Urban lagoons are increasingly common features of contemporary cities, frequently created or heavily modified by urban planning and subsequently exposed to chronic anthropogenic stress. Operating far from historical reference conditions, these systems often persist over long periods as novel urban ecosystems. Understanding how ecological functioning is maintained under such conditions is essential for sustainable urban management and resilience planning. We analyzed a highly impacted urban lagoon in Gualeguaychú city, Argentina, using long-term ecological monitoring data (2015–2019), including phytoplankton, zooplankton, benthic macroinvertebrates, fish, and physicochemical variables. Structural (taxonomic) and functional (trait-based) food webs were constructed to evaluate whether ecosystem functioning persists through non-random reorganization rather than structural complexity. Network metrics were compared with degree-preserving null models, and environmental drivers were assessed using correlation analyses and a parsimonious piecewise structural equation model. Results showed pronounced taxonomic simplification and trophic truncation, with communities dominated by pollution-tolerant, benthic-oriented guilds and limited pelagic consumers. Structural networks were simplified and largely indistinguishable from null expectations. In contrast, functional networks exhibited significantly higher modularity, connectance, and redundancy than expected by chance, indicating compensatory organization and energy canalization through detrital, periphytic, and mixotrophic pathways. A minimal physicochemical cascade (Alkalinity → pH → Dissolved Oxygen → Average Trophic Level) revealed the combined role of chemical buffering and functional redundancy in sustaining trophic organization under chronic stress. These findings suggest that urban lagoons may operate as “extreme-by-design” systems, in which persistence arises from constrained yet non-random functional organization rather than from taxonomic richness. From a sustainability perspective, our results support prioritizing functional indicators, such as redundancy, modularity, and basal-resource pathways, over species-based targets when managing chronically disturbed urban aquatic ecosystems.

This study investigates how zoning reforms and environmental plan revisions in Istanbul have transformed urban design and displaced small and medium-sized enterprises (SMEs). Drawing on official demographic statistics, business license data, and municipal planning reports, this research maps SME relocation patterns across districts such as Zeytinburnu, Kartal, Bayrampaşa, Başakşehir, and Beylikdüzü. These case studies reveal a push–pull dynamic in which SMEs are forced out of traditional industrial zones due to rezoning decisions and rising land values, while being drawn into peripheral areas with lower costs but weaker infrastructure.

The analysis combines quantitative evidence from TÜİK ADNKS, TOBB SME reports, and BTK infrastructure data with spatial visualizations of the 1/100,000 Environmental Plan revisions. Figures and maps illustrate how land-use changes reshape the city’s economic geography, highlighting the intersection of planning decisions and enterprise competitiveness.

Findings suggest that current planning frameworks prioritize large-scale redevelopment while overlooking the resilience of SMEs, which constitute the backbone of Istanbul’s economy. This paper argues for urban design strategies that integrate economic resilience into planning, ensuring that zoning reforms do not undermine local enterprise sustainability. By linking spatial transformation to economic outcomes, this study contributes to debates on inclusive urban development and the role of planning in shaping equitable cities.

Introduction: Sub-Saharan African cities confront the dual imperative of decarbonisation and poverty alleviation, yet planning instruments designed to reconcile these objectives remain inadequately evaluated in mining-dependent contexts. Kitwe, Zambia’s second-largest city, exemplifies this tension: its Integrated Development Plan (2023–2033) projects a population exceeding one million by 2035, while nineteen informal settlements accommodate most low-income residents outside statutory coverage. Strategic net-zero commitments under the Green Economy and Climate Change Act No. 18 of 2024 and NDC 3.0 must be operationalised within the Urban and Regional Planning Act No. 3 of 2015, yet bridging mechanisms between strategic intent and statutory enforcement remain critically under-examined.

Methods: A mixed-methods approach integrates geospatial analysis of land use/land cover change (1990–2020) from Landsat imagery with a systematic policy content analysis of Kitwe’s IDP, the 8th National Development Plan, and allied instruments. Spatial metrics quantify the expansion of informal settlements relative to zoned biodiversity corridors, mine buffer zones, and green infrastructure networks. Semi-structured interviews with planning officers, ward councillors, and community leaders triangulate institutional barriers to implementation.

Results: Analysis reveals that 45.2% of Kitwe’s district area underwent land-cover change over 30 years, with built-up expansion concentrated in former miombo woodland classified as biodiversity-priority. Indigenous forest cover declined 24.9% between 1990 and 2015. Statutory planning covers fewer than 30% of actively developing peri-urban zones, creating governance vacuums enabling settlement encroachment onto contaminated tailings-adjacent land. A critical disconnect emerges between national net-zero commitments and the absence of enforceable local area plans that translate them into spatially binding development controls.

Conclusions: Kitwe’s planning system exhibits dual-track failure: strategic instruments lack statutory enforceability, while statutory instruments lack spatial reach into areas of greatest development pressure. Achieving integrated net-zero and pro-poor outcomes requires binding local area plans co-produced with informal settlement communities, supported by biodiversity offset mechanisms tied to mining licence conditions and by circular land-use frameworks.

Residential density planning is a core instrument of urban planning, land-use intensity, built form, infrastructure demand, and long-term sustainability outcomes. Although residential density limits are defined through planning regulations which the density ultimately realised in development projects emerges through strategic interactions among stakeholders. Within this environment, the most influential interaction occurs between the actor requesting development density and the government authority responsible for approving density within regulatory limits. Understanding how strategic decisions taken by these two key players shape residential density outcomes remains an important challenge in planning practice.

This study examines strategic two-player decision-making in residential density planning using game-theoretic decision structures and the research focuses on how optimum residential density levels are achieved within a fixed regulatory envelope, where planning controls define permissible development capacity. Within these constraints, multiple density configurations remain feasible, enabling density to be realised through alternative vertical, horizontal, or combined strategies. The study simulates how density requests and approval responses interact under such rule-defined conditions. Two decision structures commonly observed in planning practice are examined as simultaneous decision-making, where both players act without knowledge of the other’s choice, and sequential decision-making, where one player’s action follows observation of the other’s move.

The findings show that decision structure significantly influences stakeholder behaviour and the stability of residential density outcomes. Simultaneous decision structures tend to encourage balanced strategic responses and more consistent realisation of optimum density levels, while sequential structures introduce strategic asymmetry that can lead to less stable density configurations. By explaining how two-player decision structures operate within regulatory limits, this study contributes a clearer understanding of strategic decision-making processes in residential density planning and supports more rational and effective urban planning practice.

Biophilic Urbanism is a design approach that prioritises human–nature relationships within urban environments. Along with other natural elements, water-related features, such as rivers or oceans, and even man-made water bodies like ponds, fountains or water spouts, exhibit the potential to foster this relationship across neighbourhoods and cities. Kathmandu Valley has a rich history of urban water architecture and demonstrates a strong integration of water bodies in the planning and design of its traditional towns. This paper examines the role of water bodies in fostering Biophilic Urbanism in the valley with a particular focus on the provision, use and management of the ponds (pukhus in local language) based on the data collected from secondary sources, observations and questionnaire surveys with the users. Findings show that the ponds are essential components of a larger hydrological, social and ecological system of a town that influenced the development of settlement patterns and the network of public spaces. These ponds were strategically placed within residential neighbourhoods, urban nodes and temple complexes to function as a multiuse urban amenity, allowing residents to interact with them on a daily basis. In addition to being an important element of the valley’s unique water management system, these ponds are deeply connected to the cultural and religious practices of the people and stand as a testimony of ‘ecological intelligence’. While these historical ponds face critical threats in the aftermath of rapid and uncontrolled urbanisation in recent decades, their continuous functioning through preservation and regular maintenance is of the utmost importance to uphold their cultural, religious and ecological values. This could be a significant step in pursuing Biophilic Urbanism to create resilient and sustainable cities in contemporary times.

The goal of this study is to predict urban growth in Cox’s Bazar, Bangladesh, through 2050 using historical land-use patterns, geospatial data, and machine learning techniques. Multi-temporal Landsat imagery (1990–2020) was used to classify land cover into urban, vegetation, water, and bare land. Key drivers influencing urban expansion, population density, distance to roads, elevation, slope, distance to coast, and proximity to existing urban areas were extracted and processed in a geospatial environment. By analyzing these factors together, this study identifies patterns and trends in urban expansion that can inform planning decisions. The approach also highlights areas at risk of rapid, unplanned growth, providing a basis for proactive urban management and sustainable development strategies. Random Forest (RF) will be used to quantify the relative importance of candidate drivers of urban growth, and a Cellular Automata–Markov framework will be applied to simulate future urban expansion using transition probabilities derived from multi-temporal land-use/land-cover (LULC) maps. Model validation will be conducted using Kappa statistics and strong overall accuracy. The simulations will generate projected urban extent for multiple future time horizons (2030, 2035, and 2040). Hotspot analyses will be used to detect areas of rapid urbanization, which are hypothesized to cluster along major road corridors, at peri-urban interfaces, and around refugee settlements. This study demonstrates that combining GIS, remote sensing, and machine learning provides quantitative, data-driven forecasts that can guide sustainable urban planning, infrastructure development, and environmental management in rapidly growing coastal cities.

Building lines are a fundamental development control used to regulate the spatial relationship between roads and adjacent buildings, influencing safety, infrastructure expansion and streetscape character. In Sri Lanka, building lines are typically determined using fixed distances or professional judgement, resulting in inconsistent and non-contextual decisions. The absence of a systematic analytical method limits transparency and weakens the effectiveness of planning regulation. This study proposes an objective, context-sensitive approach for building line determination using spatial data and computational modelling.

A mixed-methods framework was adopted. First, legislative documents and international practices were reviewed to establish the conceptual basis of building line regulation. Expert interviews were analysed through thematic analysis to identify influential determinants, followed by a Delphi-informed validation with multi-institutional practitioners. The validated factors were translated into spatial variables using GIS datasets and incorporated into a machine-learning-based predictive model to estimate appropriate building line distances.

Six key determinants were confirmed: road geometry and traffic capacity, development pressure and density, land use and zoning, road hierarchy and connectivity, future development proposals and population, and urban form characteristics. The model successfully generated context-responsive building line values, demonstrating improved consistency compared with fixed-distance practices. Sensitivity and expert validation indicated that the approach better reflects urban character and regulatory intent.

The research establishes a data-driven decision-support tool for building line determination, enhancing transparency, reliability and contextual responsiveness in planning control. The framework provides a replicable methodology for integrating expert knowledge, spatial analysis and machine learning into regulatory planning practice, supporting more coherent and adaptable urban development.

Accurately defining urbanity is essential for effective urban analysis and spatial planning, but conventional approaches often fail to capture the complexity of dynamic urban systems. Many existing studies assess urbanity alone through a single approach, like morphologically or socio-economically, and many countries continue to rely on rigid administrative classifications that inadequately reflect functional and socio-spatial realities. As a result, emerging and transitional urban areas are frequently misidentified, leading to planning inefficiencies and resource misallocation. In response, this study conceptualizes urbanity as a multidimensional continuum and develops an integrated analytical framework to better capture true urban characteristics. The framework combines two complementary indices, a Morphological Urbanity Index (MUI) derived from density, diversity, and accessibility, and a Lifestyle-Based Urbanity Index (LUI) constructed using census-based socio-economic indicators, service accessibility measures, and geospatial proxies such as night-time lights and point-of-interest density. All indicators were normalized and integrated within a GIS (Geographic Information System) environment using raster-based overlay techniques and fuzzy logic modeling. The framework was empirically tested in Kandy District, Sri Lanka, and validated through spatial comparison with existing administrative classifications. Results indicate that urbanity differs when assessed through form-based and lifestyle-based indices. Integrating these dimensions produces a more comprehensive understanding by capturing both spatial structure and lived experience. The resulting urbanity continuum reveals varying intensities of urban characteristics across space, challenging the conventional urban–rural dichotomy. Comparative analysis with administrative boundaries identifies significant spatial mismatches, exposing patterns of hidden urbanization in officially classified rural areas. The study demonstrates that measuring urbanity through an integrated multidimensional framework provides a more realistic representation of contemporary urban conditions. Although tested in Kandy District, the proposed approach is scalable and adaptable to diverse global contexts, supporting improved urban classification and evidence-based spatial planning.

Rapid urbanization is destroying green spaces at a never-before-seen speed throughout the developing globe, which raises major concerns about public health, climatic resilience, and ecological sustainability. Declining green spaces in planned capitals reflects a weakened foundation of planning principles, not just a loss ofenvironment. The landscapes that were formerly characterized by open areas and green belts are changing due to the rapid urbanization in Islamabad, the capital city of Pakistan. Originally intended to be a "garden city" that balanced natural barriers with constructed infrastructure, Islamabad is currently under increasing strain from land conversion and construction, especially in Sector D-12, close to Margalla Hills. The loss of green space in Sector D-12 is investigated in this study using the theories of urban ecology and sustainable development. It views the industry as a networked urban ecosystem where natural systems are directly impacted by construction operations. Concerns regarding long-term environmental sustainability have been raised by the disruption of biodiversity, changes to natural drainage patterns, and escalation of local heat conditions caused by the replacement of plants with buildings. A qualitative case study and 15 semi-structure KIIs were conducted. Findings revealed that open spaces, green belts, and tree covers have significantly decreased, as well as deteriorating environmental comfort, soil erosion during rainfall, and rising temperatures. Although the Capital Development Authority (CDA) has started park development projects and plantation campaigns, these initiatives seem to be primarily reactionary. Conservation measures are hampered by inadequate zoning enforcement, little monitoring, and ongoing development pressures. Islamabad is deviating from its initial ecological objective, this study reveals. Ecological corridors, rooftop gardening projects, more community involvement in environmental monitoring, greater enforcement of regulations, and required green integration in private projects are all necessary for sustainable urban growth.

Urban parks in rapidly industrializing cities of West Asia face a triple challenge: extreme climate, limited green space, and populations fragmented by labor migration. Planning decisions in such contexts are rarely guided by empirical evidence on what drives user satisfaction. This paper reports preliminary findings from a case study in Asaluyeh, a petrochemical city on Iran's Persian Gulf coast, where summer temperatures exceed 45°C and per capita green space is just 0.44 m², less than one-tenth of international recommendations. Analysis identifies park characteristics that most strongly influence visitor satisfaction and highlights underserved population segments. Vegetation quality emerges as the strongest predictor of overall satisfaction (r = 0.45, p < 0.001), surpassing demographic and socioeconomic variables. Gender disparity is evident, with female visitors reporting lower satisfaction than males (3.5 compared with 3.9 on a 5-point scale; t = 2.15, p = 0.045), despite equal or greater preference for public green space. Visits are temporally concentrated, with 76% occurring on weekend evenings and only 2% during weekday daytime hours. Access is constrained by transport dependency, as 84% of visitors arrive by private car. Although 43% of respondents have private gardens, 79% prefer public parks, emphasizing their social and collective value. These findings are translated into a prioritized intervention framework for urban managers, offering guidance for investment based on empirically demonstrated effects on user satisfaction. This abstract presents preliminary findings from an ongoing study, and the full manuscript is currently under review for journal publication.