Search Results (121)

Accomplishing China’s national targets of carbon peaking and carbon neutrality necessitates proactive solutions, hinging critically on fundamentally transforming rural construction models. Current construction practices in rural areas are characterized by inefficiency, high resource consumption, and reliance on imported materials. These shortcomings not only jeopardize the attainment of climate objectives, but also hinder equitable development between urban and rural regions. Using the Digital Industrial Park in Yongtai County, Fuzhou City, as a case study, this study focuses on prefabricated public buildings in regions with extreme hot–humid climate, and innovatively integrates BIM (Building Information Modeling)-driven carbon modeling with the Gaussian Two-Step Floating Catchment Area (G2SFCA) method for spatial accessibility assessment to investigate the carbon emissions and economic benefits of prefabricated buildings during the embodied stage, and analyzes the spatial accessibility of prefabricated building material suppliers in Fuzhou City and identifies associated bottlenecks, seeking pathways to promote sustainable rural revitalization. Compared with traditional cast-in-situ buildings, embodied carbon emissions of prefabricated during their materialization phase significantly reduced. This dual-perspective approach ensures that the proposed solutions possess both technical rigor and logistical feasibility. Promoting this model across rural areas sharing similar climatic conditions would advance the construction industry’s progress towards the dual carbon goals. Full article

Global building energy consumption is significantly increasing. Utilizing renewable energy sources may be an effective approach to achieving low-carbon and energy-efficient buildings. A combined system incorporating solar photovoltaic–thermal (PV/T) components with an air-source heat pump (ASHP) was studied for simultaneous heating and power generation in a real residential building. The back panel of the PV/T component featured a novel polygonal Freon circulation channel design. A prototype of the combined heating and power supply system was constructed and tested in Fuzhou City, China. The results indicate that the average coefficient of performance (COP) of the system is 4.66 when the ASHP operates independently. When the PV/T component is integrated with the ASHP, the average COP increases to 5.37. On sunny days, the daily average thermal output of 32 PV/T components reaches 24 kW, while the daily average electricity generation is 64 kW·h. On cloudy days, the average daily power generation is 15.6 kW·h; however, the residual power stored in the battery from the previous day could be utilized to ensure the energy demand in the system. Compared to conventional photovoltaic (PV) systems, the overall energy utilization efficiency improves from 5.68% to 17.76%. The hot water temperature stored in the tank can reach 46.8 °C, satisfying typical household hot water requirements. In comparison to standard PV modules, the system achieves an average cooling efficiency of 45.02%. The variation rate of the system’s thermal loss coefficient is relatively low at 5.07%. The optimal water tank capacity for the system is determined to be 450 L. This system demonstrates significant potential for providing efficient combined heat and power supply for buildings, offering considerable economic and environmental benefits, thereby serving as a reference for the future development of low-carbon and energy-saving building technologies. Full article

Against the backdrop of global climate change and increasing ecological pressure, the refined monitoring of forest resources and accurate tree species identification have become essential tasks for sustainable forest management. Hyperspectral remote sensing, with its high spectral resolution, shows great promise in tree species classification. However, traditional methods face limitations in extracting joint spatial–spectral features, particularly in complex forest environments, due to the “curse of dimensionality” and the scarcity of labeled samples. To address these challenges, this study proposes a synergistic classification approach that combines the spatial feature extraction capabilities of deep learning with the generalization advantages of machine learning. Specifically, a 2D convolutional neural network (2DCNN) is integrated with a support vector machine (SVM) classifier to enhance classification accuracy and model robustness under limited sample conditions. Using UAV-based hyperspectral imagery collected from a typical plantation area in Fuzhou City, Jiangxi Province, and ground-truth data for labeling, a highly imbalanced sample split strategy (1:99) is adopted. The 2DCNN is further evaluated in conjunction with six classifiers—CatBoost, decision tree (DT), k-nearest neighbors (KNN), LightGBM, random forest (RF), and SVM—for comparison. The 2DCNN-SVM combination is identified as the optimal model. In the classification of Masson pine, Chinese fir, and eucalyptus, this method achieves an overall accuracy (OA) of 97.56%, average accuracy (AA) of 97.47%, and a Kappa coefficient of 0.9665, significantly outperforming traditional approaches. The results demonstrate that the 2DCNN-SVM model offers superior feature representation and generalization capabilities in high-dimensional, small-sample scenarios, markedly improving tree species classification accuracy in complex forest settings. This study validates the model’s potential for application in small-sample forest remote sensing and provides theoretical support and technical guidance for high-precision tree species identification and dynamic forest monitoring. Full article

Under the new normal of China’s development, urban construction has shifted from incremental expansion to the optimization of existing stock. As the focal point of urban stock, old communities have garnered increasingly in-depth research. Recent studies have extended their perspectives from physical spaces to the interactive relationship between “space and behavior”, while also emphasizing the integration of qualitative and quantitative analyses. However, existing research primarily focuses on the static characteristics of material spatial environments, neglecting the dynamic interplay between spatial attributes and social network relationships. This study takes the Cangxia Community in Fuzhou as a case study, employing social network analysis (SNA) to construct a dual-network model of resident behavior and public space. Through a three-level analysis of “overall–subgroup–single point”, the intrinsic relationship between “space and behavior” in old communities is revealed. The model demonstrates that resident behavior characteristics are positively correlated with public space attributes, namely, the better the spatial accessibility and visibility, the higher the frequency of resident behaviors. However, mismatched spatial nodes also exist, limiting the synergistic optimization of the dual-network model. This research aims to provide scientifically effective methods and paradigms for the renewal of old communities and the sustainable development of cities. Full article

Constructing a scientific health risk assessment system for ancient trees is crucial for preserving cultural heritage and tree resources. As Fuzhou’s city tree, ancient banyan trees (Ficus microcarpa) with expansive canopies and aerial roots have shaped local ecology and history over millennia. However, urbanization-induced habitat loss and structural vulnerabilities (e.g., root damage and branch injuries) increasingly threaten their health. Current generic tree evaluation standards inadequately address banyan trees’ unique aerial root physiology. This study developed a tailored assessment model using 140 ancient banyan trees from Fuzhou’s urban core and Minhou County. The researchers analyzed 12 tree health indicators (crown, trunk, visible roots, etc.) and two environmental factors through structural equation modeling (SEM) and cluster analysis. Key findings: (1) The SEM demonstrated strong data fit (CMIN/DF = 1.575, RMSEA = 0.064, TLI = 0.927, and CFI = 0.945), validating model reliability. (2) Mechanical damage to the visible root system (weight = 0.135) most significantly impacted health, while canopy closure (0.036) and crown saturation (0.034) showed minimal effects. (3) The site environment strongly correlated with trunk and visible root system health but not crown conditions. (4) In total, 60.71% of the sampled trees were healthy/sub-healthy, while 39.29% exhibited poor health. This methodology provides a replicable framework for ancient tree conservation, emphasizing species-specific evaluation criteria and environmental management strategies. The weighted indicator system enables precise health diagnostics and prioritized protection measures for vulnerable heritage trees. Full article

The terrestrial spatial patterns were affected by human activities, primarily on regional land use (LU) changes, with habitat quality (HQ) serving as a prerequisite for achieving regional sustainable development. Assessing and predicting the spatiotemporal evolution characteristics of regional LU changes and HQ is critical for formulating regional LU strategies and enhancing ecosystem service functions. Using the Poyang Lake Region as our research object, this research employs LU data and utilizes the ‘InVEST’ model and hot-spot analysis to quantitatively evaluate the spatiotemporal changes in HQ during 2000–2020. The PLUS model is then applied to predict LU and HQ trends from 2020 to 2050. The findings are as follows: (1). From 2000 to 2020, the areas of forestland, shrubland, sparse woodland, paddy fields, and dryland in the Poyang Lake Region showed a decreasing trend, with reductions mainly occurring in urban expansion zones such as Nanchang City and largely converted into urban construction land. (2). Since 2000, HQ in the Poyang Lake Region has shown a slight retrogressive evolution, with significant spatial heterogeneity. HQ spatially exhibits a pattern of improvement radiating outward from major cities. (3). Predictions for 2030 to 2050 indicate that HQ in the Poyang Lake Region will continue to decline, with the most significant downward trends occurring in urban built-up areas and their peripheries. The spatiotemporal characteristics reveal an expansion ring around Poyang Lake and an east–west urban expansion corridor linking Pingxiang, Yichun, Xinyu, Nanchang, Fuzhou, Yingtan, and Shangrao. This study provided a research basis for LU direction and urban planning policies in the Poyang Lake Region and its surrounding areas, while also contributing to the construction of agrarian security patterns and the enhancement of ecosystem service levels in the region. Full article

The expansion of road networks profoundly affects ecological systems by intensifying habitat fragmentation, altering hydrological processes, and exacerbating pollution. However, our understanding of the multi-scale spatiotemporal coupling between road networks and ecological quality remains limited. Thus, taking Fuzhou City in Southeastern China as a case study (~12,000 km²), we apply bivariate spatial autocorrelation, geographical detectors (GDs), and multi-scale geographically weighted regression (MGWR) to explore the multi-scale interactions between road networks and ecological quality. Results reveal the following: (1) From 2016 to 2021, kernel density estimation (KDE) analysis of the road network indicates coordinated growth in both urban and rural areas, with an increase of 0.759 km/km². Analysis based on the remote sensing-based ecological index (RSEI) shows a decrease from 2000 to 2016, and then an increase from 2016 to 2021, with a trend of increasing gradually from urban center to rural area. (2) Predominant tradeoff relationships exist between KDE and RSEI in 2016 and 2021, while notable synergistic relationships emerge between ΔKDE and ΔRSEI. (3) Multi-scale GD analysis identifies ΔKDE as a principal factor influencing ΔRSEI, and the MGWR reveals their significant synergistic associations at an optimal scale of 3000 m. These findings highlight the unequal impact of road network expansion on ecological quality, underscoring the pivotal role of road density changes in its spatiotemporal dynamics. They offer essential insights for sustainable transport and ecological planning. Full article

The combination of global climate change and the urban heat island effect has given rise to a deterioration in the livability of residential districts within cities, posing challenges to enhancing the health quality of urban environments. Meanwhile, the intensification of daytime changes in temperature and humidity in residential districts has rendered the sensory representation of the urban heat island effect more pronounced. This study selects the residential districts in Fuzhou City as the research case area, which have witnessed a discernible warming trend in recent years, and acquires temperature and humidity parameter data at three time periods (early morning, noon, and evening) to represent the daytime temperature and humidity change phase. Through aerial photography and field research, three types of spatial morphological indicators (buildings I, vegetation II, and the combination of buildings and vegetation II) of residential districts are quantified to represent the three-dimensional spatial form of the case study area. The analysis results show the following: ➀ Residential districts experience two phases of daytime changes in temperature and humidity: a warming and drying phase (WDP) in the morning and a cooling and humidifying phase (CHP) in the afternoon. The characteristics of changes in temperature and humidity show a spatial correlation with each other. ➁ The impact of urban three-dimensional morphology on changes in temperature and humidity in WDP is minor, whereas, in CHP, it is influenced by Class II and Class III indicators. The two types of urban morphology exert a synergistic regulatory effect on changes in temperature and humidity. ➂ Vegetation has a significant regulatory effect on temperature and humidity variations in residential areas through changes in its three-dimensional form. Enlarging the area of individual trees while reducing their canopy volume can restrain the warming and dehumidification of residential districts and promote cooling and humidification. In contrast to only planting trees, a vegetation configuration combining trees, shrubs, and grass can bring a more obvious cooling effect to residential districts. The research results can provide a reference for urban planners in the planning and design of residential areas as well as the optimization and improvement of urban living environments. Full article

The geographical distribution and scientific evaluation of wind energy potential are crucial for regional energy planning. Wind energy is a renewable energy that can mitigate climate change. Several open-access World Bank databases and the ESRI (Environmental Systems Research Institute) Global were used to gather and process data through wind energy siting optimization in Fujian Province. This paper uses the fuzzy quantifiers of the multi-criteria decision-making (MCDM) approach in arc geographic information system (ArcGIS Pro) and the analytical hierarchy process (AHP) to handle the associated wind data uncertainties to obtain wind energy technology siting optimization for nine cities in Fujian Province. The converted database options and characteristics used the weighted overlay tool (WOT) to reflect the importance of wind farm project objectives. The sensitivity analysis tested the robustness and resilience of the integrated MCDM design for feasibility or viability. The results revealed that 21.743% of the area of Longyan City is suitable for siting wind energy. Other cities’ suitable areas comprise 14.117%, 12.800%, 5.250%, 4.621%, 4.020%, 4.020%, 3.430%, and 2.300%, respectively (Sanming, Ningde, Quanzhou, Putian, Zhangzhou, Nanping, Xiamen, and Fuzhou cities). Furthermore, a considerable amount of wind power is needed to supply the current primary energy deficit (60.0–84.0%) and satisfy the carbon emission reduction target. Wind farm installation in Fujian province is an opportunity to provide inexhaustible energy, generally affected by generation volume and operational span. Wind power is highly acceptable to local Chinese. Reasonably high understanding and excitement for wind farm investments exist among local authorities. Future research should consider wind data of the identified onshore optimization sites and design wind farms for the respective output power for pessimistic, average, and optimistic scenarios for possible wind farm development. Similarly, the long shoreline of about 1680.0 miles (or 2700.0 km) is a considerable source of offshore wind power prospecting, future research, and energy exploitation and harvesting opportunities. Full article

Being tidal-sensitive, the river channel in the Longjin Yangqi area of Cangshan, Fuzhou City, is challenged further because of rapid urbanization. Thus, resultant remediation efforts are crucial. This study aims analyzes hydrodynamic characteristics of the area and, secondly, proposes an ecological dispatch solution with evaluation of its effectiveness through the Storm Water Management Model (SWMM). The chief tasks cover imitating rainfall runoff, optimizing sluice gate activities, reorganizing pump management, and reshaping river morphology to bolster flood control and water quality. Improvements were shown through ecological dispatch strategies, which suggested increasing the channel width for the river and deepening the riverbed, thereby increasing the flood duration, lowering water levels, and less frequent flood occurrences. Optimizing sluice gate settings improved efficiency in the regulation of water flow and reduced scour or siltation problems. Various adjustments to pumping operations scattered over various times were based on live-data analysis, therefore enhancing water flow and the self-purification capacity of the water body. The SWMM was directly applied in this tidal river for urban water resource management with data processing from over 100,000 points in simulations. Wherever needed, changes to model parameters were made to improve its capability and enhance its appropriate use in future urban settings. As a whole, this study presents a plan for sustainable water resource management paired with environmental conditions for the benefit of over 500,000 urban residents in the Longjin Yangqi area. Full article

As an important part of traditional Chinese architecture, Fuzhou’s ancient houses have unique cultural and historical value. However, over time, environmental factors such as efflorescence and plant growth have caused surface damage to their gray brick walls, leading to a decline in the quality of the buildings’ structure and even posing a threat to the buildings’ safety. Traditional damage detection methods mainly rely on manual labor, which is inefficient and consumes a lot of human resources. In addition, traditional non-destructive detection methods, such as infrared imaging and laser scanning, often face difficulty in accurately identifying specific types of damage, such as efflorescence and plant growth, on the surface of gray bricks and are easily hampered by diverse surface features. This study uses the YOLOv8 machine learning model for the automated detection of two common types of damage to the gray brick walls of Fuzhou’s ancient houses: efflorescence and plant growth. We establish an efficient gray brick surface damage detection model through dataset collection and annotation, experimental parameter optimization, model evaluation, and analysis. The research results reveal the following. (1) Reasonable hyperparameter settings and model-assisted annotation significantly improve the detection accuracy and stability. (2) The model’s average precision (AP) is improved from 0.30 to 0.90, demonstrating good robustness in detecting complex backgrounds and high-resolution real-life images. The F1 value of the model’s gray brick detection efficiency is improved (classification model performance index) from 0.22 to 0.77. (3) The model’s ability to recognize the damage details of gray bricks under high-resolution conditions is significantly enhanced, demonstrating its ability to cope with complex environments. (4) The simplified data enhancement strategy effectively reduces the feature extraction interference and enhances the model’s adaptability in different environments. Full article

Active transportation and lifestyles are important components of a sustainable city. Greenways play a crucial role in providing conducive environments for jogging. To investigate the influence of micro-scale characteristics on perceived jogging supportiveness (PJS), 230 video clips of greenways within Fuzhou City were collected as samples. PJS was evaluated using a Likert scale, perceptual characteristics were assessed through a semantic difference scale, and physical characteristics were computed via semantic segmentation. By employing SHAP values and dependence plots within an XGBoost framework, the findings reveal the following: (1) Regarding perceptual characteristics, continuity, culture, and facility affordance exhibit the highest relative importance to PJS (|SHAP| ≥ 0.1). Continuity, naturalness, and vitality generally have positive impacts on PJS, while disturbance is negative. Facility affordance, scale, culture, openness, and brightness demonstrate more complex nonlinear influences that suggest optimal value ranges. (2) Concerning physical characteristics, fences, motor vehicles, and surface material are deemed most influential (|SHAP| ≥ 0.1). The presence of fences, walls, and construction generally negatively affect PJS, while excessive openness is also unfavorable. Comfortable road surfaces are associated with higher levels of PJS. Natural elements and the presence of people and vehicles have promoting effects up to certain thresholds, but beyond that point, they exert opposite influences. Finally, suggestions for designing greenways that encourage jogging are proposed. This study provides practical references for optimizing greenway design to promote active transportation and lifestyles, reinforcing the contribution of green infrastructure to public health in sustainable cities. Full article

The Fujian coastal zone, a key region in China’s coastal belt, has experienced significant landscape and ecological changes due to intense human activities. Understanding the relationship between landscape patterns and ecological quality is critical for sustainable development and ecological protection. Taking the coastal cities, including Fuzhou, Xiamen, and Ningde in Fujian Province of China, as a case, the spatio–temporal changes in landscape patterns and the remote sensing-based ecological index (RSEI) during 2000 and 2020 were explored by the Google Earth Engine (GEE) cloud platform, and then their spatial relationships were identified through Pearson correlation analysis and bivariate spatial autocorrelation analysis. The findings reveal that (1) forest land was the dominant landscape in Fuzhou and Ningde, while cropland prevailed in Xiamen. Significant changes occurred in the land use landscape patterns of the three cities, mainly due to a substantial increase in the built-up land and varying degrees of reduction in arable and forest land. At the landscape level, both Fuzhou and Xiamen exhibited increased landscape fragmentation, while Ningde showed a trend of landscape aggregation; at the class level, forest land in Fuzhou and Xiamen exhibited increased fragmentation, whereas in Ningde, it showed an aggregation trend. (2) Between 2000 and 2020, the ecological–environmental quality of Fuzhou and Ningde continuously improved, while the improvement in Xiamen was less significant. Poor and fair ecological environments in the three cities were mainly concentrated in city centers and coastal zones, and areas of ecological quality degradation were primarily concentrated in coastal zones. (3) Correlation analysis indicates that, whether at the landscape level or the class level, the ecological quality of the three cities is significantly negatively correlated with the fragmentation index and significantly positively correlated with the aggregation index. Moreover, the positive correlation between ecological quality and the forest landscape aggregation index, as well as the negative correlation with the forest landscape fragmentation index, are both significantly stronger than those at the landscape level. As urbanization progresses, forest landscape fragmentation intensifies, especially in city centers and coastal areas, having a significant negative impact on ecological quality. These results highlight the importance of landscape pattern management in maintaining ecological quality. This paper provides insights for coastal cities on balancing urban development with ecological preservation in the context of rapid urbanization. Full article

The process of urbanization leads to the rapid expansion of construction land and brings a series of ecological and environmental problems. The ecological network, as a linear landscape element, is of great significance to improve the quality of the regional ecological environment. In this study, the Morphological Spatial Pattern Analysis (MSPA) and the model of Minimum Cumulative Resistance (MCR) were used to construct the ecological corridors in the central city of Fuzhou, and the land use pattern under the constraints of the ecological network was simulated and quantified by the patch-level land use simulation (PLUS) tool with the results of the identification of ecological corridors. Meanwhile, with the help of InVEST habitat quality model, the regional habitat quality under different development scenarios was compared. The results show that (1) 19 ecological sources and 35 ecological corridors were identified; (2) under the constraints of ecological corridors, the area of forested land in the study area in 2027 was increased by 1.57% and the area of built-up land was reduced by 0.55% compared with that in 2022; (3) and under the constraints of ecological corridors, the mean value of habitat quality in Fuzhou City improved by 0.0055 and 0.0254 compared with 2022 and 2027 natural evolution scenarios, respectively. The study provides decision-making assistance for the construction of ecological corridors from the perspective of land use planning. Full article

The coordinated development of park green spaces (PGS)with urban functional areas (UFA) has a direct impact on the operational efficiency of cities and the quality of life of residents. Therefore, an in-depth exploration of the coupling patterns and influencing factors between PGS and UFA is fundamental for efficient collaboration and the creation of high-quality living environments. This study focuses on the street units of Fuzhou’s central urban area, utilizing multi-source data such as land use, points of interest (POI), and OpenStreetMap (OSM) methods, including kernel density analysis, standard deviational ellipse, coupling coordination degree model, and geographical detectors, are employed to systematically analyze the spatial distribution patterns of PGS and UFA, as well as their coupling coordination relationships. The findings reveal that (1) both PGS and various UFA have higher densities in the city center, with a concentric decrease towards the periphery. PGS are primarily concentrated in the city center, exhibiting a monocentric distribution, while UFA display planar, polycentric, or axial distribution patterns. (2) The spatial distribution centers of both PGS and UFA are skewed towards the southwest of the city center, with PGS being relatively evenly distributed and showing minimal deviation from UFA. (3) The dominant type of coupling coordination between PGS and various UFA is “Close to dissonance”, displaying a spatial pattern of “high in the center, low on the east-west and north-south wings”. Socioeconomic factors are the primary driving force influencing the coupling coordination degree, while population and transportation conditions are secondary factors. This research provides a scientific basis for urban planning and assists planners in more precisely coordinating the development of parks, green spaces, and various functional spaces in urban spatial layouts, thereby promoting sustainable urban development. Full article