Search Results (248)

Against the backdrop of China’s advancing strategy for ecological protection and high-quality development in the Yellow River Basin, improving urban land green-use efficiency is critical to reconciling ecological conservation, resource efficiency, and coordinated regional development. Using data for 64 cities across seven urban agglomerations, this study applies a Super-SBM model to estimate urban land green-use efficiency from 2012 to 2024 and combines Dagum Gini decomposition, kernel density estimation, and conventional and spatial Markov chains to examine its spatial disparities and dynamic evolution. Four principal findings emerge. First, efficiency increased overall but exhibited a clear spatial gradient, with higher levels in the upper and middle reaches and lower levels downstream. Second, overall disparities initially widened, subsequently narrowed, and rebounded slightly toward the end of the study period. Between-agglomeration disparities were the largest component on average and during most of the study period; however, their contribution declined, and transvariation density became the largest component in 2023–2024, indicating greater overlap among the efficiency distributions of urban agglomerations. Third, both within- and between-agglomeration disparities exhibited marked heterogeneity, with distinct trajectories across and within urban agglomerations. Fourth, the conventional Markov-chain analysis revealed strong state persistence, a pronounced tendency for high-efficiency states to persist, and transitions occurring predominantly between adjacent classes. The spatial Markov results further showed that local transition probabilities varied across neighborhood efficiency conditions. Overall, efficiency disparities did not exhibit sustained unidirectional convergence; instead, they were characterized by phased adjustment, increasing cross-agglomeration overlap, and neighborhood-conditioned state transitions. By establishing a sequential framework of “efficiency measurement–disparity decomposition–distributional evolution–state transition,” this study provides empirical evidence for understanding the spatial disparities and dynamic evolution of urban land green-use efficiency in the Yellow River Basin. Full article

Rapid urbanization and unplanned land development have transformed Dhaka into one of the most densely built metropolitan areas in South Asia, leading to increased surface heat accumulation and growing pressure on urban energy systems. Numerous studies have reported a progressive rise in Dhaka’s Land Surface Temperature (LST), accompanied by a strong negative correlation between the Normalized Difference Vegetation Index (NDVI) and LST and a positive correlation between the Normalized Difference Built-Up Index (NDBI) and LST. However, spatially explicit assessments that integrate multiple geospatial proxies to characterize urban energy-intensity patterns remain limited, particularly in data-scarce cities where direct energy-consumption data are unavailable. The present study aims to develop and map a proxy-based Urban Energy Intensity Index (UEI) for Dhaka by integrating remote sensing, GIS, and AHP-MCDA techniques. Landsat 9 imagery and VIIRS nighttime light data were processed to derive NDVI, NDBI, and LST layers, while building footprints and road networks were extracted from OpenStreetMap to represent urban form. Eight environmental, built-environment, and anthropogenic indicators were standardized and weighted using the Analytic Hierarchy Process (AHP) before integration through a GIS-based weighted overlay approach. Results show that dense, impervious, and intensely illuminated built-up cores exhibit elevated LST and UEI values, while peri-urban and vegetated areas consistently display lower values, producing spatially distinct high-UEI clusters concentrated within Dhaka’s urban core. Because the index is derived from proxy indicators and was not validated against observed energy-consumption data, the findings should be interpreted as relative spatial patterns rather than direct measures of energy use or energy efficiency. These findings demonstrate the effectiveness of integrating remotely sensed and geospatial indicators to capture intra-urban variability in proxy-based urban energy intensity. The study provides a scalable and data-efficient framework for identifying priority zones for urban planning interventions and supports targeted strategies such as urban greening, surface albedo enhancement, and sustainable land-use planning to mitigate thermal stress. Full article

Improving green land use efficiency is an important approach to reconciling urban development with resource and environmental constraints. Using panel data from 280 cities at the prefecture level and above in China from 2011 to 2024, this study employs a dynamic spatial Durbin model to examine the effects of the digital economy on green land use efficiency, focusing on temporal dynamics, spatial spillover effects, distance-decay boundaries, moderating mechanisms, and urban heterogeneity. The results show that the digital economy significantly improves local green land use efficiency. Its spatial externalities exhibit a pronounced dynamic transition from the spatial siphoning effect in the short term to the green spillover effect in the long term. The short-term spatial siphoning effect is mainly concentrated within approximately 200 km, whereas the long-term green spillover effect extends to approximately 250 km, indicating a clear distance-decay pattern. Green technological innovation and industrial upgrading mitigate short-term spatial siphoning and strengthen the long-term green spillover effect, whereas factor misallocation intensifies short-term spatial siphoning and weakens the long-term green spillover effect. The green-enabling effect of the digital economy is stronger in cities in eastern China, resource-based cities, high-tier cities, and cities with stricter environmental regulation. These findings underscore the importance of coordinating digital economy development with cross-regional green land governance, while strengthening regional absorptive capacity and improving factor allocation efficiency. Full article

Enhancing green total-factor energy efficiency (GTFEE) is a critical pathway for promoting the green transformation of economic and social development. However, the potential influence of the construction and development of urban functional networks (UFNs) on this process has received limited scholarly attention. Using panel data from 148 cities across nine major Chinese urban agglomerations from 2010 to 2023, this study finds the following: First, the development of UFNs at the urban agglomeration scale significantly enhances GTFEE. Second, UFNs improve GTFEE through two distinct mechanisms: “government action” and “market efficiency.” The “government action” mechanism primarily operates by promoting market integration, reducing land resource misallocation, and curbing urban sprawl. The “market efficiency” mechanism functions by enhancing factor mobility, optimizing the allocation of production factors, and accelerating the diffusion of green technological innovations. Third, the effect of UFNs on GTFEE varies according to local development conditions, infrastructure connectivity, and policy continuity and coordination. The enhancement effect is more pronounced in cities located near coastlines, those connected to other cities within the agglomeration by high-speed rail, and cities with longer-serving municipal Party secretaries. Fourth, urban agglomerations characterized by polycentric spatial structures and stronger agglomeration externalities are better able to leverage the functional node effects of their constituent cities, thereby further enhancing GTFEE. Full article

The King Abdulaziz Public Transport Project in Riyadh is one of the massive undertakings that could transform mobility and quality of life in the Saudi capital. However, a full grasp of its many-sided consequences is still hard to obtain. The project is expected to deliver several positive outcomes, including decreased traffic congestion and better air quality, as well as increased mobility; however, it remains vital that the impact of this development on different aspects of urban life is studied using modern spatial analysis methods. This research seeks to address this gap by delving into the project’s influence on land use patterns, transportation behaviors, economic development, urban growth, environmental conditions, population dynamics, and road network efficiency. Using these techniques, some of the achievements and struggles of the project are identified in terms of service coverage, travel times, and how well it fits within Riyadh’s sustainability objectives to reduce car dependency and increase ridesharing. In conclusion, the study aims to contribute knowledge that supports urban planning, policy formulation, and future infrastructure projects so that the King Abdulaziz Public Transport Project is better aligned with the needs of this growing city for a workable, sustainable Riyadh. The King Abdulaziz Public Transport Project is a significant step towards improving Riyadh’s transportation system and achieving environmental, economic, and social sustainability goals. It will contribute to alleviating traffic congestion, improving air quality, boosting economic growth, and enhancing the quality of life for residents. Sustainable landuse planning around the stations, with the allocation of green spaces and public facilities, is essential. Full article

Amid rapid urbanization, the Beijing–Tianjin–Hebei region has experienced substantial land use restructuring. This spatial evolution has created conflicts between development and conservation, challenging regional sustainability. Using 2005–2020 data, this research incorporates urban land use efficiency (ULUE) and the closeness centrality of spatial correlation network into the Patch-generating Land Use Simulation (PLUS) model to reveal driving mechanisms. It simulates 2035 land use patterns under four scenarios: Business as Usual (BAU), Food Security (FS), Ecological Security (ES), and Efficiency-Driven Optimization (EDO). The findings reveal: (1) Regional land use transitioned from rapid expansion to structural adjustment, with cultivated land acting as the primary source for new construction land. (2) ULUE and the closeness centrality of its spatial correlation network exhibited high feature importance in land use transitions, confirming that land allocation efficiency and network structures significantly reshape regional patterns. (3) Compared to BAU or single baseline constraints, the EDO scenario effectively limits inefficient county expansion and promotes compact core city development, balancing construction land control with cultivated and blue-green space preservation. For large urban agglomerations, a spatial governance pathway integrating efficiency-driven strategies and stock optimization is optimal for coordinating multi-dimensional spatial objectives. Full article

Cultivated land is the cornerstone of agricultural production, and its green utilization efficiency is directly linked to the sustainable development of the ecological environment. To investigate the impact and mechanisms of rural entrepreneurship and innovation (REI) on the cultivated land green utilization efficiency (CLGUE), this study employs a Super-SBM with undesired output to estimate the CLGUE of 27 provincial-level administrative units in China from 2014 to 2022. Using a fixed-effects model, the study analyzes the impact of REI on CLGUE and reaches the following conclusions: (1) An increase in REI has a significant positive effect on CLGUE across all provinces, and this conclusion remains robust after testing. (2) Heterogeneity analysis indicates that the positive impact of REI on CLGUE is more pronounced in the eastern and central regions, as well as in areas with lower urbanization rates and higher levels of digital inclusive finance development. (3) Mechanism analysis reveals that REI promotes improvements in CLGUE through three pathways: driving agricultural technological progress, increasing investment in agriculture, and optimizing labor allocation. (4) The impact of REI on CLGUE exhibits a threshold effect; once REI reaches a certain level, its promotional effect is further strengthened. (5) Farm household cultivation scale acts as a negative moderator in the relationship between REI and CLGUE; the higher the proportion of farm households cultivating large-scale cultivated land, the less significant the impact of REI on CLGUE. (6) Stable farmland tenure relationships better facilitate the promotional effect of REI on CLGUE. This study provides theoretical support and practical guidance for optimizing green cultivated land utilization models and improving the quality of cultivated land utilization. Full article

Indian metropolitan cities such as Mumbai grapple with rapid urbanisation, extreme urban density, high built-up areas, loss of green cover, and shrinking open spaces, resulting in increased impermeable surfaces, urban heat island effects, and frequent flooding occurrences. Modern stormwater management has increasingly been characterised by integrated grey-green approaches; however, cities in the Global North benefit from established policies, technical expertise, and financial resources that enable the systematic and large-scale integration of Blue-Green Infrastructure (BGI) through district-wide geospatial assessment frameworks, unlike many cities in the Global South. Despite growing interest in nature-based stormwater solutions, there remains a dearth of geospatial empirical research from India examining the placement, distribution, performance, and functionality of BGI integrated with existing stormwater management systems in cities such as Mumbai. Furthermore, hydrological modelling using tools such as the Storm Water Management Model (SWMM) for the design, planning, and implementation of BGI in Indian cities remains largely unexplored. This study explores the role of BGI strategies in improving urban stormwater management within high-density Indian cities under a 25-year return period extreme rainfall scenario. Using an integrated approach that combines QGIS-based spatial analysis with EPA-SWMM hydrologic-hydraulic modelling, the research examines runoff behaviour, identifies flooding hotspots, and evaluates the effectiveness of Low Impact Development (LID)-based BGI measures such as permeable pavements, infiltration trenches, and green roofs applied at the ward level in Mumbai’s F/North and G/North Wards. Detailed land use classification, spatial mapping, and rainfall simulation corresponding specifically to a 25-year return period rainfall event was used to assess pre- and post-intervention conditions. The findings indicate that the applied BGI measures led to a 12.6% reduction in peak runoff (137.6 m³/s to 120.2 m³/s) and a 5.5% decrease in total runoff volume (783,510 m³ to 740,410 m³). More importantly, the peak flooding flow rate decreased by 45% (94.1 m³/s to 51.7 m³/s), demonstrating that BGI measures can efficiently reduce peak flooding flows by extending runoff hydrographs during extreme rainfall events. These findings are specifically applicable to the simulated 25-year return period extreme rainfall scenario and may vary under different rainfall intensities or return periods. Less extreme events could potentially experience even greater relative reductions or prevent flooding altogether, while also easing downstream hydraulic loads. Overall, strategically placed BGI interventions can significantly reduce surface runoff and peak flow, thereby enhancing stormwater resilience within spatially constrained urban environments. This study provides a replicable, data-driven framework for catchment-scale stormwater planning in dense Indian cities under extreme rainfall conditions, offering practical insights into methods, local contextual considerations, and spatial planning strategies for policymakers and urban planners seeking to retrofit and adapt existing infrastructure under increasing hydrologic stress and climate variability. Full article

The measurement and improvement of urban land use efficiency (ULUE) are crucial for sustainable development in China’s Canal Cities (CCCs). Drawing on the theories of production factors, spatial externalities, and agglomeration economy, this study proposes a framework that explicitly addresses the trade-offs and synergies of sustainable land use. A comprehensive ULUE evaluation index system was established. The super-SBM (Slack-Based Measure) and Global Malmquist–Luenberger (GML) index models were employed to assess the green efficiency of urban land use from 2002 to 2023, while Kernel Density Estimation (KDE) and the optimal parameters-based geographical detector (OPGD) model were used to investigate the spatiotemporal evolution and influencing factors of ULUE. The results reveal a distinctive V-shaped trend in efficiency, marked by significant spatial disequilibrium and predominantly technology-driven sustainable growth. Furthermore, ULUE exhibits a spatial distribution characterized by bipolar and multipolar differentiation, accompanied by concurrent concentration and dispersion, with high-value clusters dominating the spatial clustering type. Government regulation emerges as the dominant factor influencing ULUE, underscoring the pivotal role of policy intervention in guiding the sustainable development of land use. The interactions among pairs of influencing factors strengthened over time; notably, the interaction between government regulation and other factors is the strongest. Four-quadrant analysis profoundly reveals the underlying mechanism, distinguishing a high-quality, sustainable development model driven by technological innovation and a resource-dependent economic growth model. The findings provide valuable insights for promoting green development and formulating sustainable land use policies in CCCs. Full article

The housing sector in major cities is facing escalating challenges due to rapid population growth and land scarcity. Consequently, vertical growth has been adopted as a strategic solution to optimize land use while balancing economic, social, and environmental needs. This study examines the phenomenon of vertical growth of the Dammam Metropolitan Area (DMA) in Saudi Arabia, from an urban sustainability perspective, focusing on evaluating the current state of multi-story buildings, their determinants, and their impact on quality of life and infrastructure efficiency. This study utilizes a systematic review methodology and a conceptual approach to develop an integrated framework for sustainable vertical growth. Furthermore, an empirical validation was conducted by projecting this framework onto vertical housing projects in Dammam, focusing on challenges related to design, construction quality, shared service management, and the suitability of apartments for family needs. The results indicate that the shift toward vertical growth achieves land-use efficiency, limits random horizontal expansion, and provides economic opportunities. However, it faces social and cultural constraints, most notably the resistance of some families to changing traditional ownership patterns, limited privacy and green spaces, and challenges in building maintenance and operations. The study highlights the importance of integrating urban planning, governance, architectural design, and infrastructure to ensure the sustainability of vertical growth and provide suitable housing alternatives. The study recommends further field research to assess social acceptance, improve quality-of-life indicators, and develop policies encouraging sustainable vertical expansion in alignment with Saudi Vision 2030 and the 2030 Sustainable Development Goals (SDGs), ensuring cities are more resilient, efficient, sustainable, and liveable. Full article

Due to climate change and rapid urbanization, cities worldwide face the dual challenge of improving flood resilience and providing accessible green space within limited land resources. Sponge City parks offer a landscape-based approach for integrating stormwater management with park services. However, how park morphology structures this combined performance remains insufficiently understood. This study examines 26 Sponge City parks in Shanghai and evaluates how node-, line-, and patch-type morphologies are linked to stormwater storage and service provision. Using geospatial analysis, DEM-derived catchment delineation, land-cover interpretation, and statistical analysis, this study compares estimated stormwater storage, storage efficiency, local park availability, and land-cover composition across different park morphologies. The results show that estimated performance of stormwater management and park service provision vary across morphological types, but these differences do not follow a simple node–line–patch hierarchy. Rather, the observed patterns are jointly shaped by park morphology, catchment setting, land-cover allocation, and surrounding urban context. These findings suggest that Sponge City parks should not only be evaluated by total stormwater storage. Their contribution depends on morphology, scale, catchment setting, land-cover allocation, and urban context. The study provides a morphology–performance perspective to support more differentiated planning of multifunctional green infrastructure. Full article

Against the backdrop of rapid urbanization, urban land-resource use faces the dual challenge of improving efficiency while maintaining ecological sustainability. Enhancing urban land green use efficiency contributes to the achievement of the United Nations Sustainable Development Goals, particularly SDG 11 and SDG 15. As an emerging governance approach for urban green infrastructure, the National Sponge City Policy (NSCP) aims to address urban waterlogging through nature-based solutions while improving land multifunctionality and ecological carrying capacity. Based on city-level panel data from 2005 to 2022, this study employs a difference-in-differences (DID) approach to identify the policy effect of the NSCP on ULGUE and further examines three transmission channels: innovation effects, infrastructure-support effects, and population-agglomeration effects. The novelty of this study lies in integrating the NSCP into the analytical framework of urban land green use efficiency, extending previous research that mainly focused on waterlogging control, water-resource management, and ecological benefits, and further developing a “policy intervention-factor reallocation-ULGUE improvement” mechanism pathway. The empirical results show that the NSCP significantly improves land green use efficiency in pilot areas, and this conclusion remains valid across multiple robustness checks. The mechanism analysis indicates that strengthened green innovation capacity, improved green infrastructure, and population agglomeration are key channels through which the policy effect is realized. Heterogeneity analysis further reveals that the policy effect varies across regions, dominant industrial structures, and industrial-base types. Overall, the NSCP promotes green spatial governance and efficient resource utilization, providing important institutional experience for coordinating ecological protection and urban development. Full article

Urban land use systems are shaped by market forces, institutional arrangements, and planning regulations. Based on panel data from 266 Chinese prefecture-level cities from 2006 to 2021, this study treats the staggered establishment of environmental courts as a quasi-natural experiment and applies a difference-in-differences approach to examine its impact on urban green land use efficiency. The results indicate that the establishment of environmental courts significantly increases urban green land use efficiency. The effects are more pronounced in cities facing greater environmental pressure, exhibiting more carbon-intensive development patterns, and possessing stronger legal foundations. Mechanism tests suggest that the effect operates primarily through strengthened environmental regulation, enhanced green innovation, and adjustments in local energy consumption structures. Full article

Built-up area extraction is important for monitoring urban development and land-use change. Index-based methods are widely used for extracting built-up areas from Landsat imagery because of their simplicity and efficiency. However, conventional built-up indices often enhance bare land together with built-up areas due to their similar spectral characteristics, which reduces extraction accuracy and limits automatic threshold selection. To address this problem, this study proposes a built-up area extraction method based on multi-index synthesis and principal component analysis (PCA). First, NDBI (Normalization Differential Building Index), SAVI (Soil-Adjusted Vegetation Index), MNDWI (Modified Normalized Difference Water Index), and the brightness, greenness, and wetness components of the Tasseled Cap transformation were stacked to construct a six-band synthetic index image, enhancing the contrast among built-up areas, bare land, vegetation, and water bodies. PCA was then applied to the synthetic image using both correlation and covariance matrices, and the second principal component was used to enhance built-up area information. The resulting CorPC2 and CovPC2 methods were evaluated and compared with conventional built-up indices. The results showed that both PC2-based methods improved the separability between built-up areas and background features, while CovPC2 achieved the best performance by more effectively suppressing bare-land interference without requiring an additional bare-land mask. In the main experimental area, CovPC2 achieved higher accuracy than the comparison methods, and its Otsu-based result remained close to the optimal-threshold result. Validation in three typical cities further demonstrated the applicability of the proposed method across different Landsat sensors and urban environments. The proposed PC2-based method, particularly CovPC2, provides an effective and more automated approach for Landsat-based built-up area extraction under bare-land interference. Additionally, by using a threshold optimizing algorithm, built-up areas can be automatically extracted with high accuracy. Full article

The rapid expansion of the digital economy is reshaping urban systems, yet the pathways through which digitalization drives urban green land use transition remain insufficiently understood. Using panel data from 279 Chinese cities, we measure Urban Green Land Use Efficiency (UGLUE) via a super-efficiency Slack-Based Measure (SBM) model and estimate digital economy effects through double machine learning (DML). We find that digital technology, digital industry, and digital infrastructure all positively influence UGLUE, with digital technology exerting the strongest effect, followed by digital industry, while digital infrastructure exerts the weakest direct effect. Urban spatial compactness (USC) mediates this relationship, functioning as a dominant transmission channel for both digital industry and digital technology, and a supplementary yet significant pathway for digital infrastructure, indicating that digitalization enhances UGLUE in part by promoting more compact urban forms. Effects are heterogeneous, as resource-based and old industrial cities benefit more from technological upgrades, while cities with higher administrative status gain more from broader digital development. These findings identify USC as a key transition pathway linking digitalization to sustainable land use outcomes, and provide evidence-based support for governance-differentiated digital economy policies that steer urban land use transition toward green and compact development trajectories. Full article