SDSs) play a pivotal role in sustainable urban development. In arid regions, urban SDS often underperform during prolonged dry periods, leaving them inoperable due to sediment buildup and clogging from the intrusion of sprawling waste. Municipalities either rely on emergency response to flooding complaints or inspect storm sewers individually to handle flash floods and conserve high-value rainwater. The present study developed a risk-based decision-analysis framework for resource-efficient inspection and maintenance (I&M) planning of SDS to prioritize geographically clustered sub-zones. The study applied the framework to a case study of three urban zones with varying population densities and land use distributions in Buraydah, Qassim, Saudi Arabia. The framework integrates fuzzy synthetic evaluation (FSE) to address data limitations and subjective expert knowledge, with geographic information system (GIS)-based spatial analysis to assess three risk factors: likelihood, consequences, and detectability of sewer clogging potential. In addition to traditional likelihood-based evaluation of the susceptibility of smaller sewers to sediment accumulation due to performance anomalies, the consequence analysis augmented the process by considering land-use characteristics, exemplified by commercial areas exhibiting higher socio-economic losses than open spaces that buffer excess runoff. The detectability factor consolidated the decision analysis by incorporating the impacts of past delayed inspections, deep manholes, and scattered construction-related waste on clogging potential. The analysis identified sub-zones with aged sewers, deep manholes, long-awaited inspections, and high population densities, resulting in a high risk. GIS maps showing distinct impacts of the three factors on overall flood risk facilitate municipalities facing unique urban flooding challenges arising from sediment accumulation during long dry periods, followed by short-duration, high-intensity rainfall. Full article

Since the 1950s, Türkiye has experienced rapid urbanization and urban expansion followed by continuous planning initiatives, yet these efforts have resulted in significant land degradation and unsustainable urban sprawl. As a remedy, legislators and administrations are increasingly turning to the use of transferable development rights (TDRs), which have arisen as an innovative land readjustment tool and have recently been incorporated into the spatial planning system. This paper examines the effectiveness of TDRs by analyzing the legislative framework and operational rationale of the Turkish model through a hypothetical scenario, while also considering the institutional restrictions that could limit its usefulness as a sustainable planning instrument. By contrasting the scenario model with the framework recently developed through legal reform, this study employs the success factors of TDRs from the literature to assess the effectiveness of the tool integrated into the spatial planning system. Since the new legislation that forms the basis of the TDR model was passed in late 2024, empirical data on completed transactions is currently unavailable, and hence, the analysis used a hypothetical what-if-case scenario model in the local context, the Muratbey-Torbalı district of Izmir. To clarify the rationale behind incorporating the TDR into the planning system, we will first examine its conceptual development within the national legislation, followed by a critical evaluation of the TDR model as established by the recent amendment. Secondly, the study will present a hypothetical TDR model that incorporates the essential components ex-ante and offer guidance for conducting a market-based evaluation of TDRs, considering factors influencing agricultural market values and related standards. The findings demonstrate that there is a lack of legal clarity that stresses the program’s holistic design with sending and receiving locations or TDR-allocation rates. The implementation regulation is challenging to ascertain how transfers impact land use justice, social benefit, and the public interest. Full article

This study investigates peri-urban land management in Uttar Pradesh through a comparative analysis of Varanasi, Kanpur, and Prayagraj, focusing on the gap between planned frameworks and actual urban growth. As rapidly expanding Tier-II cities, they represent critical sites where formal planning intersects with complex peri-urban transformations. The study employs a mixed-method approach, combining GIS-based master plan conformance analysis using Effective Boundary Control (EBC) with semi-structured expert interviews. This integration enables both spatial measurement of urban expansion and interpretive understanding of underlying governance and institutional dynamics. The results reveal significant divergence between planned and observed development, particularly in peripheral areas, with clear variation across cities. Kanpur exhibits the highest level of non-conformance (EBC: 2.23), indicating weak boundary control and pronounced peri-urban sprawl. Varanasi also demonstrates substantial deviation (EBC: 2.06), reflecting persistent gaps between planning intent and implementation. In contrast, Prayagraj shows relatively stronger conformance (EBC: 1.04), though underlying challenges remain. These differences are shaped by local conditions, including land acquisition conflicts, fragmented governance structures, infrastructure deficits, and limited financial mechanisms. Importantly, the findings underscore that even where spatial conformity appears stronger, it does not necessarily translate into effective planning outcomes. The study concludes that peri-urban growth is not simply unplanned but is shaped by negotiated and context-specific processes. It highlights the need for adaptive, implementation-focused planning, stronger institutional capacity, and integrated financial strategies. By bridging spatial and qualitative analysis, the research provides a more comprehensive framework for understanding and managing peri-urban development in rapidly urbanizing regions. Full article

In response to environmental degradation and social inequities exacerbated by automobile-dependent urban sprawl, this study proposes a framework for dynamic delineation and vitality assessment of 15-min walkable neighborhoods, using Baohe District, Hefei, China as a case study. Static service catchments were constructed using POI and road network data, then refined using one week’s mobile phone signaling trajectories calibrated to actual walking behavior, yielding 143 validated living circles (out of 156 initially delineated). These circles are classified into five typologies: commercial-residential, industrial-residential, educational-residential, predominantly residential, and public-service-oriented. A dual-index system—Facility Vitality Index (FVI) and Population Vitality Index (PVI)—is developed and synthesized into a Composite Vitality Index (VI) through normalization and weighting. Results show that only 27.3% of living circles achieve high vitality in both dimensions, indicating widespread service–demand misalignment. Conversely, 61.5% exhibit low or very low vitality, forming a “vitality depression” around the urban periphery—a pattern of service poverty with significant socioeconomic implications. High-vitality circles cluster along the Binhu New District corridor, while low-vitality circles concentrate in industrial parks (e.g., Feinan Industrial Park) and transport hubs (e.g., Hefei South Railway Station). The historic core lacks micro-infrastructures, whereas new districts—despite high-standard amenities—suffer from weak pedestrian activity. To address these deficiencies, we propose a differentiated zoning strategy: retrofitting micro-infrastructures in legacy neighborhoods, applying Transit-Oriented Development (TOD) principles in new urban extensions, and integrating community-serving functions within industrial peripheries. This framework provides actionable protocols for data-informed governance of 15-min living circles. Full article

The urban heat island effect, a typical rapid urbanization issue, arises from natural surfaces covered by impermeable layers via urban sprawl. To clarify its unclear response to urban expansion under human–land synergy, this paper proposes a multidimensional urban expansion model and a random forest–intelligence integrated method for high-precision large-region population mapping. Taking the Pearl River Delta urban agglomeration as a sample, its urban expansion is divided into five modes to explore thermal environment impacts. The results show: (1) The proposed random forest–intelligence method achieves 84% overall accuracy in 30 m resolution population mapping. (2) The Pearl River Delta urban agglomeration is dominated by vertical expansion, but all cities have population-shrinking regions, especially around Guangzhou and Shenzhen. (3) From 2010 to 2020, Pearl River Delta urban agglomeration impervious surface expansion and population growth were mismatched: impervious surface extended to fringes, while population grew in core areas. (4) The expansion of impervious surface does not always exacerbate the urban heat island effect; when the per-capita land area is less than 1.8 m², it can actually mitigate the effect. (5) Guangzhou–Foshan–Zhaoqing and Shenzhen–Dongguan–Huizhou integration reduces heat island intensity. Core cities driving surrounding areas via clustered, interconnected development alleviates this effect. Full article

Aligning urban morphology with carbon emission intensity categories is essential for advancing sustainable urban development and achieving dual carbon objectives. This study utilizes data from 336 Chinese cities across 2010, 2015, and 2020 to construct multi-dimensional morphological indicators. Spectral clustering categorizes cities into four distinct classes: high-emission intensity, medium-emission ecological, medium-emission developmental, and low-emission. An integrated gradient boosting framework, combined with SHAP and PDP interpretability tools, identifies key morphological drivers and their nonlinear contributions to class assignments. Results demonstrate that morphological features exert nonlinear and threshold-dependent effects on carbon emission intensity category assignments, exhibiting substantial spatial heterogeneity across urban clusters. Core drivers, such as economic density and the landscape shape index, follow distinctly different decision pathways in each category. Furthermore, morphological factors produce non-additive interactive effects that generate region-specific shifts in classification probability. Through this classification-oriented approach, the study provides policymakers with a systematic and readily interpretable reference to inform the formulation of context-specific low-carbon spatial planning strategies. Full article

Enhancing carbon productivity is fundamental to achieving carbon neutrality while sustaining economic growth. Utilizing a comprehensive dataset of Chinese cities from 2010, 2015, and 2020, this study investigates the spatiotemporal patterns and underlying drivers of urban carbon productivity (UCP). Methods including kernel density estimation, spatial autocorrelation analysis, and the spatial Durbin model (SDM) are employed. The results reveal that China’s UCP has improved significantly overall, yet with increasing internal disparities among cities. The SDM decomposition indicates a fundamental shift in driving mechanisms. Green technological innovation has supplanted generalized R&D expenditure as the most dependable core driving force for improving local carbon productivity. Moreover, the economic development level also exerts positive spatial spillover effects in the later stage, which jointly contribute to the formation of a multi-centered pattern. Urban form metrics exert dual influences: urban compactness (ENN_MN) shows a stable positive local effect, whereas urban fragmentation (PD) and urban sprawl (CONTAG) exhibit a paradoxical “local inhibition–neighborhood promotion” effect, highlighting intricate inter-city spatial interactions. The findings underscore the necessity for differentiated local practices, namely, policy must target differentiated city roles and manage spatial spillovers for synergistic regional green and sustainable transition. Full article

Rapid urbanization in China has reshaped the coupling coordination between pollution and carbon emissions. However, existing studies largely rely on linear approaches and lack multidimensional and nonlinear assessments of urban growth patterns. Using panel data for 289 prefecture-level cities from 2010 to 2023, including built-up land, nighttime lights, CO₂ emissions, and PM_2.5 concentrations, this study develops three indicators: Urban Expansion Intensity (UEI), Urban Sprawl Index (USI), and Urban Compactness (UC). By integrating a coupling coordination model, K-means clustering, Geographically and Temporally Weighted Regression (GTWR), and interpretable XGBoost-SHAP analysis, four urban growth patterns are identified: High-Speed Low-Efficiency Expansion (HLE), Low-Speed Low-Efficiency Expansion (LLE), High-Speed High-Efficiency Compact (HHC), and Low-Speed High-Efficiency Compact (LHC). Results indicate that: (1) USI and UC exhibit significant nonlinear threshold effects on CCD; moderate expansion and higher compactness enhance synergy, whereas excessive dispersion or over-compactness weakens coordination. (2) UEI plays a relatively indirect and spatially heterogeneous role. (3) HHC and LHC cities achieve the highest CCD levels, while HLE cities perform the lowest. (4) Urban expansion shows an overall contraction trend, yet substantial regional disparities persist. These findings highlight nonlinear and spatially heterogeneous mechanisms linking urban growth patterns and pollution–carbon coupling coordination, providing implications for differentiated spatial governance. 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

The urban remoteness of warehouses and distribution centres, known as logistics sprawl, has been observed for several decades. According to some, this increase in distances between logistics facilities and hypercentres contributes to the environmental worsening of transport operations, especially in densely populated places such as the Paris metropolitan area. Therefore, the question of logistics tightening—the opposite phenomenon—arises in the context of reducing pollutant emissions in the territories concerned. The objective of this work is to clarify the “hidden” mechanisms of freight transport services. It evaluates, through a simulation, the carbon footprint and operational efficiency of logistics tightening in the city of Paris. The input data we use comes from a large courier service company that can be regarded as an interesting case study when it comes to the Paris region. In our scenario, the ecological consistency of the journeys and the logistical requirements of the transport chain may be contested. Indeed, the inner resettlement of hubs for greener deliveries suggests the actual scheme of the company gets closer to optimum and ironically illustrates the relevance of the current locations. Logistics tightening mainly focuses on the last mile, but such a problem is complex, as each link of the chain has its own peculiarities, meaning the sustainability of one can undermine that of another. Full article