Case Study In Xiamen Research Articles

Supply and demand analysis and security pattern optimization of flood regulation ecosystem services adapted to the complex terrain of coastal estuaries: A case study in Xiamen

The flood risk in coastal areas has been exacerbated by global climate change. Research on flood risk assessment is emerging from the perspective of supply and demand for flood regulation ecosystem services (FRES). However, there are still limitations in the evaluation of lowland regulation, implementation of intelligent algorithms, comparison of multi-grain FRES supply and demand, and overall optimization of security pattern. Therefore, we propose a comprehensive FRES supply assessment method that incorporates soil and vegetation, lowland, and water regulations. Additionally, we introduce the random forest model to enhance the FRES demand assessment approach. Two grain sizes of the sub-catchment area and grid unit are used to compare FRES supply and demand. Using Xiamen as a case study, this research unveils the following findings: (1) Significant disparities exist between the assessment outcomes of FRES based on multiple types of regulatory services and those solely considering soil and vegetation regulation. The areas with high FRES supply extend beyond upper mountain forests to include local lower plains exhibiting strong capabilities for lowland or water system regulation. (2) Consistent yet distinct results are observed when comparing two grain sizes. Imbalances in supply and demand occur in estuaries, bays, and densely built-up regions. Sub-catchment units exhibit wider distribution and concentration, while grid units display more dispersed patterns. (3) In terms of in-situ regulation, 26.77 km2 ecological protection area, 9.85 km2 ecological restoration area, and 119.59 km2 construction land flood control intervention area are demarcated. From a directional regulation perspective, 22 FRES corridors connecting source and sink areas along with 24 pinch points are identified. Optimizing security patterns through coordinated management of FRES supply and demand can enhance the resilience of coastal estuaries.

Urban functional area building carbon emission reduction driven by three-dimensional compact urban forms’ optimization

Previous optimization approaches with regard to the overall urban form can no longer meet the demand for accurately implementing building energy consumption carbon emission reduction at small spatial scales. This study constructed building energy consumption-oriented urban functional area division method using points of point-of-interest (POI), three-dimensional building and roadway data with urban functional areas as units. The method linked POI to buildings, using building volume as an auxiliary parameter to determine the functional attributes of blocks while taking into account the building operational energy consumption. The residential functional areas, commercial functional areas and industrial functional areas, which account for more than 90% of the total building operation energy consumption and the top three in terms of share, are selected as the analysis objects. Geographic detector was applied to analyze the mechanism of carbon metabolism in the compact spatial patterns of these three functional areas. The case study in Xiamen, China reveals that (1) Three-dimensional building compactness is an important factor influencing building energy consumption(normalized difference vegetation index q-value is 0.227); (2) the difference in energy consumption between different compactness classes in residential and commercial functional areas is significant, while not in industrial functional areas; (3) according to the three-dimensional building compactness optimization path of this study, the building operation energy consumption in central Xiamen City could be optimized to reduce by 7% in 2015. Based on the self-created building energy consumption-oriented functional area division method, it is concluded at the functional areas scale that different types of urban functional zones have different optimization methods for three-dimensional building compactness. Such optimization can save construction resources and achieve double carbon more effectively.

Exploring the evolutionary patterns of urban tourist mobility within a day: A three‐step analysis framework

AbstractDespite the importance of tourist mobility for urban tourism, mechanisms as to how these tourist activities shift throughout the day remain scarcely explored. This study fills this gap by providing a three‐step analysis framework. First, aggregated trajectory data were transformed into a directed weighted network. Then, a new community detection method was proposed to capture the spatial interactions, and two approaches were employed to quantify the evolution patterns of tourist mobility. Finally, the capability of the framework and its potential applications were explored and implemented through a case study in Xiamen, China.

Unlock city-scale energy saving and peak load shaving potential of green roofs by GIS-informed urban building energy modelling

Urban green roofs have emerged as a significant trend in urban architecture worldwide, offering numerous benefits, including enhanced energy performance, improved urban microclimate, and public health. This study proposes a holistic framework for assessing the green roofs' energy-saving potential at the city scale, achieved by scaling up building-scale energy simulations to city-scale energy demands. Firstly, massive building information is collected using Geometric Information System (GIS) technologies. Subsequently, prototype buildings are generated to accurately represent the geometric characteristics of buildings at the city scale. Building performance simulation is further conducted considering three types of plants on roofs. A case study in Xiamen, China, demonstrates the effectiveness of the proposed framework to efficiently quantify the city-scale energy-saving potential of green roofs. By implementing green roofs in Xiamen, energy savings of 1.62–1.83% and peak load shaving of 1.10–1.63% can be achieved for the whole city. Overall, the proposed framework has the potential for widespread application in other cities with minor adjustments to accommodate variations in climate and building parameters.

Assessing the spatial pattern of supply-demand mismatches in ecosystem flood regulation service: A case study in Xiamen

Balancing the supply and demand of urban flood regulation services is crucial for refining flood management policies. Previous studies often employed coarse evaluation units and data limitations may constrained assessments of flood regulation service demand, while this study employs finer evaluation units and an integrated methodology using open data. Taking Xiamen as a case study, machine learning and a comprehensive multi-criteria evaluation model were used to assess flood regulation service demand, hydrological modeling was conducted to evaluate the service supply. Spatial supply-demand disparities were analyzed by the supply-demand ratio. Results reveal pronounced spatial mismatches between flood regulation service supply and demand in Xiamen, with supply deficient units primarily concentrated in intense constructed areas, specifically Jimei, Huli, and Siming districts. The transferability of the method is examined, the correlation between supply-demand relationships and land use is analyzed, demonstrating the applicability of the methods in supporting similar studies in poor-data areas. The methodology could thereby facilitate spatial planning optimization and policy adjustments.

Intelligent transport design with a dual focus: Tourist experience and operating cost

Considering further improvements in the intelligent transportation in tourist attraction management is highly appealing. Inspired by the success of the ride-sharing platform, this study designs an intelligent transport system for attractions that can effectively generate user demand-oriented vehicle operation schemes and timely adjust the scheme to match dynamic requests. The system's core components are a vehicle operation scheme optimization module based on an improved heuristic approach and an adaptive updating module that follows time- and quantity-driven rules. Results of a case study in Xiamen indicate that our system significantly outperforms existing systems in improving tourist experience and saving transport operating costs and can provide more diversified and flexible vehicle operation schemes, thereby contributing to economic, social, and environmental benefits.

Applying Spatial Techniques in Understanding Evolution and Accessibility of Cultural Facilities based on Multi-Source Data: A Case Study in Xiamen, China

Cultural facility is a kind of public facilities that can improve residents’ education, ensure local cultural inheritance, and promote cultural exchanges. Well-planned construction of cultural facilities can promote sustainable development and avoid wasting resources. Xiamen, a coastal city with uneven development, is focused on this study. The time-space evolution of cultural facilities in Xiamen is studied by collecting total number of 34461 POI data, 229071 street data. With help of multi-source data and ArcGIS software, cultural facilities’ distribution and accessibility are visualized and analysed as the standard deviation ellipse, kernel density analysis diagram and accessibility classification diagram. The results show that the construction of cultural facilities in Xiamen is mainly concentrated on the island and other coastal areas. The growth rate of construction was declined by 48.1% over the period. The unequal distribution of cultural facilities has increased over the past eight years. The accessibility of cultural facilities increased in 2016 and worsened in 2022. This is due to the government's emphasis on tourists and lack of attention to residents who lives in industrial areas. To improve equity of residents, strengthen on the construction of cultural facilities in Xiamen industrial zone is required.

Daily hotel demand forecasting with spatiotemporal features

PurposeGiven the importance of spatial effects in improving the accuracy of hotel demand forecasting, this study aims to introduce price and online rating, two critical factors influencing hotel demand, as external variables into the model, and capture the spatial and temporal correlation of hotel demand within the region.Design/methodology/approachFor high practical implications, the authors conduct the case study in Xiamen, China, where the hotel industry is prosperous. Based on the daily demand data of 118 hotels before and during the COVID-19 period (from January to June 2019 and from January to June 2021), the authors evaluate the prediction performance of the proposed innovative model, that is, a deep learning-based model, incorporating graph convolutional networks (GCN) and gated recurrent units.FindingsThe proposed model simultaneously predicts the daily demand of multiple hotels. It effectively captures the spatial-temporal characteristics of hotel demand. In addition, the features, price and online rating of competing hotels can further improve predictive performance. Meanwhile, the robustness of the model is verified by comparing the forecasting results for different periods (during and before the COVID-19 period).Practical implicationsFrom a long-term management perspective, long-term observation of market competitors’ rankings and price changes can facilitate timely adjustment of corresponding management measures, especially attention to extremely critical factors affecting forecast demand, such as price. While from a short-term operational perspective, short-term demand forecasting can greatly improve hotel operational efficiency, such as optimizing resource allocation and dynamically adjusting prices. The proposed model not only achieves short-term demand forecasting, but also greatly improves the forecasting accuracy by considering factors related to competitors in the same region.Originality/valueThe originalities of the study are as follows. First, this study represents a pioneering attempt to incorporate demand, price and online rating of other hotels into the forecasting model. Second, integrated deep learning models based on GCN and gated recurrent unit complement existing predictive models using historical data in a methodological sense.

Marine Spatial Planning Scheme evaluation based on the conflict analysis system - A case study in Xiamen, China

To achieve the ultimate goal of the coordination of the three elements: sea use activities, ecological environment, and marine economy, a Marine Spatial Planning (MSP) scheme requires regular evaluation and adjustments, given that one particular scheme may not take all elements into account. However, concrete evaluation methods were rarely studied, and there are few practical cases. In this study, a conflict analysis system consisting of three matrices was established to quantitatively evaluate the conflicts between the three elements. Combined with the assessment of the current status of certain sea area through the application of ArcGIS functions and tools, the major issues that certain scheme needs to address could be summarized. The conflict analysis system could also be applied to evaluate and compare different adjusted schemes under different scenarios, with the aim to determine one that can better promote coordination. The proposed method was applied in the Marine Functional Zoning (MFZ) of Xiamen, China, a precursor of MSP. The results showed that under the current MFZ scheme, conflicts among different sea use activities and conflicts between sea use activities and ecological environment were caused by the dense and diverse setting of functional zones, some overlaps, and the unsatisfying water quality, biological quality, and biodiversity. Also, the current MFZ scheme is too economically oriented to adequately balance the three elements. Based on the setting of different scenarios and evaluation of different adjusted schemes, the syncretic Scenario 4 can better meet the goal of coordination by avoiding overlaps and reducing the over-dense sea use activities, setting reserved areas and establishing restoration zones, as well as adjusting functional zones with greater economic stimulation to areas with lower pressure, etc. The application prospects and study limitations of the method were discussed in the last part. This study can provide great policy implications for Xiamen's future MFZ revision as well as a workable method for MSP scheme evaluation, adjustment, and development in other regions, which is of great significance and innovation to the sustainable management of coastal and marine areas.

Developing a GIS-based model to quantify spatiotemporal pattern of home appliances and e-waste generation-A case study in Xiamen, China.

The growing amount of electronic waste (e-waste) poses considerable risks to the environment and human health, especially when treated inadequately. However, it is difficult to assess the significance of these issues without quantitative understanding of spatiotemporal patterns of e-waste generation. This paper proposes a new model to estimate in-use stock of electric household appliances (HAs) and e-waste generation at the level of 1km×1km grids by coupling geographic information system (GIS) and material flow analysis (MFA). We took Xiamen, a rapidly urbanized city in China, as a case and the results showed that demands for HAs increased from 1980, peaked in 2016, and then declined. In-use HAs exhibited a logistic growth and significantly increased in both spatial extent and intensity. E-waste generation kept rising until 2019, and its spatial center expanded outward from downtown to suburban areas. Our study highlights that a dynamic and spatial model is useful for designing effective policies for e-waste management by providing spatiotemporal details of e-waste types and generation magnitudes and explicitly recognizing generation hotspots in cities.

Long-Term Dynamic of Land Reclamation and Its Impact on Coastal Flooding: A Case Study in Xiamen, China

While land reclaimed from the sea meets the land demand for coastal development, it simultaneously causes socio-economic systems to be prone to coastal flooding induced by storm surges and sea-level rise. Current studies have seldom linked reclamation with coastal flood impact assessment, hindering the provision of accurate information to support coastal flood risk management and adaptation. This study, using Xiamen, China as a case study, incorporates the spatiotemporal dynamics of reclamation into a coastal flood impact model, in order to investigate the long-term influence of reclamation activities on coastal flood inundation and the consequent exposure of the population to coastal flooding. We find that rapid population growth, continual economic development and urbanization drive a substantial logarithmic increase in coastal reclamation. Historical and future expansions of seaward land reclamation are found to cause dramatic surges in the expected annual inundation (EAI) and the expected annual population (EAP) exposed to coastal flooding. In Xiamen, EAI is estimated to increase by 440.2% from 1947 to 2035, owing to continuing land reclamation. Consequently, the population living in the flooded area has also increased sharply: the EAP of total population is estimated to rise from 0.8% in 1947 to 4.7% in 2035, where reclamation contributes over 80% of this increase. Moreover, a future 10 cm sea-level rise in 2035 will lead to extra 5.73% and 8.15% increases in EAI and EAP, respectively, and is expected to cause massive permanent submersion in the new reclamation zone. Our findings emphasize an integration of hard structures and nature-based solutions for building resilient coasts.

Accessibility-Based Equity of Public Facilities: a Case Study in Xiamen, China

China's rapid economic development has led to inequality in terms of property, education, and health. Equal access to basic public facilities has become a key concern of inclusive development policies. However, previous studies have paid little attention to the effects of different travel modes on the accessibility of basic public facilities. The present research fills this gap. Taking Xiamen city as a case study, it explores the degrees of horizontal and vertical equity by examining the accessibility of various basic public facilities, paying attention to different travel modes and travel times. The results for Xiamen city show that disadvantaged groups experience a greater level of inequity. By taking these aspects into account, one is better equipped to identify areas in the city where access to basic public facilities is in need of substantial improvement.

Identifying multiple stakeholders’ roles and network in urban waste separation management-a case study in Xiamen, China

Urban waste management is a complex social-ecological system that requires broader stakeholder participation and widespread environmental awareness. However, further investigation is required to identify interdependencies among different stakeholders and improve their interactions within the system. This research took Xiamen, a Chinese city, as a case study, which was one of 8 Chinese pilot cities that implemented waste separation in 2000 and one of the 46 key cities participating in a new separation policy since 2017. We used stakeholder analysis (SA), social network analysis (SNA) and ecological network analysis (ENA) to identify the characteristics of different stakeholders, their network structure, and the beneficiaries and contributors to the urban waste separation management (UWSM) system. The research conducted a comparison of resident’s participation before and after the new waste separation policy, as well as a comparison among different stakeholders in the new policy. The results showed that all stakeholders had a high level of satisfaction in 2017, but that satisfaction levels decreased with distance from the downtown area. Residents were more willing to participate in waste separation in 2017 than in 2012. Based on their powers and interests, stakeholders were divided into 4 categories that had different network centrality. The ecological relationships between stakeholders were mainly exploitative and competitive which may cause potential inefficiency; powerful stakeholders did not benefit the whole system and the least powerful stakeholder was the largest contributor. The combined application of these methods were complementary to help diagnose information flow problems in the socio-ecological system. Policy implications to further promote mutualism in UWSM are discussed.

Optimization of cool roof and night ventilation in office buildings: A case study in Xiamen, China

Increasing roof albedo (using a “cool” roof) and night ventilation are passive cooling technologies that can reduce the cooling loads in buildings, but existing studies have not comprehensively explored the potential benefits of integrating these two technologies. This study combines an experiment in the summer and transition seasons with an annual simulation so as to evaluate the thermal performance, energy savings and thermal comfort improvement that could be obtained by coupling a cool roof with night ventilation. A holistic approach integrating sensitivity analysis and multi-objective optimization is developed to explore key design parameters (roof albedo, night ventilation air change rate, roof insulation level and internal thermal mass level) and optimal design options for the combined application of the cool roof and night ventilation. The proposed approach is validated and demonstrated through studies on a six-storey office building in Xiamen, a cooling-dominated city in southeast China. Simulations show that combining a cool roof with night ventilation can significantly decrease the annual cooling energy consumption by 27% compared to using a black roof without night ventilation and by 13% compared to using a cool roof without night ventilation. Roof albedo is the most influential parameter for both building energy performance and indoor thermal comfort. Optimal use of the cool roof and night ventilation can reduce the annual cooling energy use by 28% during occupied hours when air-conditioners are on and reduce the uncomfortable time slightly during occupied hours when air-conditioners are off.

Using a heuristic approach to design personalized urban tourism itineraries with hotel selection

Urban tourism is a worldwide form of tourism and is one of the most important social and economic impetus for urban development. The urban tourism market has been increasingly dominated by the demand for personalized experiences. Accordingly, this study aims to design personalized itineraries with hotel selection for multi-day urban tourists. A two-level heuristic approach is proposed, which embeds genetic algorithm, variable neighborhood search, and differential evolution algorithm into the structure of memetic algorithm. A case study in Xiamen, a coastal city in Southeast China, is carried out to evaluate the performance of our approach. Results of paired sample t-tests show that our proposed approach is remarkably superior to existing methods. In addition, compared with previous methods, our approach can design more reasonable and personalized itineraries for tourists.

Modeling passengers’ loyalty to public transit in a two-dimensional framework: A case study in Xiamen, China

Sustaining and improving passengers’ loyalty has become an effective strategy for the development of bus priority. Passengers’ loyalty towards public transportation could be generally assessed in both attitudinal and behavioral levels. Thus, in this context, spuriously loyal passengers could be characterized by attaching a relatively low level of attitude to public transit users who have high behavioral patronage. Due to the lack of attitudinal preference, these passengers have the potential to turn to alternative transportation modes. Therefore, their loyalty should be better assessed, and targeted approaches should be provided to maintain the market share. This paper adopted a cross-classification framework to divide bus riders by considering different levels of loyalty in both attitudinal and behavioral dimensions. The framework led to four specific segments of passengers, and spurious-loyalty users were identified by using clustering analysis methods in a case study in Xiamen, China. Then, Structural Equation Modeling approach was employed, and hypotheses accounting for public transit loyalty were examined and analyzed in a baseline model. Moreover, key factors leading to spurious loyalty were identified, and index score of corresponding variables was calculated. Surprisingly, the results indicated that over half of users who highly adhered to public transit were not attitudinally loyal. However, although these passengers were dissatisfied with the current level of public transit service in specific regions as expected, their willingness of continuing-to-use public transit maintained at a high level. It implied that the cost of shifting to private motorization in Xiamen might still be high, so most spuriously loyal passengers had to continue choosing public transit in the near future. Nevertheless, the key to successfully sustain the long-term development of public transit should still focus on delivering passenger-value-oriented quality services. Therefore, with regards to the improvement of bus service to maintain the market share, targeted measures should be taken in terms of “crowdedness in the bus during peak hours”, “driving stability and comfort”, “bus speed”, “waiting time at stations” and “convenience of route transfers”.

Dissipation of water in urban area, mechanism and modelling with the consideration of anthropogenic impacts: A case study in Xiamen

Dissipation of water (evapotranspiration and water vapor conversion in human water use activities) is one of the significant hydrological processes in urban area, which becomes more complicated with rapid urbanization. However, there are few systematic studies on water dissipation problems in urban area, and even the related concepts are unclear. This paper proposed the concept of urban water dissipation (UWD) to describe water vapor conversion in urban areas, and presented analysis on mechanism of UWD based on observing and monitoring experiments. The urban underlying surface was divided into five categories: buildings, paved ground, vegetation, water surface, and soil, in which the buildings have been scarcely discussed in terms of water dissipation. The dissipation of water in buildings plays a more and more important role in the urban water circulation system, as the water supply increases in urban areas. To reveal how much water is dissipated in the buildings, the main water dissipation processes in different kinds of buildings were analyzed, and the quantitative model was proposed. Based on the traditional evapotranspiration models for urban underlying surface and the proposed model for water dissipation in buildings, a new modelling system was built to simulate the total UWD. The new model system reflects the impact of human water use activities on urban water dissipation. It was applied in Xiamen city to simulate the UWD in 2000, 2005, 2010, and 2015. The results show that the UWD intensity increased with the urbanization process in Xiamen urban area in past 15 years. The UWD contribution rate increased for most land use types, except green land. For example, the water dissipation on residential land is the fastest growing one of all land use types, and its contribution rate surpassed that of green land to become the largest contributor in 2010. Because of the interference of strong human activities, the contribution rate of water dissipation on the social side continues increasing. The contribution rate of UWD on the social side was more than 40% in 2015, and it is still increasing.

An improved method for assessing vegetation cooling service in regulating thermal environment: A case study in Xiamen, China

Quantitatively evaluating vegetation cooling service has become an important issue in current ecosystem service assessment, especially for urban area. Based on a previous method proposed on the energy exchanging theory, this study developed an improved method to generate a spatially explicit evaluation of the vegetation cooling service by introducing fractional vegetation cover (FVC) and the daily length of vegetation cooling service provision. Using remote sensing data from Landsat-8 and MODIS-Terra observations and field measurements from local meteorological stations, the method was successfully applied in Xiamen, a city located on the southeastern coast of China. The results showed that surface elevation and FVC had profound impacts on the length of vegetation cooling service provision and the vegetation cooling ability, respectively. For the vegetation surfaces of total 799.48 km2 in Xiamen, the annual heat absorption was 2.73 × 109 MJ/a in 2015 with an average length of cooling service provision of 1954.04 h. A more reasonable spatial distribution of vegetation heat absorbing capacity can be found with the differences not only among different vegetation types but also within the same vegetation type. Thus, this study emphasized the impacts of vegetation coverage and cooling length on providing cooling service, which has practical implications for vegetation planning in urban areas.

Identifying Public Transit Commuters Based on Both the Smartcard Data and Survey Data: A Case Study in Xiamen, China

Understanding the travel patterns of public transit commuters was important to the efforts towards improving the service quality, promoting public transit use, and better planning the public transit system. Smartcard data, with its wide coverage and relative abundance, could provide new opportunities to study public transit riders’ behaviors and travel patterns with much less cost than conventional data source. However, the major limitation of smartcard data is the absence of social attributes of the cardholders, so that it cannot clearly extract public transit commuters and explain the mechanism of their travel behaviors. This study employed a machine learning approach called Naive Bayesian Classifier (NBC) to identify public transit commuters based on both the smartcard data and survey data, demonstrated in Xiamen, China. Compared with existing methods which were plagued by the validation of the accuracy of the identification results, the adopted approach was a machine learning algorithm with functions of accuracy checking. The classifier was trained and tested by survey data obtained from 532 valid questionnaires. The accuracy rate for identification of public transit commuters was 92% in the test instances. Then, under a low calculation load, it identified the objectives in smartcard data without requiring travel regularity assumptions of public transit commuters. Nearly 290,000 cardholders were classified as public transit commuters. Statistics such as average first boarding time and travel frequency of workdays during peak hours were obtained. Finally, the smartcard data were fused with bus location data to reveal the spatial distributions of the home and work locations of these public transit commuters, which could be utilized to improve public transit planning and operations.

Public Transit Loyalty Modeling Considering the Effect of Passengers’ Emotional Value: A Case Study in Xiamen, China

To better sustain passengers’ loyalty towards bus service, this paper addressed the modeling of the public transit loyalty by the use of structural equation model. As a novel hypothesis, the emotional value was considered to have effects on the perceived value of bus services in this study, which reflected the degree of passengers’ emotional dependence on the public transit. Specifically, in order to better assess the loyalty, seven unobserved variables were measured to construct the structural model, namely, “service guarantee,” “operational services and efficiency,” “emotional value,” “perceived value,” “expectation,” “satisfaction,” and “loyalty.” The goodness-of-fit of the model was estimated and evaluated by using the survey data harvested from Xiamen, China. Besides, the index score of variables was also computed to help determine targeted approaches to better improve the level of bus service. The results indicated that the time cost and the monetary cost actually had no effects on the perceived value of users in the case study. At the same time, however, it also proved that passengers’ emotional value towards the public transit indeed affected passengers’ perception of the service value. In addition, whether users’ perceived value was as expected determined how much passengers satisfied with the service. Regarding the index score of variables, it indicated a great dissatisfaction of passengers towards the current bus service. Unexpectedly, the score of loyalty even still retained a relatively high level, which reflected continue-to-use willingness of passengers. It implied that being subject to economic conditions and other factors, passengers were captive and had to continue relying on the public transit, in spite of their dissatisfaction. As for the improvement direction of bus services, targeted approaches should be determined to improve the quality of bus service, regarding the aspects of “condition of facilities in the bus,” “driving stability and comfort,” “vehicle speed,” and “safety.”