Search Results (804)

The supply and demand levels of urban health resources directly impact residents’ quality of life and health. This study employs the Multi-Mode Three-Step Floating Catchment Area (MM3SFCA) method to assess the supply and demand levels of health resources in the main urban area of Harbin under different transportation modes. To address the gap in previous studies that did not consider the impact of the spatial distribution of health resources at varying distances on residents, K-means clustering analysis was applied. The results indicate a significant imbalance between supply and demand for health resources in Harbin’s main urban area. Specifically, approximately 86% of the population met the supply-and-demand standards for health care facilities. However, only 29% and 41% of the population met the supply and demand standards for physical activity facilities and leisure wellness facilities, respectively. From a transportation perspective, the findings reveal that in areas with balanced or abundant supply and demand, residents primarily rely on driving and public transportation. This suggests that health resources are still concentrated in areas far from residential zones, thereby affecting accessibility to resources for some residents. Full article

A well-designed layout for urban parks plays a crucial role in constructing livable cities and enhancing residents’ well-being. The provision of age-friendly park access is fundamental to building an elderly-friendly city. However, previous studies have lacked comprehensive analyses that integrate the distribution of the elderly population, park accessibility, park quality, environmental characteristics, and social equity within a unified framework. Specifically, the supply–demand imbalance mechanism underlying the spatial variations in accessibility has not been adequately addressed. This study employs an improved two-step floating catchment area (2SFCA) method, combined with Lorenz curves and urban park-adapted Gini coefficients, to examine the supply–demand relationship and allocation differences between the elderly population and parks at the neighborhood and community levels. The analysis highlights issues related to equity and accessibility and explores their spatial disparity and influencing factors. The key findings are as follows: (1) The classic 2SFCA model exhibits significant biases in evaluating park supply–demand relationships, accessibility, and equity at a fine-grained scale, indicating the necessity of high-precision modeling. (2) Park accessibility in the Old City of Nanjing follows a dual-ring pattern of high accessibility, contrasted with clustered areas of low accessibility, while accessibility equity shows a central–peripheral gradient. Overall equity is relatively low, with good walking accessibility within only about one-third of communities. (3) Park supply levels, neighborhood construction year, and plot ratios are the primary factors influencing park accessibility for elderly residents. The comprehensive aging index is positively correlated with the equity in park layout, whereas housing prices and neighborhood size do not exhibit a simple linear relationship with park accessibility or equity for elderly residents. These findings provide a comprehensive and realistic perspective for understanding elderly park accessibility and equity, offering decision-making references for enhancing urban livability, managing an aging society, and formulating spatial equity policies in the future. Full article

Hydrological behavior plays a critical role in seasonally dry forest ecosystems, as it underpins water availability for multiple productive activities, including forestry, agriculture, grazing, and urban supply. This study evaluated the hydrological effects of thinning treatments in a semi-arid oak–pine forest of Chihuahua, Mexico, using a Before–After–Control–Impact (BACI) design. Three Micro-catchments (MC) with initially comparable tree density and canopy cover were monitored during the rainy seasons of 2018 (pre-thinning) and 2019 (post-thinning). Thinning treatments were applied at 20% and 60% canopy cover in two MC, while a third remained unthinned as a 100% control. Precipitation and surface runoff were recorded at the event scale, and data were analyzed using Weibull probability models with a log link to capture the frequency and magnitude of runoff events. Precipitation patterns were broadly comparable across years, although 2018 included an extreme storm event (59 mm). In contrast, runoff volumes in 2019 were lower despite marginally higher seasonal rainfall, reflecting the absence of large storms. Statistical modeling indicated that for each additional millimeter of precipitation, mean runoff increased by approximately 12%, although thinning significantly altered baseline conditions. Relative to 2018, mean runoff ratios were 0.087 in the 100% canopy catchment, 0.296 in the 60% treatment, and 0.348 in the 20% treatment, suggesting that reduced canopy cover retained proportionally more runoff than the control. BACI contrasts confirmed that thinned catchments maintained higher proportions of runoff than the unthinned control, although statistical significance was marginal for the 20% canopy treatment. Overall, the study provides ecohydrological insights relevant to the management of semi-arid forest ecosystems. Full article

The Dal Lake ecosystem is a vital freshwater body situated in the heart of Srinagar, Kashmir, India. It is not only a natural asset but also a cornerstone of environmental health, economic vitality, cultural heritage, and urban sustainability. In the last few decades, the condition of the lake ecosystem and water quality has deteriorated significantly owing to the intensification of the eutrophication process. Effective integrated management of the lake is crucial for the long-term sustainable development of the region and the communities that rely on it for their livelihoods. The main reasons for eutrophication are the substantial quantity of anthropogenic pollution, especially nutrients, discharged from the catchment area of the lake and the overexploitation of the lake space and its biological resources. The research presented in this paper aimed to diagnose the state of the lake by analysing trends in eutrophication development and its long-term changes related to the catchment area and lake ecosystem relationships. The research period was 25 years, from 1997 to 2023. Land use and land cover data and water quality monitoring data, which are the basis for trophic state assessment, allowed us to analyze the long-term dynamics of eutrophication in the reservoir. For these purposes, GIS-generated thematic maps were created by using QGIS software version 3.44.1, and an appropriate methodology for quantifying eutrophication was chosen and adapted to the specifics of Dal Lake. The obtained results provide a foundation for a eutrophication management strategy that considers the specificity of the Dal Lake ecosystem and the impact of the catchment area. The outcomes highlighted the varied trophic conditions in different lake basins and the dominance of eutrophic conditions during the study period. The research highlights the complexity of the problem and underscores the need for a comprehensive lake management system. Full article

The uncoordinated water–sediment relationship, fragile eco-environment and unbalanced economic development in the Wei River Basin (WRB) pose serious challenges to its high-quality development. Most existing studies focus on static structures or single elements, making it difficult to systematically reveal the complex interrelationships among ecosystem services (ESs) supply, transmission and demand. To address this issue, this paper innovatively combines the “system perspective” with the “flow network model”. From the perspective of flood-sediment transport, eco-environmental and socio-economic (FES) subsystems, we take the WRB as its research object and systematically analyzes the supply–demand relationship of ESs, the pathways of the ESs flows and ecological compensation (EC) strategies at multiple scales. By constructing a supply–demand assessment model for six types of ESs combined with the water-related flows model, the enhanced two-step floating catchment area method and the gravity model, this paper simulates the ESs flows driven by different transmission media (water, road and atmosphere). The results showed the following: (1) a significant spatial mismatch was observed between the high-supply areas at the northern foothills of the Qinling Mountains and the high-demand areas in the Guanzhong Plains. Furthermore, the degree of this mismatch increased with decreasing scale. (2) The pathways of different ESs flows were influenced by their respective transmission media. The water-related flows passed through areas along the Wei River and the Jing River. The carbon sequestration flows were identified in the upper reaches of the Luo River and between the core urban agglomerations of the Guanzhong Plains. The crop production flows were significantly influenced by the scale of urban crop demand, radiating outward from Xi’an City. (3) At the county and watershed scales, The EC fund pools of 7.5 billion yuan and 2.6 billion yuan were formed, respectively. These EC funds covered over 90% of the areas. These findings verify the applicability of the “FES subsystems” framework for multi-scale EC and provide a theoretical basis for developing an integrated EC mechanism across the entire basin. Full article

Urban expansion in cold semi-arid regions poses significant threats to river ecosystems through land use changes and impervious surface proliferation. This study examined the Selbe River in Ulaanbaatar, Mongolia, integrating Landsat satellite imagery (2000–2020) with long-term water quality monitoring data (2012–2023) to assess land use change impacts on river water quality. Land use classification revealed that built-up areas expanded 3.5-fold from 16.20 km² (2000) to 57.9 km² (2020), driven primarily by informal Ger residential areas and high-rise residential zones. Over the same period, barren land decreased from 149.5 km² to 64.80 km², while green areas increased from 156.89 km² to 200.11 km², which was insufficient to offset ecological stress from impervious surfaces. Water quality analysis of five sampling sites along the river showed progressive deterioration, with the Water Quality Index (WQI) increasing from 1.08 (2012) to 7.24 (2023), classifying the river as “dirty”, the most severe pollution category in Mongolia’s national classification system. Downstream sites adjacent to high-rise residential and Ger districts exhibited elevated concentrations of NH₄⁺, NO₂⁻, NO₃⁻, PO₄³⁻, and suspended solids, frequently exceeding permissible limits established by MNS 4586-98. These findings underscore the cumulative impact of unregulated urban growth on aquatic ecosystems and emphasize the urgent necessity for integrated land use regulation and watershed-based planning to safeguard urban water resources in cold semi-arid environments. The study provides a replicable framework for assessing land use impacts on water quality in rapidly urbanizing regions. Full article

With the accelerating pace of urbanization, cities are increasingly affected by rainstorm and flood disasters, which pose severe threats to the safety of residents’ lives and property. Existing models are increasingly inadequate in meeting the accuracy requirements for flood simulation in highly urbanized regions. Thus, it is urgent to develop a new method for flood inundation simulation based on high-resolution urban hydrological units. The novelty of the model lies in the novel structure of the high-resolution Urban Hydrological Units model (HRGM), which replaces coarse sub-catchments with a fine-grained network of urban hydrological units. The primary innovation is the node-based coupling strategy, in which the HRGM provides precise overflow hydrographs at drainage inlets as point sources for LISFLOOD-FP, rather than relying on diffuse runoff inputs from larger areas. In this paper, a high-resolution hydraulic model (HRGM) based on urban hydrological units coupled with a 2D hydrodynamic model (LISFLOOD-FP) was constructed and successfully applied in the Chebeichong watershed. Results show that the model’s simulations align well with observed data, achieving a Nash efficiency coefficient above 0.8 under typical rainfall events. Compared with the SWMM model, the simulation results of HRGM were significantly improved and more consistent with measured results. Taking the rainstorm event on 10 August 2021 as an example, the Nash coefficient increased from 0.7 to 0.85, while the peak flow error decreased markedly from 15.8% to 3.1%. It should be emphasized that urban waterlogging distribution is not continuous but appears as patchy, discontinuous, and fragmented patterns due to the segmentation and blocking effects of roads and buildings in urban areas. The framework presented in this study shows potential for application in other regions requiring flood risk assessment at urban agglomeration scales, offering a valuable reference for advancing flood prediction methodologies and disaster mitigation strategies. Full article

E-bikes are emerging as a competitive alternative to private cars in both urban and suburban contexts, enhancing accessibility to daily amenities and aligning with the proximity-oriented principles of X-minute city development. However, empirical knowledge remains limited regarding e-bike adopter profiles, trip purposes, influencing factors, and modal substitution patterns, particularly in urban Global South contexts. This exploratory pilot study employs correlation analysis and exploratory factor analysis to examine the sociodemographic characteristics of e-bike users in Surabaya, identify trip behavior patterns, and uncover potential determinants associated with e-bike usage within the X-minute city framework. Based on a sample of 71 e-bike users, the preliminary findings reveal notable socioeconomic patterns in e-bike adoption, with lower-income inner-city residents, particularly women in informal employment, emerging as early adopters. Additionally, two potential influence dimensions are identified: utilitarian trip chaining and active mobility infrastructure. While these findings require validation through larger-scale studies, they suggest potential for e-bikes to expand feasible X-minute city catchments and support low-carbon mobility transitions in similar Global South contexts. Full article

Floodwater depth estimation is essential for disaster response and infrastructure planning yet remains challenging in urban areas with limited gage and hydrological data. This study presents a deep learning-based framework grounded in the hydrostatic equilibrium principle to estimate flood depth using a remote sensing approach. A series of ResNet architectures were trained and evaluated under two different scenarios: (a) a baseline model input using LiDAR-derived DTM and flood extent, and (b) an enhanced model incorporating additional terrain features such as slope, curvature, and Topographic Wetness Index (TWI). The results demonstrate that ResNet18 outperformed deeper models, achieving an RMSE of 0.71 ft, Huber Loss of 0.28 ft, MAE of 0.23 ft, SSIM of approximately 99% and R-Squared of approximately 94% under the enhanced scenario. Inclusion of terrain predictors led to significant improvements in prediction accuracy and spatial coherence. They improved Huber Loss by 28%, RMSE by 13%, and MAE by 21%. However, when applied to an unseen peri-urban catchment, model performance declined (RMSE = 1.95 ft), mainly due to limited and temporally misaligned ground truth data, and differences in spatial characteristics. Despite these limitations, ResNet18 generalizes well, mapping flood depth in unseen catchments, and demonstrates the potential for rapid assessments in data-scarce regions. Full article

Flash floods are among the most destructive hazards in northeastern Bangladesh, particularly in Sylhet district, where intense rainfall from the Meghalaya hills generates rapid inundation of low-lying areas. This study applies the Delft3D Flexible Mesh (FM) Suite to simulate flash flood inundation in the Surma River catchment and assess its potential for hazard mapping. Hydrological inputs were obtained from Bangladesh Water Development Board (BWDB) stations, combined with bathymetric surveys and a 10 m resolution DEM derived from remote sensing data. Model calibration and validation were performed using observed discharge and water level data at SW267 for the years 2019–2020 and verified for flood events in 2012, 2016, and 2017. The model achieved strong agreement with observed flows (R² > 0.9, NSE = 0.75–0.93), and the simulated inundation extent corresponded well with Sentinel-1A satellite-derived flood maps. Validation indicated that Delft3D FM can reasonably capture flash flood propagation and floodplain inundation patterns, including frequently affected areas, e.g., Sylhet Uposhohor. The results demonstrate the value of integrating hydrodynamic modeling with satellite-based validation for improved flood risk management. Findings highlight the potential of Delft3D FM to support early warning, urban planning, and disaster preparedness in flash flood-prone regions of Bangladesh. Full article

Urban catchments are increasingly vulnerable to hydrologic extremes driven by land-use change and climate variability, challenging the traditional assumption of stationarity. This study develops a computational framework to assess the nonstationary behavior of peak flow, volume, and duration in an urban catchment in the Philippines using 39 years of daily flow records (June 1984–November 2022). Missing observations (~8% of the series) were reconstructed using multiple linear regression (MLR) and artificial neural networks (ANNs) with four predictors: daily rainfall, antecedent rainfall, antecedent flow, and built-up area index. MLR with all predictors yielded the most accurate reconstructions. Nonstationarity was detected using the Mann–Kendall test, Sen slope estimator, Pettitt test, and variance change test. Flood events were extracted using block maxima (BM) and peak-over-threshold (POT) methods. BM-based results showed stationary peak flow and volume, while duration increased by 1.78 h/year. POT analyses revealed nonstationarity across all variables, without significant shifts in variance. These findings demonstrate that methodological choices strongly influence nonstationary detection. The framework underscores the importance of reliable data reconstruction and robust statistical testing for nonstationary analysis of flood events. POT-based approaches more effectively capture evolving trends in peak flow, volume, and duration. These can be used in designing resilient infrastructure and flood risk management in urbanizing catchments. Full article

Against the backdrop of rapid urbanization and an increase in extreme rainfall, the impermeable expansion caused by land use changes is significantly altering the urban property convergence process and intensifying the risk of waterlogging. To reveal the impact of land use change on the urban flooding processes, this study takes the main urban area of Wuhan (MUAW) as an example. Based on land use data from 2006 and 2020, it designs rainfall events with return periods of 5, 50, and 100 years. The NewFlood two-dimensional hydrodynamic model is employed to simulate flood evolution, with results validated against flood-prone locations. Flow velocity changes at typical flood-prone points are grouped and statistically analyzed according to land use conversion types. The results showed the following: (1) Between 2006 and 2020, land use transfer in MUAW is primarily influenced by urban sprawl and cropland reduction. (2) Urban expansion led to an increase in the area and depth of rainwater accumulation during rainstorms, which was highly aligned with the direction of urban sprawl, thereby increasing the risk of urban flooding during rainstorms. (3) Land use transfer has a limited impact on the maximum water depth and flow direction in MUAW. However, it can increase peak flow velocity or shift the peak time earlier, reducing the city’s available emergency response time and increasing the difficulty of emergency response. The contribution of this paper lies in quantifying the waterlogging effect of land use change from dynamic dimensions such as “flow velocity—peak occurrence time”, providing process evidence for the assessment of urban early warning advance, the allocation of drainage capacity and land use control, and offering a reference for prioritizing the layout of nature-based solutions and green infrastructure in low-lying catchment areas and key catchment channels to reduce flood risks. Full article

This study evaluated the applicability of the dual drainage model, Hyper Connected–Solution for Urban Flood (HC-SURF), for real-time urban flood forecasting. The model was applied to the extreme rainfall event of August 2022 in the Sillim and Daerim drainage basins in Seoul. Its accuracy and computational efficiency were quantitatively compared with those of two widely used commercial models, the Personal Computer Storm Water Management Model (PC-SWMM) and InfoWorks Integrated Catchment Modelling (ICM). Accuracy was assessed by measuring spatial agreement with observed inundation trace maps using binary indicators, including the Critical Success Index (CSI), Probability of Detection (POD), and False Alarm Ratio (FAR). Computational efficiency was evaluated by comparing simulation times under identical conditions. In terms of accuracy against observations, HC-SURF achieved CSI values ranging from 0.26 to 0.45, with POD values from 0.37 to 0.81 and FAR values from 0.49 to 0.53 across the two basins. In inter-model comparisons, the model showed high hydraulic consistency, demonstrating CSI values between 0.72 and 0.88, POD between 0.82 and 0.99, and FAR between 0.08 and 0.15. In terms of computational efficiency, HC-SURF reduced calculation times by approximately 9% and 44% compared with InfoWorks ICM and PC-SWMM, respectively, for a 48 h simulation. The model also completed a 6 h rainfall simulation in approximately 8 min, meeting the lead time requirements for rapid urban flood forecasting. Overall, these findings show that HC-SURF effectively balances simulation accuracy with computational efficiency, demonstrating its suitability for real-time urban flood forecasting. Full article

Evaluating transit-oriented development (TOD) efficiency in metro station areas remains challenging, as the traditional “Node–Place” model gives limited consideration to guiding factors and struggles to account for inter-regional flows under spatial heterogeneity. To address these limitations, this study develops an enhanced “Node–Place–Accessibility” model by introducing an accessibility dimension to better capture station-level connectivity and walkability. DepthmapX and a convex space approach were applied to quantify station-area accessibility, reflecting passengers’ perceived spatial distance during transfers. The model establishes a TOD measurement framework based on spatial coupling and functional connectivity, enabling the identification of factors influencing metro ridership across different spatial scales. Moran’s I was employed to describe spatial agglomeration and a local spatial clustering method integrating both passenger flow and built-environment (BE) characteristics was constructed to reveal differentiated spatial patterns. The Multiscale Geographically Weighted Regression (MGWR) model was further employed to quantify the spatially varying impacts of BE factors on ridership. Results indicate that the improved model provides stronger discriminative power in identifying “balanced stations,” and that BE conditions exert significant impact on metro ridership, particularly in areas with strong coordination among TOD components. Among the BE dimensions, design granularity exerts a more substantial impact on ridership than connectivity, density, and accessibility. This methodology provides large cities with a reliable tool for formulating targeted strategies that promote positive interactions between transportation and land use, thereby supporting sustainable urban development. Full article

This dataset presents field observations collected in the municipality of Goiatuba, Goiás State, Brazil, a consolidated and representative agricultural frontier of the Brazilian Cerrado biome. The region presents diverse land use dynamics, including annual cropping systems, irrigated fields with up to three harvests per year, and pasturelands. We conducted a field campaign from 3 to 7 November 2025, corresponding to the beginning of the 2025/2026 Brazilian crop season, when crops were at distinct early phenological stages. To ensure representativeness, we delineated 117 reference fields prior to the field campaign, and an additional 463 plots were surveyed during work. Geographic coordinates, crop types, and photographic records were obtained using the GPX Viewer application, a handheld GPS receiver, and the QField 3.7.9 mobile GIS application running on a tablet uploaded with Sentinel-2 true-color imagery and the municipal road network. Plot boundaries were subsequently digitized in QGIS Desktop 3.34.1 software, following a conservative mapping strategy to minimize edge effects and internal heterogeneity associated with trees and water catchment basins. In total, more than 26,000 hectares of agricultural fields were mapped, along with additional land use and land cover polygons representing water bodies, urban areas, and natural vegetation fragments. All reference fields were labeled based on in situ observations and linked to Sentinel-2 mosaics downloaded via the Google Earth Engine platform. This dataset is well-suited for training, testing, and validation of remote sensing classifiers, benchmarking studies, and agricultural mapping initiatives focused on the beginning of the agricultural season in the Brazilian Cerrado. Full article