Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (100)

Search Parameters:
Keywords = urban joint distribution

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
22 pages, 642 KiB  
Article
Policy Tools, Policy Perception, and Compliance with Urban Waste Sorting Policies: Evidence from 34 Cities in China
by Yingqian Lin, Shuaikun Lu, Guanmao Yin and Baolong Yuan
Sustainability 2025, 17(15), 6787; https://doi.org/10.3390/su17156787 - 25 Jul 2025
Viewed by 353
Abstract
Promoting municipal solid waste (MSW) sorting is critical to advancing sustainable and low-carbon urban development. While existing research often focuses separately on external policy tools or internal behavioral drivers, limited attention has been given to their joint effects within an integrated framework. This [...] Read more.
Promoting municipal solid waste (MSW) sorting is critical to advancing sustainable and low-carbon urban development. While existing research often focuses separately on external policy tools or internal behavioral drivers, limited attention has been given to their joint effects within an integrated framework. This study addresses this gap by analyzing micro-survey data from 1983 residents across 34 prefecture-level and above cities in China, using a bivariate probit model to examine how policy tools and policy perception—both independently and interactively—shape residents’ active and passive compliance with MSW sorting policies. The findings reveal five key insights. First, the adoption and spatial distribution of policy tools are uneven: environment-type tools dominate, supply-type tools are moderately deployed, and demand-type tools are underutilized. Second, both policy tools and policy perception significantly promote compliance behaviors, with policy cognition exerting the strongest effect. Third, differential effects are observed—policy cognition primarily drives active compliance, whereas policy acceptance more strongly predicts passive compliance. Fourth, synergistic effects emerge when supply-type tools are combined with environment-type or demand-type tools. Finally, policy perception not only directly enhances compliance but also moderates the effectiveness of policy tools, with notable heterogeneity among residents with higher cognitive or emotional alignment. These findings contribute to a deeper understanding of compliance mechanisms and offer practical implications for designing perception-sensitive and regionally adaptive MSW governance strategies. Full article
Show Figures

Figure 1

19 pages, 2183 KiB  
Systematic Review
Mercury Scenario in Fish from the Amazon Basin: Exploring the Interplay of Social Groups and Environmental Diversity
by Thaís de Castro Paiva, Inácio Abreu Pestana, Lorena Nascimento Leite Miranda, Gabriel Oliveira de Carvalho, Wanderley Rodrigues Bastos and Daniele Kasper
Toxics 2025, 13(7), 580; https://doi.org/10.3390/toxics13070580 - 10 Jul 2025
Viewed by 458
Abstract
The Amazon faces significant challenges related to mercury contamination, including naturally elevated concentrations and gold mining activities. Due to mercury’s toxicity and the importance of fish as a protein source for local populations, assessing mercury levels in regional fish is crucial. However, there [...] Read more.
The Amazon faces significant challenges related to mercury contamination, including naturally elevated concentrations and gold mining activities. Due to mercury’s toxicity and the importance of fish as a protein source for local populations, assessing mercury levels in regional fish is crucial. However, there are gaps in knowledge regarding mercury concentrations in many areas of the Amazon basin. This study aims to synthesize the existing literature on mercury concentrations in fish and the exposure of urban and traditional social groups through fish consumption. A systematic review (1990–2022) was conducted for six fish genera (Cichla spp., Hoplias spp. and Plagioscion spp., Leporinus spp., Semaprochilodus spp., and Schizodon spp.) in the Web of Science (Clarivate Analytics) and Scopus (Elsevier) databases. The database consisted of a total of 46 studies and 455 reports. The distribution of studies in the region was not homogeneous. The most studied regions were the Madeira River sub-basin, while the Paru–Jari basin had no studies. Risk deterministic and probabilistic assessments based on Joint FAO/WHO Expert Committee on Food Additives (JECFA, 2007) guidelines showed high risk exposure, especially for traditional communities. Carnivorous fish from lakes and hydroelectric reservoirs, as well as fish from black-water ecosystems, exhibited higher mercury concentrations. In the Amazon region, even if mercury levels in fish muscle do not exceed regulatory limits, the high fish consumption can still elevate health risks for local populations. Monitoring mercury levels across a broader range of fish species, including both carnivorous and non-carnivorous species, especially in communities heavily reliant on fish for their diet, will enable a more accurate risk assessment and provide an opportunity to recommend fish species with lower mercury exposure risk for human consumption. The present study emphasizes the need to protect regions that already exhibit higher levels of mercury—such as lakes, hydroelectric reservoirs, and black-water ecosystems—to ensure food safety and safeguard public health. Full article
(This article belongs to the Special Issue Mercury Cycling and Health Effects—2nd Edition)
Show Figures

Figure 1

15 pages, 26611 KiB  
Article
Unveiling Multistability in Urban Traffic Through Percolation Theory and Network Analysis
by Rui Chen, Jiazhen Liu, Yong Li and Yuming Lin
Entropy 2025, 27(7), 668; https://doi.org/10.3390/e27070668 - 22 Jun 2025
Viewed by 321
Abstract
Traffic congestion poses a persistent challenge for modern cities, yet the complex behavior of urban road networks—particularly multistability in traffic flow—remains poorly understood. To address this gap, we analyzed a high-resolution traffic dataset from four Chinese cities over 20 working days (5-min intervals), [...] Read more.
Traffic congestion poses a persistent challenge for modern cities, yet the complex behavior of urban road networks—particularly multistability in traffic flow—remains poorly understood. To address this gap, we analyzed a high-resolution traffic dataset from four Chinese cities over 20 working days (5-min intervals), applying percolation theory to characterize system performance via congestion rate (f) and the size of the largest functional cluster (G). Our analysis revealed clear bimodal and multimodal distributions of G versus f across different periods, ruling out random failure models and confirming the presence of multistability. Leveraging data-driven clustering and classification techniques, we demonstrated that road segments with high betweenness centrality are disproportionately likely to become congested, and that the top 1% most topologically important roads accurately predict both stable state types and the joint behavior of G and f. These findings offer the first large-scale empirical evidence of multistability in urban traffic, laying a quantitative foundation for forecasting phase transitions in congestion and informing more effective traffic management strategies. Full article
(This article belongs to the Special Issue Statistical Physics Approaches for Modeling Human Social Systems)
Show Figures

Figure 1

24 pages, 6610 KiB  
Article
Research on Location Planning of Battery Swap Stations for Operating Electric Vehicles
by Pengcheng Ma, Shuai Zhang, Bin Zhou, Wenqi Shao, Haowen Li, Tengfei Ma and Dong Guo
World Electr. Veh. J. 2025, 16(6), 332; https://doi.org/10.3390/wevj16060332 - 16 Jun 2025
Viewed by 639
Abstract
Currently, the layout planning of power exchange facilities in urban areas is not perfect, which cannot effectively meet the power exchange demand of urban operating vehicles and restricts the operation of urban operating vehicles. The article proposes a vehicle power exchange demand-oriented power [...] Read more.
Currently, the layout planning of power exchange facilities in urban areas is not perfect, which cannot effectively meet the power exchange demand of urban operating vehicles and restricts the operation of urban operating vehicles. The article proposes a vehicle power exchange demand-oriented power exchange station siting planning scheme to meet the rapid replenishment demand of operating vehicles in urban areas. The spatial and temporal distribution of power exchange demand is predicted by considering the operation law, driving law, and charging decision of drivers; the candidate sites of power exchange stations are determined based on the data of power exchange demand; the optimization model of the site selection of power exchange stations with the lowest loss time of vehicle power exchange and the lowest cost of the planning and construction of power exchange stations is established and solved by using the joint algorithm of MLP-NSGA-II; and the optimization model is compared with the traditional genetic algorithm (GA) and the Density Peak. The results show that the MLP-NSGA-II joint algorithm has the lowest cost of optimizing the location of switching stations. The results show that the MLP-NSGA-II algorithm improves the convergence efficiency by about 30.23%, and the service coverage of the optimal solution reaches 94.30%; the service utilization rate is 85.35%, which is 6.25% and 19.69% higher than that of the GA and DPC, respectively. The research content of the article can provide a design basis for the future configuration of the number and location of power exchange stations in urban areas. Full article
Show Figures

Figure 1

17 pages, 2975 KiB  
Article
A Topology Identification Strategy of Low-Voltage Distribution Grids Based on Feature-Enhanced Graph Attention Network
by Yang Lei, Fan Yang, Yanjun Feng, Wei Hu and Yinzhang Cheng
Energies 2025, 18(11), 2821; https://doi.org/10.3390/en18112821 - 29 May 2025
Viewed by 447
Abstract
Accurate topological connectivity is critical for the safe operation and management of low-voltage distribution grids (LVDGs). However, due to the complexity of the structure and the lack of measurement equipment, obtaining and maintaining these topological connections has become a challenge. This paper proposes [...] Read more.
Accurate topological connectivity is critical for the safe operation and management of low-voltage distribution grids (LVDGs). However, due to the complexity of the structure and the lack of measurement equipment, obtaining and maintaining these topological connections has become a challenge. This paper proposes a topology identification strategy for LVDGs based on a feature-enhanced graph attention network (F-GAT). First, the topology of the LVDG is represented as a graph structure using measurement data collected from intelligent terminals, with a feature matrix encoding the basic information of each entity. Secondly, the meta-path form of the heterogeneous graph is designed according to the connection characteristics of the LVDG, and the walking sequence is enhanced using a heterogeneous skip-gram model to obtain an embedded representation of the structural characteristics of each node. Then, the F-GAT model is used to learn potential association patterns and structural information in the graph topology, achieving a joint low-dimensional representation of electrical attributes and graph semantics. Finally, case studies on five urban LVDGs in the Wuhan region are conducted to validate the effectiveness and practicality of the proposed F-GAT model. Full article
Show Figures

Figure 1

25 pages, 11422 KiB  
Article
ESCI: An End-to-End Spatiotemporal Correlation Integration Framework for Low-Observable Extended UAV Tracking with Cascade MIMO Radar Subject to Mixed Interferences
by Guanzheng Hu, Xin Fang, Darong Huang and Zhenyuan Zhang
Electronics 2025, 14(11), 2181; https://doi.org/10.3390/electronics14112181 - 27 May 2025
Viewed by 427
Abstract
Continuous and robust trajectory tracking of unmanned aerial vehicles (UAVs) plays a crucial role in urban air transportation systems. Accordingly, this article presents an end-to-end spatiotemporal correlation integration (ESCI)-based UAV tracking framework by leveraging a high-resolution cascade multiple input multiple output (MIMO) radar. [...] Read more.
Continuous and robust trajectory tracking of unmanned aerial vehicles (UAVs) plays a crucial role in urban air transportation systems. Accordingly, this article presents an end-to-end spatiotemporal correlation integration (ESCI)-based UAV tracking framework by leveraging a high-resolution cascade multiple input multiple output (MIMO) radar. On this account, a novel joint anti-interference detection and tracking system for weak extended targets is presented in this paper; the proposed method handles them jointly by integrating a continuous detection process into tracking. It not only eliminates the threshold decision-making process to avoid the loss of weak target information, but also significantly reduces the interference from other co-channel radars and strong clutters by exploring the spatiotemporal correlations within a sequence of radar frames, thereby improving the detectability of weak targets. In addition, to accommodate the time-varying number and extended size of radar reflections, with the ellipse spatial probability distribution model, the extended UAV with multiple scattering sources can be treated as an entity to track, and the complex measurement-to-object association procedure can be avoided. Finally, with Texas Instruments AWR2243 (TI AWR2243) we can utilize a cascade frequency-modulated continuous wave–multiple input multiple output (FMCW-MIMO) radar platform. The results show that the proposed method can obtain outstanding anti-interference performance for extended UAV tracking compared with state-of-the-art methods. Full article
Show Figures

Figure 1

27 pages, 1797 KiB  
Article
Urban Joint Distribution Problem Optimization Model from a Low-Carbon Point of View
by Lingjia Kong, Liting Cao, Xiaoyan Zhang and Zhiguo Wu
Sustainability 2025, 17(10), 4602; https://doi.org/10.3390/su17104602 - 17 May 2025
Viewed by 480
Abstract
As the carrier of small-piece logistics, urban joint distribution has frequent and complex operations, lacks systematic management and planning, and has large optimization space. Enterprises should bear the social responsibility of reducing carbon emissions in the logistics industry. Using Company M as an [...] Read more.
As the carrier of small-piece logistics, urban joint distribution has frequent and complex operations, lacks systematic management and planning, and has large optimization space. Enterprises should bear the social responsibility of reducing carbon emissions in the logistics industry. Using Company M as an example, this article examines the urban joint distribution problem from a low-carbon point of view to reduce carbon emissions. By deriving the carbon emission formula, we obtain the crucial component for resolving the issue—the kilogram kilometers of distribution operation—and develop a mathematical model to minimize carbon emissions. The strategy of delayed delivery is used in distribution optimization to lower the no-load rate, and a scoring mechanism is presented to assist in determining the distribution time and location. In terms of route optimization, the problems of traditional ant colony algorithms that cannot consider distribution energy consumption, cannot deal with load limitations, and have slow iteration speeds are solved by using the introduction of minimum energy consumption, employing k-means clustering, and setting up elite ants, respectively. Finally, numerical simulations are implemented using C and Python, and the proposed optimization scheme demonstrates a 33.5% reduction in total carbon emissions compared to Company M’s original distribution model. It has been proven that the method proposed in this article has a certain effect on reducing carbon emissions from urban joint distribution. Full article
Show Figures

Figure 1

28 pages, 9110 KiB  
Article
Spatiotemporal Characteristic and Driving Factors of Synergy on Carbon Dioxide Emission and Pollutants Reductions in the Guangdong–Hong Kong–Macao Greater Bay Area, China
by Sinan He, Yanwen Jia, Qiuli Lv, Longyu Shi and Lijie Gao
Sustainability 2025, 17(9), 4066; https://doi.org/10.3390/su17094066 - 30 Apr 2025
Cited by 1 | Viewed by 433
Abstract
As an economically active region, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) faces dual challenges of carbon and air pollution reduction. Existing studies predominantly focus on single pollutants or engineering pathways, lacking systematic analyses of multi-scale synergistic effects. This study investigates the spatiotemporal [...] Read more.
As an economically active region, the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) faces dual challenges of carbon and air pollution reduction. Existing studies predominantly focus on single pollutants or engineering pathways, lacking systematic analyses of multi-scale synergistic effects. This study investigates the spatiotemporal distributions, driving factors, and synergistic effects of CO2 and volatile organic compounds (VOCs) at the multi-scale of urban agglomerations, cities, and industries, using global Moran’s index, standard deviational ellipse, logarithmic mean divisa index decomposition model, and Tapio decoupling model. The results show that the average annual growth rate of CO2 (7.4%) was significantly higher than that of VOCs (4.5%) from 2000 to 2020, and the industrial sector contributed more than 70% of CO2 and VOC emissions, with the center of gravity of emissions migrating to Dongguan. Industrial energy intensity improvement emerged as the primary mitigation driver, with Guangzhou and Shenzhen demonstrating the highest contribution rates. Additionally, CO2 and VOC reduction show two-way positive synergy, and the path of “energy intensity enhancement–carbon and pollution reduction” in the industrial sector is effective. Notably, the number of strong decouplings of the economy from CO2 (11 times) is much higher than the number of strong decouplings of VOCs (3 times), suggesting that the synergy between VOC management and economic transformation needs to be strengthened. This study provides scientific foundations for phased co-reduction targets and energy–industrial structure optimization, proposing regional joint prevention and control policy frameworks. Full article
(This article belongs to the Section Air, Climate Change and Sustainability)
Show Figures

Figure 1

14 pages, 14268 KiB  
Article
Vertical Deformation Extraction Using Joint Track SBAS-InSAR Along Coastal California, USA
by Shunyao Wang, Fengxian Lu, Pengcheng Qi, Miao Zhang, Ziyue Zhang, Shunying Wang, Wenkai Song and Taofeng Ma
J. Mar. Sci. Eng. 2025, 13(4), 761; https://doi.org/10.3390/jmse13040761 - 11 Apr 2025
Viewed by 511
Abstract
Ground deformation poses a major threat to socioeconomic development, especially in coastal regions where compounding effects of anthropogenic activities and natural processes exacerbate its destructive consequences. This urgency calls for comprehensive, spatially extensive, and temporally continuous deformation monitoring. In this study, we propose [...] Read more.
Ground deformation poses a major threat to socioeconomic development, especially in coastal regions where compounding effects of anthropogenic activities and natural processes exacerbate its destructive consequences. This urgency calls for comprehensive, spatially extensive, and temporally continuous deformation monitoring. In this study, we propose a joint track small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) methodology that enhances conventional SBAS-InSAR workflows through integration of ascending and descending orbit data processing, enabling accurate extraction of vertical surface deformation. By analyzing 2348 Sentinel-1 acquisitions, we derived vertical ground deformation across coastal California. The proposed method demonstrates superior measurement accuracy (4.81 mm/year) compared to individual ascending track (7.19 mm/year) or descending track (7.07 mm/year) results. Our analysis identifies substantial deformation signals in coastal urban centers, reveals deformation-fault distribution correlations, and documents characteristic subsidence patterns induced by subsurface resource extraction. These comprehensive data and insights provide invaluable support for the prevention and mitigation of ground deformation in coastal California, and serve as a scientific basis for formulating effective prevention and control strategies, ensuring the safety and sustainable development of these vulnerable coastal regions. Full article
(This article belongs to the Section Coastal Engineering)
Show Figures

Figure 1

22 pages, 6913 KiB  
Article
Coordinated Interaction Strategy of User-Side EV Charging Piles for Distribution Network Power Stability
by Juan Zhan, Mei Huang, Xiaojia Sun, Zuowei Chen, Zhihan Zhang, Yang Li, Yubo Zhang and Qian Ai
Energies 2025, 18(8), 1944; https://doi.org/10.3390/en18081944 - 10 Apr 2025
Viewed by 530
Abstract
In response to the challenges of imbalanced economic efficiency of charging stations caused by disorderly charging of large-scale electric vehicles (EVs), rising electricity expenditure of users, and increased risk of stable operation of the power grid, this study designs a user-side vehicle pile [...] Read more.
In response to the challenges of imbalanced economic efficiency of charging stations caused by disorderly charging of large-scale electric vehicles (EVs), rising electricity expenditure of users, and increased risk of stable operation of the power grid, this study designs a user-side vehicle pile resource interaction strategy considering source load clustering to enhance the economy and safety of electric vehicle energy management. Firstly, by constructing a dynamic traffic flow distribution network coupling architecture, a bidirectional interaction model between charging facilities and transportation/power systems is established to analyze the dynamic correlation between charging demand and road network status. Next, an EV charging and discharging electricity price response model is established to quantify the load regulation potential under different scenarios. Secondly, by combining urban transportation big data and prediction networks, high-precision inference of the spatiotemporal distribution of charging loads can be achieved. Then, a multidimensional optimization objective function covering operator revenue, user economy, and grid power quality is constructed, and a collaborative decision-making model is established. Finally, the IEEE69 node system is validated through joint simulation with actual urban areas, and the non-dominated sorting genetic algorithm II (NSGA-II) based on reference points is used for the solution. The results show that the optimization strategy proposed by NSGA-II can increase the operating revenue of charging stations by 33.43% while reducing user energy costs and grid voltage deviations by 18.9% and 68.89%, respectively. Full article
(This article belongs to the Topic Advances in Power Science and Technology, 2nd Edition)
Show Figures

Figure 1

21 pages, 3706 KiB  
Article
Multi-Joint Symmetric Optimization Approach for Unmanned Aerial Vehicle Assisted Edge Computing Resources in Internet of Things-Based Smart Cities
by Aarthi Chelladurai, M. D. Deepak, Przemysław Falkowski-Gilski and Parameshachari Bidare Divakarachari
Symmetry 2025, 17(4), 574; https://doi.org/10.3390/sym17040574 - 10 Apr 2025
Viewed by 471
Abstract
Smart cities are equipped with a vast number of IoT devices, which help to collect and analyze data to improve the quality of life for urban people by offering a sustainable and connected environment. However, the rapid growth of IoT systems has issues [...] Read more.
Smart cities are equipped with a vast number of IoT devices, which help to collect and analyze data to improve the quality of life for urban people by offering a sustainable and connected environment. However, the rapid growth of IoT systems has issues related to the Quality of Service (QoS) and allocation of limited resources in IoT-based smart cities. The cloud in the IoT system also faces issues related to higher consumption of energy and extended latency. This research presents an effort to overcome these challenges by introducing opposition-based learning incorporated into Golden Jackal Optimization (OL-GJO) to assign distributed edge capabilities to diminish the energy consumption and delay in IoT-based smart cities. In the context of IoT-based smart cities, a three-layered architecture is developed, comprising the IoT system, the Unmanned Aerial Vehicle (UAV)-assisted edge layer, and the cloud layer. Moreover, the controller positioned at the edge of UAV helps determine the number of tasks. The proposed approach, based on opposition-based learning, is put forth to offer effective computing resources for delay-sensitive tasks. The multi-joint symmetric optimization uses OL-GJO, where opposition-based learning confirms a symmetric search process is employed, improving the task scheduling process in UAV-assisted edge computing. The experimental findings exhibit that OL-GJO performs in an effective manner while offloading resources. For 200 tasks, the delay experienced by OL-GJO is 2.95 ms, whereas Multi Particle Swarm Optimization (M-PSO) and the auction-based approach experience delays of 7.19 ms and 3.78 ms, respectively. Full article
Show Figures

Figure 1

17 pages, 3018 KiB  
Article
eVTOL Dispatch Cost Optimization Under Time-Varying Low-Altitude Delivery Demand
by Tao Li, Yingjun Du, Zemin Zhang and Yushun Wang
World Electr. Veh. J. 2025, 16(4), 220; https://doi.org/10.3390/wevj16040220 - 7 Apr 2025
Viewed by 628
Abstract
In the emerging paradigm of embodied intelligence, eVTOL technology holds significant potential to transform the low-altitude economy, particularly in short-distance emergency logistics and urban distribution. Companies like Meituan and Shunfeng (SF) are pioneering fixed low-altitude routes to reduce reliance on human delivery. We [...] Read more.
In the emerging paradigm of embodied intelligence, eVTOL technology holds significant potential to transform the low-altitude economy, particularly in short-distance emergency logistics and urban distribution. Companies like Meituan and Shunfeng (SF) are pioneering fixed low-altitude routes to reduce reliance on human delivery. We first investigate the performance and routing of Meituan’s eVTOL system, focusing on the dynamic optimization of eVTOL reserves and total costs at distribution stations under fluctuating order surges and charging constraints. An iterative algorithm is constructed, supported by numerical examples and Monte Carlo simulations. Our results reveal that cost parameters and demand characteristics jointly shape eVTOL incremental decision-making and its economic performance. To optimize costs, strategies like multi-period decentralized scheduling or low-frequency centralized decision-making are proposed. Future research will address limitations such as 2C charging effects and joint battery-eVTOL replenishment to further advance urban logistics and low-altitude economy development. Full article
Show Figures

Figure 1

24 pages, 15880 KiB  
Article
A High-Resolution DEM-Based Method for Tracking Urban Pluvial–Fluvial Floods
by Yongshuai Liang, Weihong Liao and Hao Wang
Remote Sens. 2025, 17(7), 1225; https://doi.org/10.3390/rs17071225 - 30 Mar 2025
Viewed by 566
Abstract
Flood models based on high-resolution digital elevation models (DEMs) are important for identifying urban land inundation during extreme rainfall events. Urban pluvial and fluvial floods are influenced by distinct processes that are interconnected; thus, they can transform into one another. Conventional flood models [...] Read more.
Flood models based on high-resolution digital elevation models (DEMs) are important for identifying urban land inundation during extreme rainfall events. Urban pluvial and fluvial floods are influenced by distinct processes that are interconnected; thus, they can transform into one another. Conventional flood models struggle to delineate inundation caused by drainage system overflow (urban pluvial flood) and that caused by rivers (urban fluvial flood). In this study, we proposed a novel method for identifying urban pluvial–fluvial floods using a high-resolution DEM. We developed a DEM-based surface pluvial and fluvial inundation tracking model (DEM-SPFITM) that incorporated flood development and mutual transformation processes. When combined with a surface flood control model (SFCM), this approach enabled tracking of the flow paths and exchanged water volume associated with both flood types. The case study results indicate that the proposed method effectively captures the interplay between pluvial and fluvial flooding, enabling the separate identification of flood extent, depth, and velocity under extreme rainfall conditions for both pluvial and fluvial flooding. Compared to the conventional approach, which independently simulates pluvial and fluvial flooding using the SFCM and subsequently overlays the results to estimate pluvial–fluvial flooding inundation, the proposed method demonstrates superior accuracy and computational efficiency. Simulations of three extreme rainstorms indicated that pluvial flooding primarily contributed to extensive land inundation, characterised by shallower depths and lower velocities, with a limited influence of flood depth on velocity. Meanwhile, fluvial flooding further exacerbated land inundation, leading to significant pluvial–fluvial coexistence. In areas adjacent to these flood zones, fluvial flooding predominated, resulting in greater inundation depths and a more pronounced effect of flood depth on velocity. As rainfall intensity and total rainfall increased, the area of fluvial inundation diminished significantly, whereas pluvial–fluvial coexistence intensified and was distributed in zones with relatively large inundation depths and higher flow velocities. This research presented a novel method for distinguishing between urban pluvial–fluvial floods, providing valuable insights for integrated urban flood management and joint flood risk zoning. Full article
Show Figures

Figure 1

29 pages, 24123 KiB  
Article
Spatial and Temporal Evolution Assessment of Landscape Ecological Resilience Based on Adaptive Cycling in Changsha–Zhuzhou–Xiangtan Urban Agglomeration, China
by Huaizhen Peng, Huachao Lou, Yifan Liu, Qingying He, Maomao Zhang and Ying Yang
Land 2025, 14(4), 709; https://doi.org/10.3390/land14040709 - 26 Mar 2025
Cited by 5 | Viewed by 463
Abstract
Urban agglomeration ecosystems are impacted by human activities and natural disasters, so analyzing the spatial and temporal evolution of landscape ecological resilience from the perspective of adaptive cycling is crucial. Using the Changsha–Zhuzhou–Xiangtan urban agglomeration in China as a case study, this research [...] Read more.
Urban agglomeration ecosystems are impacted by human activities and natural disasters, so analyzing the spatial and temporal evolution of landscape ecological resilience from the perspective of adaptive cycling is crucial. Using the Changsha–Zhuzhou–Xiangtan urban agglomeration in China as a case study, this research constructs a “Risk-Potential-Connectivity” framework to evaluate ecological resilience. This framework applies exploratory spatial data analysis methods to examine the spatiotemporal evolution and associated patterns of resilience and the Geodetector model to measure the driving factors of spatial variation. This study constructs an adaptive cycle model based on ecological resilience analysis, integrating potential and connectivity indices to classify the development stages of urban agglomeration regions dynamically. The results showed that the overall spatial distribution pattern of ecological risk decreased from the center outward, whereas ecological potential and connectivity increased. The average resilience index from 2000 to 2020 was 0.31, with a declining trend and shifting center of gravity from northwest to southeast. The spatial and temporal distribution of toughness exhibited high and low aggregation, with an overall Moran index greater than 0.75. Land-use intensity had the strongest explanatory power (q = 0.3662) for the spatial differentiation of landscape ecological resilience drivers and the joint effects of factor interaction had a higher explanatory power than single factors. Adaptive cycle analysis revealed that Furong District is in the protection stage, Xiangtan County in the development stage, and Liling City in the reorganization stage, with no region yet in the release stage. The findings offer a better understanding of the interactive adaptation characteristics and evolutionary patterns of social-ecological systems over extended periods, providing scientific support for the formulation of protection strategies to respond to dynamic changes in urban agglomeration ecosystems. Full article
Show Figures

Figure 1

20 pages, 12949 KiB  
Article
An Uncertainty Analysis of Low-Impact Development Based on the Hydrological Process with Invariant Parameters and Equivalent Effects: Supporting Sustainable Urban Planning
by Xinyi Shu, Chenlei Ye and Zongxue Xu
Sustainability 2025, 17(6), 2587; https://doi.org/10.3390/su17062587 - 14 Mar 2025
Viewed by 733
Abstract
Climate change and urbanization are increasingly threatening urban environments through pluvial flooding, prompting the widespread use of coupled hydrological–hydrodynamic models. These models provide accurate urban flood simulations and forecasting capabilities, and they can analyze the benefits of low-impact development stormwater control measures in [...] Read more.
Climate change and urbanization are increasingly threatening urban environments through pluvial flooding, prompting the widespread use of coupled hydrological–hydrodynamic models. These models provide accurate urban flood simulations and forecasting capabilities, and they can analyze the benefits of low-impact development stormwater control measures in surface-flooding processes. However, most studies have primarily focused on analyzing the stormwater control effects for specific flood events, lacking an analytical framework that accounts for uncertainty. This research proposes a framework for evaluating uncertainty in urban pluvial-flood stormwater control, combining urban-scale simulation, stormwater control modeling, and uncertainty analysis, while constructing nonlinear dependencies between the features reflecting the surface-flood-control benefits. Based on uncertainty analysis and copula methods, this research aims to support sustainable urban planning and provide a sustainable decision-making approach for urban stormwater management. The results show that the uncertainty assessment method based on generalized likelihood uncertainty is effective. By comparing the posterior joint distribution with the prior joint distribution, for different governance performance metrics, the joint, synergistic, conditional, and combined governance effects all exhibit consistent trends as the metrics change. The current research presents an innovative method for simulating and analyzing stormwater control benefits at the urban scale, providing valuable insights for urban sustainable development and flood mitigation strategies. Full article
(This article belongs to the Section Sustainable Urban and Rural Development)
Show Figures

Figure 1

Back to TopTop