Search Results (107)

Urban growth often surpasses the actual needs of the population, leading to inefficient land use and long-term environmental challenges. This study provides an integrated perspective on urban landscape transformation by linking socio-demographic dynamics with ecological consequences, notably vegetation loss and increased impervious surfaces. The study area is Năvodari Administrative-Territorial Unit (ATU), a coastal tourist city located along the Black Sea in Romania. By integrating geospatial datasets such as Urban Atlas and Corine Land Cover with population- and construction-related statistics, the analysis reveals a disproportionate increase in urbanized land compared to population growth. Time-series analyses based on the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) from 1990 to 2022 highlight significant ecological degradation, including vegetation loss and increased built-up density. The findings suggest that real estate investment and tourism-driven development play a more substantial role than demographic dynamics in shaping land use change. Understanding urban expansion as a coupled social–ecological process is essential for promoting sustainable planning and enhancing environmental resilience. While this study is focused on the coastal city of Năvodari, its insights are relevant to a broader international context, particularly for rapidly developing tourist destinations facing similar urban and ecological pressures. The findings support efforts toward more inclusive, balanced, and environmentally responsible urban development, aligning with the core principles of Sustainable Development Goal 11, particularly Target 11.3, which emphasizes sustainable urbanization and efficient land use. Full article

Forest land plays a vital role as a terrestrial carbon sink. Urbanization, particularly the conversion of forest land into agricultural and construction areas, has significantly affected the carbon sink capacity of forests. The protection of carbon sinks in forest land has become a critical issue in advancing the dual carbon strategy. Taking Liushahe Town as a case study, this study develops an integrated framework of analysis and response strategies, which encompass “land use change prediction, forest land carbon sink evaluation, and multi-objective optimization”. The purpose is to identify an optimal forest planning scheme that balances carbon sink capacity and biodiversity. The results indicate that: (1) Land use change substantially affects the extent of forest land in Liushahe Town, in which the area exhibits an initial increase followed by a decrease, and is projected to shrink to 89.88% of its 2021 level by 2041. (2) There are significant disparities in carbon sink performance among various forest land plots. The strategic elimination of inefficient plots and preservation of those with high carbon sink potential are key to enhancing the resilience of forest land to disturbances. (3) Multi-objective optimization planning schemes effectively reconcile carbon sinks and biodiversity, and enhance the synergistic effects of forest ecosystem services. Overall, this research provides practical guidance and methodological support for the protection of carbon sinks in forest land within township-scale spatial planning. Full article

Resource-exhausted cities face dual crises of economic stagnation and ecological degradation, which is primarily attributable to the inefficient use of industrial land. The redevelopment of industrial land has emerged as a crucial solution to the “resource depletion-urban decline” dilemma. The issue of inefficient industrial land use in resource-exhausted cities is of great significance as it directly impacts both economic development and ecological protection. Therefore, finding effective ways to redevelop this land is essential for the sustainable development of these cities. This research takes Hegang, a representative resource-exhausted city in China, as a case study. A multi-dimensional evaluation framework and an adaptive redevelopment strategy system are constructed in this research. By integrating data related to land use status, land use efficiency, policy constraints, and development potential, a parcel-scale assessment model is established. This model consists of 4 primary indicators and 13 secondary indicators. Through this model, 11.01 km² of inefficient industrial land in the main urban area of Hegang is identified. Standard deviation ellipse and kernel density analysis are employed to reveal the spatial pattern of inefficient land. The results show that the inefficient industrial land in Hegang exhibits a pattern of “overall dispersion with localized agglomeration”. It is found that idle and abandoned land are the dominant types of inefficient industrial land in Hegang’s main urban area, accounting for 69.7% of the total. This finding provides a clear understanding of the nature of the inefficient land use problem in resource-exhausted cities. A strategic framework is proposed, which incorporates classified governance, dynamic restoration, and multi-stakeholder collaboration. This framework offers a governance toolkit with both theoretical depth and practical value for resource-exhausted cities. Breaking the locked relationship between industrial land and resource dependence promotes the deep integration of spatial restructuring and sustainable transformation. The findings of this research provide significant scientific insights for similar cities worldwide to address the challenges they face and achieve harmony between human activities and land use. Future research could focus on further refining the evaluation framework and redevelopment strategies based on different regional characteristics and resource endowments. Full article

The strategic prioritization of inefficient industrial land (IIL) redevelopment is critical for directing capital allocation toward sustainable urban regeneration. However, current redevelopment prioritization suffers from inefficient identification of IIL and ambiguous characterization of redevelopment potential, which hinders the efficiency of land resource allocation. To address these challenges, this study develops an AI-driven redevelopment prioritization framework for identifying IIL, evaluating redevelopment potential, and establishing implementation priorities. For land identification we propose an improved YOLOv11 model with an AdditiveBlock module to enhance feature extraction in complex street view scenes, achieving an 80.1% mAP on a self-built dataset of abandoned industrial buildings. On this basis, a redevelopment potential evaluation index system is constructed based on the necessity, maturity, and urgency of redevelopment, and the Particle Swarm Optimization-Projection Pursuit (PSO-PP) model is introduced to objectively evaluate redevelopment potential by adaptively reducing the reliance on expert judgment. Subsequently, the redevelopment priorities were classified according to the calculated potential values. The proposed framework is empirically tested in the central urban area of Ningbo City, China, where inefficient industrial land is successfully identified and redevelopment priority is categorized into near-term, medium-term, and long-term stages. Results show that the framework integrating computer vision and machine learning technology can effectively provide decision support for the redevelopment of IIL and offer a new method for promoting the smart growth of urban space. Full article

In the context of accelerated urbanization and ageing in China, the inefficient use of land resources and ecological space extrusion pose significant challenges to the development of age-friendly cities. Existing studies predominantly adopt a single-disciplinary perspective, and there is a paucity of systematic exploration of regional heterogeneity and the multidimensional influencing mechanisms of the effects of adaptive land management policies. Drawing upon the theoretical framework of social-ecological system resilience in environmental sociology, this study integrates the concept of adaptive land management as a factor in the resilience of old-age-friendly cities. Empirical investigation is conducted to examine the impact of adaptive land management on the resilience of old-age-friendly cities and its spatial differentiation. The entropy weight method and the panel regression model are utilized to analyze the panel data of 269 prefectural-level cities in China from 2010 to 2022. The study posits that effective land management is instrumental in enhancing the resilience of age-friendly cities through optimal spatial allocation and ecological restoration. The promotion effect is more pronounced in the central and western regions and in small and medium-sized cities. The internal dimensions of resilience demonstrate heterogeneity, with economic and social resilience showing significant improvement, and ecological resilience being constrained by natural thresholds with a limited effect. The study also puts forward policy recommendations for further building the resilience of age-friendly cities. Full article

Subsidized, decent, and durable housing is a persistent issue for South Africa’s urban areas. Social housing is one of the most important instruments for addressing the situation, yet structural barriers such as land prices, bureaucracy, and governance pose a challenge to forward momentum. This study provides a qualitative examination of social housing in Durban, Cape Town, and Johannesburg on the basis of three dimensions: effectiveness of governance, land accessibility, and practice of sustainability. It is evident that land acquisition is still a great hindrance due to private stakeholder opposition, complex rezoning processes, and speculative ownership of land. Institutional systems within the three cities are characterized by poor intergovernmental coordination, a lack of transparency in land disposition, and lengthy project approval. Johannesburg has seen extensive transit-oriented development, while Cape Town is more advanced in sustainability initiatives, albeit with a resource constraint, and Durban’s human-scale housing types suffer from finance and technical capacity challenges. This study underscores the need for interlinked policy changes to bridge the inefficiencies in governance, facilitate land accessibility, and enhance the incentives of sustainability. An across-the-board data-driven process involving government authorities, private builders, and civil society stakeholders is indispensable in advocating effective and sustainable urban housing strategies for South Africa. Full article

Three-dimensional architectural greening (TAG) enables the integration of ecological, economic, and social advantages via the effective use of multidimensional space in a variety of forms, making it a significant method for enhancing spatial quality in densely populated cities. TAG technology has expanded the scope and capabilities of urban greening. It has the ability to provide green space, improve urban ecology and aesthetics, and alleviate the conflict between limited land resources and rising demand for greening throughout the urbanization process. Currently, there is a lack of a systematic assessment approach that focuses on the public’s visual perception of TAG. It is critical to focus on advances in visual perception approaches and create a “people-oriented perception driven” evaluation system that serves as a scientific foundation for urban three-dimensional greening initiatives. First, this study created a database of 300 TAG cases and selected classic cases using screening, classification, and sampling. Second, three experiments were set up for the study, including the use of the semantic differential (SD) method, and scenic beauty estimation (SBE) for subjective evaluation, and the eye-tracking experiment for objective evaluation. Finally, this study compared subjective and objective evaluations and demonstrated that both two approaches had a certain amount of accuracy. It also investigated the relationship between spatial features and public visual perceptions using methods such as factor and correlation analysis. The three effective methods for evaluating the quality of TAG based on visual perception that are presented in this study—two subjective and one objective—use standardized images, are quick and simple to use, and make up for the drawbacks of conventional strategies like indirectness, inefficiency, and time-consuming data collection. They also form a solid foundation for the real-world application of categorization prediction. In addition to being adaptable to a wide range of application settings, these two assessment paths—subjective evaluation and objective evaluation—can be integrated to complement one another and provide scientific references for future TAG designs and spatial decision making. Full article

This study proposes replacing traditional single-value urban development intensity control with an elastic interval-based approach to address urban development challenges under population shrinkage. It constructs a Floor Area Ratio (FAR) assignment framework guided by “ideal value determination—interval value demarcation—specific value agreement”. The northern central urban area of Shantou City serves as an empirical case. The study, focusing on the conflict between inefficient expansion and population loss, delineates elastic development intensity intervals through multi-dimensional factor analysis: a baseline FAR is determined based on master plan objectives and resource carrying capacity; upper limits are calculated considering transportation and ecological constraints; and lower limits are set according to economic feasibility and social demands, forming a gradient-based control framework. Practically, the study area is divided into differentiated density units, with optimized pathways designed for newly developed, under-construction, and existing plots across multiple scenarios. A multi-stakeholder negotiation mechanism is established to dynamically adapt elastic intervals. Results demonstrate that this method maintains the regulatory authority of master plans while significantly enhancing the adaptability of spatial governance. It provides a theoretical and practical paradigm for balancing regulatory rigidity and flexibility in shrinking cities, offering actionable solutions for vacancy risk mitigation and land-use intensification. Full article

Inefficient stock space use in urban and rural areas causes economic losses and environmental harm, needing better solutions. Currently, this field is constrained by a relatively underdeveloped research history, which has led to the lack of a comprehensive theoretical framework and established solution methodologies. Therefore, it is crucial to clarify the principles of spatial evolution within theoretical approaches to promote the rapid advancement and practical application of subsequent theories. This effort will improve the understanding of the effective utilization of inefficient inventory space and encourage critical analysis by systematically reviewing the developmental trajectory of previous research. This study aims to conduct a thorough analysis of the developmental trajectory, evaluation frameworks, and strategies for the effective utilization of inefficient space by utilizing the Web of Science (WOS) and China National Knowledge Infrastructure (CNKI) databases. Through the application of CiteSpace for visualization and analysis, the research investigates the pertinent literature on inefficient stock space, covering the period from 2004 to the present. The results show that research on inefficient stock space exhibits diverse characteristics, with WOS publications focusing on four primary dimensions, namely land space reuse, the establishment of evaluation systems, environmental governance, and urban and rural development planning. Conversely, CNKI publications tend to prioritize spatial optimization design and the mechanisms of planning and development. In relation to policy frameworks and evolutionary trends, the study of inefficient stock space in urban and rural contexts has evolved through three distinct phases, the embryonic stage (2004–2013), the exploration stage (2013–2020), and the growth stage (2020–present). While the effective utilization of currently inefficient stock space in urban areas has been addressed through various initiatives, there remains a significant gap in research focused on rural areas, highlighting the necessity for an enhanced exploration of urban–rural coupling mechanisms. Additionally, the efficient utilization of inefficient stock space in both urban and rural environments is a multidisciplinary challenge that requires the development of innovative urban and rural development models aligned with the principles of sustainable development, drawing insights from disciplines such as economics, architecture, and urban planning. Full article

China’s rapid urbanization has driven significant economic growth, but has also resulted in resource depletion, ecological degradation, and inefficient land use, collectively hindering sustainable development. In response, pilot policies for “low-carbon cities” and “carbon emissions trading” have been implemented to enhance urban land use efficiency. This study evaluates the green land use efficiency of 282 prefectural-level cities in China from 2006 to 2023, using the non-expected output super-efficiency SBM model. Some cities serve as pilot sites for both “low-carbon cities” and “carbon emissions trading.” A multi-period Difference-in-Differences model is employed to empirically assess the impact and mechanisms of this “dual-pilot” policy on green land use efficiency. The findings indicate the following: (1) The dual-pilot policy significantly improves green land use efficiency, with coordinated implementation yielding greater efficiency gains than single-policy approaches. (2) Mechanism analysis suggests that these policies enhance efficiency by promoting technological innovation and industrial agglomeration. (3) Heterogeneity analysis reveals that the policy’s impact is stronger in western regions, cities with high human capital, large urban centers, areas with stringent environmental regulations, and non-resource-dependent cities. (4) Spatial econometric analysis shows that while low-carbon policies improve local land use efficiency, they also create a siphoning effect on neighboring areas, with positive impacts observed within a 100–600 km range, diminishing and turning negative beyond 600 km. These insights provide a valuable framework for sustainable urban planning, emphasizing the importance of adaptive, context-sensitive policy design in addressing complex ecological and economic challenges. Full article

Inefficient land reuse has emerged as a critical pathway for the sustainable development of urban spaces. Efficient land development in megacities’ industrial heritage areas is heavily influenced by the influx of mass passenger flows from new subway stations. To address this issue, a dynamic passenger flow-oriented land use prediction model for subway stations was developed. This model iterates a simulation model for dynamic passenger flow based on tourists and residents with an artificial neural network for land use prediction. By enhancing the kappa coefficient to 0.86, the model accurately simulated pedestrian flow density from stations to streets. Experiments were conducted to predict inefficient land use scenarios, which were then compared with the current state in national industrial heritage areas. The results demonstrated that the AnyLogic-Markov-FLUS Coupled Model outperformed expert experience in objectively assessing dynamic passenger flow impacts on the carrying capacity of old city neighborhoods during peak and off-peak periods at subway stations. This model can assist in resilient urban space planning and decision-making regarding mixed land use. Full article

With the acceleration of urbanization, urban regeneration has become a critical strategy for megacities to address spatial fragmentation and inefficient resource allocation. However, the mismatch between transportation nodes and land development potential remains a key barrier to sustainable urban renewal. This research takes the urban renewal areas in Changsha as a typical case. Based on the “Node–Place–Value” (NPV) model, a multi-dimensional evaluation system was constructed. Through multiple empirical analysis methods such as spatial data analysis, field research, and economic indicator evaluation, this study deeply explores how this evaluation system provides a theoretical and data basis for detailed planning and further provides guidance for meeting the needs of urban renewal. Through the empirical analysis of the urban renewal areas in Changsha, this study quantifies the matching relationship among transportation nodes, land use, and economic value and reveals the current imbalance issues of these elements in the areas. For example, there is a common mismatch between the functions of transportation nodes and the potential of land development. Specifically, the land use in transportation hub areas fails to fully utilize their transportation advantages, resulting in the waste of transportation resources and low economic benefits. The results reveal significant imbalances in the following areas: Transportation–Land Mismatch: High-accessibility areas (e.g., Martyrs’ Park and Railway Station ) exhibit underdeveloped land use and low economic conversion efficiency. Peripheral Lag: Remote areas (e.g., Wang Xin and Sunshine 100 ) lack both transportation infrastructure and land development potential, leading to resource waste. Value Dimension Impact: The added “value” dimension highlights thatareas with cultural assets (e.g., Martyrs’ Park) achieve higher comprehensive scores despite spatial constraints. The findings of this study not only provide a scientific basis for urban renewal in Changsha but also offer crucial theoretical support and practical references for other megacities in China to address similar issues and achieve sustainable development. Full article

The Thessaly Plain, Greece’s largest alluvial basin, has undergone significant geological, hydrological, and anthropogenic transformations. This study synthesises historical records, geological and hydrogeological studies to assess the evolution of the East Thessaly Plain, focusing on land use changes, groundwater management, and environmental challenges. Intensive agricultural practices, particularly from the 1970s onward, have led to groundwater overexploitation, land subsidence, and declining water quality. The overexploitation of the aquifers, exacerbated by extensive irrigation and inefficient water management, has resulted in critical groundwater shortages and widespread subsidence, particularly in the Larissa–Karla and Titarisios Cone systems. Additionally, recent extreme weather events, including Medicane Daniel (2023) and Medicane Ianos (2020), have highlighted the region’s vulnerability to hydrological hazards, with extensive flooding affecting urban and agricultural areas. The re-emergence of Lake Karla as a flood retention area underscores the unintended consequences of past drainage efforts. Remote sensing, geodetic surveys, and historical records have been examined to assess the interplay between groundwater withdrawals, land subsidence, and flood risks. Full article

Responding to cost inefficiency in the Indonesian cadastral mapping system, this study aimed to analyze the implementation of integrated mapping activities, namely complete systematic land registration, assessing land value zones, and regional land stewardship balance. This study employed an operational management system, particularly focusing on financial aspects, using data envelopment analysis (DEA), a non-parametric technique for evaluating the relative efficiency of decision-making units. These approaches are rarely explored in cadastral mapping. DEA was used to analyze the efficiency of seven aspects: aerial mapping, office supplies, meetings, consumption, transportation, capital expenses, and socialization. Content analysis was used to identify integration parameters derived from operational management-based integration. Cronbach’s alpha was used for the reliability test. The Way Sulan sub-district of South Lampung Regency in Lampung Province, Indonesia, was selected as the study area due to its complete mapping activities. The findings suggested that applying operational management for integrated cadastral mapping is effective. However, contrary to expectations, efficiency was lower in dense urban areas, where costs tend to be cheaper, while efficiency was higher in agricultural areas, where expenses were much greater. Based on this study, an operational management approach to integrated cadastral mapping is recommended to improve budget efficiency and general standards of land management, especially in areas with complex land use. Full article

This study evaluates the spatial–temporal evolution of land use intensity and regional development under five shared socioeconomic pathways (SSPs) through prefecture-level projections in China (2020–2050). This study integrates the population–development–environment model with back propagation (BP) neural networks, a supervised learning algorithm, to analyze how differentiated development trajectories reshape land systems. Results reveal distinct pathways: SSP5 (conventional development) and SSP1 (sustainability) achieve high-income thresholds by 2025/2028 with intensive land development, while SSP3 (fragmentation) risks stagnation post-2037 accompanied by inefficient land use. Spatial analysis identifies persistent dualism across the Hu Huanyong Line—83.6% of urban land expansion concentrates in eastern regions, whereas western areas exhibit 56% lower land productivity. By 2050, regional land use efficiency differentials (0.3–4.3% Gross Domestic Product/capita growth) highlight challenges in balancing urban agglomeration and ecological conservation. These findings provide empirical evidence for optimizing land allocation policies during China’s economic transition. Full article