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Forest carbon sink efficiency refers to the efficiency of input-output indicators related to carbon sinks. This paper studies carbon sink efficiency from the perspective of resource allocation; guides the optimal allocation of resources; and selects forestry employees, forestry investment amount and afforestation area as input indicators; the forest carbon sink efficiency in China is calculated and analyzed based on a data envelopment analysis model by converting the forest volume into the forest carbon sink through the volume expansion factor method. The grey prediction model is used to estimate the change in the input indicator, and the production possibility set is constructed with the input indicator before and after the change and the current output indicator. The efficiency of the decision units before the change is calculated, and through the comparison of efficiency, the conditions of forest carbon sink increase in 15 provinces are obtained. The optimal allocation of the output indicator is calculated based on the inverse data envelopment analysis model. The largest increase in forestry carbon sink is 169,362 megatons in Guangdong, and the smallest is 619 megatons in Tianjin. Finally, some suggestions for the path of forest carbon sink increment are put forward. [ABSTRACT FROM AUTHOR]

The coordination and stability of the regional economy (RE) and ecological quality (EQ) are essential for the synergistic development of the Beijing–Tianjin–Hebei urban agglomeration (BTH). In this paper, based on remote sensing data and economic statistics data, this paper analysed the current situation and evolution of the RE and EQ in the BTH region. Based on the coupled coordination degree (CCD) model, this paper has developed an evaluative framework and quantifies the spatiotemporal coupled coordination of the RE and EQ in the BTH region from 2000 to 2020. The results show that: (1) in 2020, the GDP of the poverty-stricken counties (PSCs) around BTH accounted for 4.57% of the total BTH region, and the area of high-quality ecosystems, Net Primary Productivity (NPP), soil conservation, water conservation, and sand fixation accounted for more than 40% of the total BTH region; (2) the GDP growth of the PSCs accounted for 4.45% of the total growth in BTH, the reduced area of high-quality ecosystems accounted for 21.04%, and the increase in NPP, soil conservation, water conservation, and sand fixation accounted for more than 40% of the total growth in the BTH region; (3) the CCD of the RE and EQ in the BTH region showed a tendency to increase, but the gap between the regions gradually expanded, and the development type changed from a lagging RE to a lagging EQ, in which the coupled coordination grade of the PSCs was in a dissonance stage for a long time, and the level of economic development had to improve. Deepening the understanding of the spatiotemporal coupling relationship between the RE and EQ and adopting appropriate development policies is of great significance for achieving the coordinated and integrated development of the BTH region. [ABSTRACT FROM AUTHOR]

The Sino–U.S. Treaty of Tientsin (1858), for the first time in history, included an article to ensure the toleration of Protestantism in China, i.e., the Toleration Article. The man behind the article was S. Wells Williams (1812–1884), an interpreter of the U.S. Legation and a former missionary, who negotiated with Chinese officials directly. Williams produced the Chinese version of the clause and its official English translation which led to controversies, for it was deemed unfaithful and humiliating to the Christian communities. This paper revisits this important episode in the history of Protestantism in China. Using first-hand archival materials, it reveals how Williams was forced to "mistranslate" the article in order to satisfy both parties. It further discusses the reasons behind the missionaries' criticism, which placed Williams in the center of clashes between religious and political interests. Through Williams' case, the paper foregrounds the crucial roles and difficult situations of missionary translators in diplomatic incidents that shaped the history of Christianity in China. More importantly, it highlights the conflicting interests and ideas in early Sino–U.S. diplomacy and shows how missionary translators worked to mediate the dilemma between evangelism and politics in 19th-century China. [ABSTRACT FROM AUTHOR]

The snow-shaped distribution network (SDN) is a cable distribution network composed of eight (or six) 10 kV feeders from four (or three) substations in a regular connection. Compared with the traditional 10 kV distribution network, SDN can support a wide range of load transfer among six or eight feeders. Aiming at the problem of load spatial-temporal unbalanced condition caused by the integration of distributed generators (DGs) and different load types in different feeders, this paper proposes a dynamic reconfiguration strategy for load balancing in SDN considering DGs and energy storage system (ESS). Firstly, the basic structure of SDN is analyzed and the power flow model for its dynamic reconfiguration is developed. Secondly, the dynamic reconfiguration optimization model for load balancing in SDN considering DGs and ESS is proposed to utilize the load transfer capability to mitigate the load unbalanced condition and reduce active power loss. Thirdly, the original nonconvex model is converted into a mixed-integer second-order cone programming (MISOCP) model by applying the second-order cone relaxation and the big-M method, which is solved by CPLEX solver. Finally, the effectiveness of the proposed model and method are verified by an actual case in Tianjin and IEEE 33-node system. The analysis results show that the proposed method can significantly alleviate the load unbalanced spatial-temporal distribution and improve the economic efficiency by regulating the operation of SDN including ESS optimization and dynamic reconfiguration. [ABSTRACT FROM AUTHOR]

In response to the volatility of photovoltaic power generation, this paper proposes a short-term photovoltaic power generation prediction model (HWOA-MVMD-TPA-TCN) based on a Hybrid Whale Optimization Algorithm (HWOA), multivariate variational mode decomposition (MVMD), temporal pattern attention mechanism (TPA), and temporal convolutional network (TCN). In order to improve the accuracy of photovoltaic power generation forecasting, HWOA-MVMD is used for data decomposition, the Minimum Mode Overlap Component (MMOC) is used as the objective function, the photovoltaic power generation sequence is decomposed into finite Intrinsic Mode Functions (IMFs) according to the optimal solution, and the training set is formed with key meteorological variable data such as total radiation (unit: W/m2), ambient temperature, and humidity. Then, the TPA-TCN model is used to train the sub-sequences, the final predicted values are obtained after superimposing the reconstruction of the prediction results, and finally the prediction error of the photovoltaic power generation data is studied. The proposed method is applied to real photovoltaic power generation data from a commercial center in Tianjin and is compared with HWOA-MVMD-BiLSTM, GWO-MVMD-TPA-TCN, and TPA-TCN prediction models. The simulation results demonstrate that the MAE value of the forecast method proposed in this paper is 1.95 MW and the RMSE value is 2.55 MW, which can be reduced by up to 33.74% and 38.85%, respectively. The HWOA-MVMD-TPA-TCN-based short-term photovoltaic power generation prediction model presented in this paper achieves higher prediction accuracy and superior performance, serving as a valuable reference for related research. [ABSTRACT FROM AUTHOR]

Determining whether the supply–demand matching (SDM) of urban public health resources is reasonable involves important issues such as health security and the rational use of resources. Using the central urban area of Tianjin as the research area, this paper used the Gaussian-based 2-step floating catchment area method (Ga2SFCA), combined with multi-source data, and comprehensively considered public medical, natural, and physical resources to evaluate the SDM of single-category and integrated public health resources in the research area. The results showed the following: (1) there was a good fit between supply and demand for public medical and natural health resources in Tianjin's central urban area. For public physical health resources, there was a poor fit between supply and demand; the population in the supply insufficient and scarce areas for 82.78% of the total and was mainly distributed in the marginal areas of the four districts around the city and the six districts of the inner city. (2) For integrated public health resources, the degree of SDM was generally good. It had a circular structure that gradually shrank from the core to the edge. In order to promote the supply–demand balance of urban public health resources, this paper proposed three strategies involving three aspects: the supply, accessibility, and demand of urban public health resources. These strategies involve the service supply level, urban traffic network and slow traffic, development intensity, and population scale. [ABSTRACT FROM AUTHOR]

To help related operators to allocate and dispatch the number of bike-sharing and provide good guidance for setting up electronic fences, this paper proposes a spatiotemporal graph convolution network prediction model (SGCNPM) with multiple factors to enhance the accuracy of predicting the demand for bike-sharing. First, we consider time, built environment, and weather. We use a multigraph convolution network (GCN) to model the built environment, utilize a long short-term memory (LSTM) network to extract temporal features, and utilize a fully connected network (FCN) to model weather influence. We construct SGCNPM which can effectively fuse GCN, LSTM, and FCN, thus creating a prediction method considering the influence of multiple factors. The results of the real case in Tianjin, China, show that the proposed model can perform well in improving prediction accuracy. Also, we analyze the influence of factors on model prediction results in different periods. [ABSTRACT FROM AUTHOR]

The South-to-North Water Diversion Project (SNWDP) is believed to drive the next phase of sustainable productivity growth, meeting growing water demand, so as to address increasing environmental sustainability challenges. The Middle Route of SNWDP is regarded as an extremely large long-distance inter-basin water diversion project, which has benefited Henan, Hebei, Tianjin and Beijing since 2014 with great sustainable changes to the cities, groundwater, ecological environment, industrial structure and social development of the beneficiary areas. Taking the number of industrial enterprises above designated size (IEDS) in the water-receiving areas as the research object, this paper takes the year of policy implementation 2014 as the basic time point, evaluating the change of the number of IEDS in the beneficiary areas of the Middle Route of SNWDP through difference-in-difference model. The results show that: (1) The Middle Route of SNWDP promotes the additional growth of the number of IEDS in the beneficiary areas. (2) When the Middle Route of SNWDP promotes the growth of the number of IEDS in beneficiary areas, there is no regional difference for regions with different development levels. (3) The reasons why the Middle Route of SNWDP contributes to the additional growth of the number of IEDS are composed of promoting mixed ownership reform of enterprises in beneficiary areas, increasing water supply and increasing population. However, the Middle Route of SNWDP has not had a significant impact on the traditional total factor productivity or the components of production factors, technology and capital. From the final outcome, the South-to-North Water Diversion Project has played a facilitating role in the sustainable development of large-scale enterprises in the water-receiving areas. [ABSTRACT FROM AUTHOR]

As a politically and culturally important city cluster, the Beijing–Tianjin–Hebei (BTH) region is the most prominent area in China where the imbalance between the supply and demand of water resources restricts the sustainable and healthy development of the regional social economy. In the context of global warming, research into water demand prediction that takes climate change into consideration would be more in line with the strategic goal of the low-carbon sustainable development of future cities. At the same time, the prediction of agricultural water demands against a background of climate change is urgently needed, while industrial water consumption is weakly correlated with climate change, an investigation of the statistical relationship between the two is needed. Thus, in this paper, future climate data from the BTH region under the scenarios RCP2.6, RCP4.5 and RCP8.5 were generated using a statistical downscaling model, and then coupled with agricultural and industrial water demand prediction models to simulate and analyze the impact of climate change on the agricultural and industrial water demands, respectively. The results show that during the forecast period (2020–2035), the reference crop evapotranspiration (ET0) growth rates in the Beijing, Tianjin and Hebei areas under the RCP2.6 scenario are 1.438 mm·a−1, 1.393 mm·a−1 and 2.059 mm·a−1, respectively. Under the RCP4.5 scenario, they are 2.252 mm·a−1, 2.310 mm·a−1 and 2.827 mm·a−1, respectively. Under the RCP8.5 scenario, they are 3.123 mm·a−1, 2.310 mm·a−1 and 2.141 mm·a−1, respectively. Furthermore, under each climate scenario, the increase in evapotranspiration in the Hebei area is the largest, followed by that in the Tianjin area, and that in the Beijing area is the smallest. For water consumption per CNY 10,000 of industrial added value during the forecast period, under the three different climate scenarios, a downward trend is seen in the Beijing area, with rates of 0.158, 0.153 and 0.110, respectively, but in the Tianjin area, there is an upward trend, with an upward tendency in rates of 0.170, 0.087 and 0.071, and an upward trend in the Hebei area, with an upward tendency in rates of 0.254, 0.071 and 0.036, respectively. This study will help the BTH region to rationally allocate agricultural and industrial water against the background of future climate change, and strengthen the coordination and cooperation between the different regions to promote the healthy and sustainable development of the cities. [ABSTRACT FROM AUTHOR]

The production connection is a crucial component of the Inter City Association. An urban network based on the enterprise perspective better reflects the structural characteristics of regional cities. Based on data gathered from the headquarters and branches of the listed manufacturing enterprises in 2020, this paper analyzes the county-level administrative units in the Beijing-Tianjin-Hebei region of China. Using the subordinate connection model and the social network analysis method, this paper examines the spatial structural characteristics and factors of urban networks in the Beijing-Tianjin-Hebei region. The results suggest that resource allocation in the Beijing-Tianjin-Hebei region is unbalanced, with a significant difference in urban radiation and agglomeration capacity. As the administrative centers, Beijing, Tianjin, and Shijiazhuang show a strong ability to allocate resources within the network. The overall network density in the region was shown to be relatively low, with the main links being of low or medium level. The urban network is defined by the network connection led by Beijing and Tianjin with Beijing-Tianjin-Tangshan and Beijing-Baoding-Shijiazhuang as the main axis. These cities exhibit a "dense southeast and sparse northwest" pattern. From a hierarchical perspective, high-level network connections are based mainly on spatial proximity. Analyzing the agglomerative subgroups, the study found that the inner and outer connections of the core subgroups were relatively high. Semi-marginal subgroups generally accepted the radiation of core subgroups, while marginal subgroups had little connection with other subgroups in the region. The results of the QAP analysis show that the administrative relationship, spatial distance, city size difference, economic development level difference, industrial structure difference, and labor cost difference have a significant influence on the urban network of the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

The Beijing-Tianjin-Hebei integration plan rose to the status of a national-level strategy in 2014. This paper provides a deep analysis of the Beijing-Tianjin-Hebei area's inter-city commuter big data. This research analyzed the overview of spatial structure, polycentric structure, hierarchical structure and clustering characteristics of the BTH based on network analysis methods. It reveals that the inter-city commuter network exhibits clear polycentric characteristics, with Beijing acting as the central hub. The degree of network correlation between cities in Tianjin and Hebei is notably low, indicating that the flow of people primarily revolves around Beijing, while interactions between other cities remain limited. Therefore, it is necessary to further decentralize Beijing's non-capital core functions. The level of connectedness among the areas surrounding the Bohai Rim is not very high, and it has not developed the coastal advantage. The cooperation could be strengthed among the cities within Bohai Rim. The polycentric structure has initially taken shape, but it exhibits obvious polarization characteristics. It is necessary to strengthen the interaction of talents between cities to form secondary central units in BTH. [ABSTRACT FROM AUTHOR]

Industrial heritage creative industrial parks are an organic component of historical neighborhood buildings. According to several field visits and surveys of creative industrial parks, it has been found that the external space of some creative industrial parks does not meet the needs of the people. This research primarily investigates the critical factors influencing the usability of external spaces in these revitalization projects. Spatial syntax, a field that has seen considerable advancement in recent years, offers a more scientific approach to understanding spatial relationships. Therefore, this paper employs spatial syntax as its principal methodology. It conducts a quantitative analysis of the external spatial morphology of four creative industrial parks of industrial heritage in Tianjin. The study critically evaluates the syntactic values and identifies issues in the external spatial morphology, including a dearth of cultural elements and limited environmental richness. Furthermore, it provides recommendations for the enhancement of these external spaces. The aim is to furnish data support and strategic insights to invigorate the revitalization efforts of Tianjin's industrial heritage creative industrial parks. [ABSTRACT FROM AUTHOR]

Traffic incidents pose substantial hazards to public safety and wellbeing, and accurately estimating their duration is pivotal for efficient resource allocation, emergency response, and traffic management. However, existing research often faces limitations in terms of limited datasets, and struggles to achieve satisfactory results in both prediction accuracy and interpretability. This paper established a novel prediction model of traffic incident duration by utilizing a tabular network-TabNet model, while also investigating its interpretability. The study incorporates various novel aspects. It encompasses an extensive temporal and spatial scope by incorporating six years of traffic safety big data from Tianjin, China. The TabNet model aligns well with the tabular incident data, and exhibits a robust predictive performance. The model achieves a mean absolute error (MAE) of 17.04 min and root mean squared error (RMSE) of 22.01 min, which outperforms other alternative models. Furthermore, by leveraging the interpretability of TabNet, the paper ranks the key factors that significantly influence incident duration and conducts further analysis. The findings emphasize that road type, casualties, weather conditions (particularly overcast), and the number of motor and non-motor vehicles are the most influential factors. The result provides valuable insights for traffic authorities, thus improving the efficiency and effectiveness of traffic management strategies. [ABSTRACT FROM AUTHOR]

Port-centric intermodal transshipment hubs are significant nodes in the global freight network and are likewise the gateway to a country's external communications. It is vital to increase the service capacity of PCITHs, and it is necessary to assess the service capacity of port-centric intermodal transshipment hubs to respond to the growth of economies and global freight needs. This study provides a detailed definition of port-centric intermodal transshipment hubs through a review of relevant kinds of works from the literature and analyzes their primary functions. Based on the research perspective of sea–rail intermodal transportation, the three evaluation dimensions of service capacity of port-centric intermodal transshipment hubs are divided into radiation scale capacity, transportation connection capacity, and resource integration capacity, focusing on the functions of cargo aggregation, cargo transfer, and connection of different transportation modes. The service capacity evaluation indicators were then selected based on the three dimensions. The subjective and objective weightings were calculated by the G1 weighting method and the modified CRITIC method, and the combination weightings were determined based on game theory. The service capability of port-centric intermodal transshipment hubs was evaluated by the fuzzy matter element method, and the evaluation results were quantified by the Euclidean closeness degree. Finally, through the barrier degree model, the current indicators of PCITHs that urgently need improvement were explored, and targeted improvement suggestions are proposed in this paper. The results show that Tianjin Port has the highest service capacity, followed by Ningbo Zhoushan Port. The port rail dedicated line mileage is the most critical area that needs attention in Ningbo Zhoushan Port and Qingdao Port. Tianjin Port needs to improve the container sea–rail transportation volume, while Guangzhou Port and Xiamen Port need to improve the sea–rail container handling capacity. [ABSTRACT FROM AUTHOR]

CO2 is the main greenhouse gas. Urban spatial development, land use, and so on may be affected by CO2 and climate change. The main questions studied in this paper are as follows: What are the drivers of CO2 emissions of expanding megacities? How can they be analyzed from different perspectives? Do the results differ for megacities at different stages of development? Based on the XGBoost model, this paper explored the complex factors affecting CO2 emissions by using data of four Chinese megacities, Beijing, Tianjin, Shanghai, and Chongqing, from 2003 to 2017. The main findings are as follows: The XGBoost model has better applicability and accuracy in predicting carbon emissions of expanding megacities, with root mean square error (RMSE) as low as 0.036. Under the synergistic effect of multiple factors, population, land size, and gross domestic product are still the primary driving forces of CO2 emissions. Population density and population become more important in the single-factor analysis. The key drivers of CO2 emissions in megacities at respective developmental stages are different. This paper provides methods and tools for accurately predicting CO2 emissions and measuring the critical drivers. Furthermore, it could provide decision support for megacities to make targeted carbon-emission-reduction strategies based on their own developmental stages. [ABSTRACT FROM AUTHOR]

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This paper explores how ideas and practices of elder-care may be changing for the new Chinese middle class. This paper draws on in-depth interviews with the members of different generations of ten middle class families in the Chinese city of Tianjin. It explores how increased resources but also increased pressure are affecting the care of older people and the expectations around elder-care. Thematic analysis of transcripts entered into NVIVO revealed three findings. Firstly, that the generation born in the 1950s and 1960s are often negotiating their care responsibilities between their parents and their grandchildren. Secondly, the only viable elder-care solution for many families is to buy in support from an unregulated market-based home care sector. Thirdly driven by an increasingly postmodern culture, filial piety may be changing from a normative expectation to a set of new practices based on familial reciprocity. The paper concludes by reflecting on the issues that will arise from the proposed raising of the retirement age in China, and the increasing geographic dispersal of generations. Flexible working policies as well as investment in a regulated home care sector are recommended as solutions to be explored. [ABSTRACT FROM AUTHOR]

With the accelerating urbanization process in China, the extensive economic growth model with high energy consumption and high pollution aggravates atmospheric environmental pollution and restricts the sustainable development of the social economy. The Beijing–Tianjin–Hebei region has the most severe haze pollution and the most acute contradiction between resources, environment and economic development. Based on the physical coupling theory, this paper constructs a coupling coordination degree model of the economy, environment and high haze pollution industries, such as the thermal power industry. Through literature analysis and expert investigation of the economic, industrial and environmental data of the Beijing–Tianjin–Hebei region from 2006 to 2018, the coordinated development of the economy, environment and high haze pollution industries, such as the thermal power industry, in the above region, was dynamically monitored. The monitoring results show that the development level of the Beijing, Tianjin and Hebei region is significantly different, and the three subregions have not entered the stage of coordinated development. Moreover, since 2015, they have been in a bottleneck period of development and have not achieved a higher level of progress. The three subregions have different advantages and restraining factors. For example, the backward level of Hebei's economy and high haze pollution industries, such as the thermal power industry, restrict the coordinated development of the region as a whole. Only by accelerating the high-quality development of the Hebei economy can we break through the bottleneck of the development of Beijing, Tianjin and Hebei. [ABSTRACT FROM AUTHOR]

Urban fire disasters are one of the most frequent disasters that threaten public safety and social development in cities. Most urban fire disasters feature dynamics and processes. The locations, time, meteorological conditions and surroundings of each fire incidents are diverse, besides the traffic conditions around the fire place would be changing dynamically. At present, there is no unified modeling language to describe urban fire incidents, which makes it difficult to obtain experience from historical cases and hard to describe. This paper used the Event pattern Markup Language (EML) to model urban fire incidents from an observation perspective based on MetaObject Facility (MOF) framework, designed and implemented an urban fire incident modeling prototype. It can realize the information description of urban fire disasters, and provide descriptions of different observation missions during the process of the fire incidents. The detailed description of the process allows multiple observations based on the expression of EML to be performed, and offer evidence for emergency response phase and post-mortem archiving. The real data of the "12.1" major fire in Tianjin, China in 2017 was used as a use-case to show the modeling results of the entire fire incident in four phases – mitigation, preparedness, response, and recovery. The results show that this modeling method proposed in this paper can represent the dynamic information of urban fire incidents and achieve the dynamic modeling of urban fire incidents. [ABSTRACT FROM AUTHOR]

The profound impacts of severe air pollution on human health, ecological balance, and economic stability are undeniable. Precise air quality forecasting stands as a crucial necessity, enabling governmental bodies and vulnerable communities to proactively take essential measures to reduce exposure to detrimental pollutants. Previous research has primarily focused on predicting air quality using only time-series data. However, the importance of remote-sensing image data has received limited attention. This paper proposes a new multi-modal deep-learning model, Res-GCN, which integrates high spatial resolution remote-sensing images and time-series air quality data from multiple stations to forecast future air quality. Res-GCN employs two deep-learning networks, one utilizing the residual network to extract hidden visual information from remote-sensing images, and another using a dynamic spatio-temporal graph convolution network to capture spatio-temporal information from time-series data. By extracting features from two different modalities, improved predictive performance can be achieved. To demonstrate the effectiveness of the proposed model, experiments were conducted on two real-world datasets. The results show that the Res-GCN model effectively extracts multi-modal features, significantly enhancing the accuracy of multi-step predictions. Compared to the best-performing baseline model, the multi-step prediction's mean absolute error, root mean square error, and mean absolute percentage error increased by approximately 6%, 7%, and 7%, respectively. [ABSTRACT FROM AUTHOR]

With the rapid development of the global economy and trade, the number of ships serving ports in China is increasing continuously. Port traffic is becoming busier, and ship behavior is more complex and changeable. The analysis of ship behavior patterns in port waters has become an urgent problem to improve the efficiency and safety of port areas. In this paper, through the full integration of ship trajectory and port geographic information, the behavior chain of a single ship across the whole process of entering and exiting the port is identified. The traffic complexities and dynamics can be further analyzed by grouping the movement patterns of large ships. Based on graph theory, the port areas can be described as a transportation network in which functional areas are nodes and fairways between different areas are edges. The traffic can be analyzed through the network structure characteristics, such as node degree, node weight, and edge weight, and by their similarities and differences. This methodology provides a quantitative analysis for exploring the behavior patterns of large ships as well as the various traffic complexities. A case study in Tianjin Port has been conducted to verify the proposed model. The results show that it can accurately analyze a ship behavior's regularity, occasion, and correlation. It provides a theoretical reference for the port to schedule and formulate emergency plans. [ABSTRACT FROM AUTHOR]

Urban space architectural color is the first feature to be perceived in a complex vision beyond shape, texture and material, and plays an important role in the expression of urban territory, humanity and style. However, because of the difficulty of color measurement, the study of architectural color in street space has been difficult to achieve large-scale and fine development. The measurement of architectural color in urban space has received attention from many disciplines. With the development and promotion of information technology, the maturity of street view big data and deep learning technology has provided ideas for the research of street architectural color measurement. Based on this background, this study explores a highly efficient and large-scale method for determining architectural colors in urban space based on deep learning technology and street view big data, with street space architectural colors as the research object. We conducted empirical research in Jiefang North Road, Tianjin. We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. Based on K-Means clustering model, we identified the colors of the architectural elements in the street view. The accuracy of the building color measurement results was cross-sectionally verified by means of a questionnaire survey. The validation results show that the method is feasible for the study of architectural colors in street space. Finally, the overall coordination, sequence continuity, and primary and secondary hierarchy of architectural colors of Jiefang North Road in Tianjin were analyzed. The results show that the measurement model can realize the intuitive expression of architectural color information, and also can assist designers in the analysis of architectural color in street space with the guidance of color characteristics. The method helps managers, planners and even the general public to summarize the characteristics of color and dig out problems, and is of great significance in the assessment and transformation of the color quality of the street space environment. [ABSTRACT FROM AUTHOR]

Many free-floating bicycle-sharing (FFBS) operators in cold region cities will put bicycles in warehouses and suspend services in winter due to factors such as safety and maintenance costs, resulting in the corresponding travel demand no longer be met. Considering the short-distance and green travel characteristics of FFBS, the flexible bus, as a sustainable demand-responsive transit service, is a suitable alternative transportation mode. To operate such a flexible bus system, service area and operation time planning is a key stage, however, the planning methods in relevant studies are not suitable for this research scenario. In view of the above, this paper proposed a data-driven method to determine the service area and operation time of flexible buses based on FFBS data. Firstly, an FFBS trip path reconstruction algorithm consists of fine-grained road network modelling and trajectory matching is proposed. Then, in the defined time slice, incorporating the idea of ride-sharing routes generation, according to the density-based clustering principle and considering topology between trajectories, a path clustering algorithm PATHSCAN is developed to generate the one-day path clusters. After that, a frequent pattern mining algorithm is applied to the multiday path clusters, and frequent pattern results with spatio-temporal correlation will be merged into the final service area. The generated planning results will cover ride-matching trips and high-frequency riding paths. Detailed application analysis and verification are carried out by using the real data from Tianjin, China. Through the evaluation and verification under the relatively limited experimental data set, the proposed data-driven method shows ideal planning results. Flexible bus service can supplement the green short-distance travel mode after the suspension of FFBS and can avoid FFBS travel demands switched to unsustainable transportation modes to a large extent. This study will contribute to urban sustainable transportation development and improving greenness. [ABSTRACT FROM AUTHOR]

Concerns about the environment and renewable energy are growing. Improving the perception of renewable energy in urban and rural households is required to promote green development and to learn about consumer preferences for renewable energy based on the gradual reduction in financial subsidies for photovoltaic (PV) power generation. This paper aims to estimate the willingness of consumers to pay for a Household PV system and explores the factors that affect consumers' product selection, which is conducive to optimizing Household PV products and policies and is important for achieving the carbon peaking and carbon neutrality goals. Using a discrete choice model, this paper surveyed 765 urban and rural residents without installing Household PV systems in Tianjin, China. Subsequently, the respondents' attribute preferences and willingness to pay (WTP) for a Household PV system were analyzed using a logit regression analysis model. The influence of respondents' socio-economic characteristics on WTP was analyzed. The empirical results showed that (1) price significantly impacts consumers' PV adoption behaviors and consumers tend to choose cheaper PV products; (2) consumers are more willing to pay for the after-sales service (3959 USD/level) and traceable information (2176 USD/level), indicating their preference for these two attributes when considering options; (3) socio-economic variables, including gender and the number of minor children (i.e., children under the age of 18) at home, significantly impact consumers' PV adoption behaviors. Males and consumers without minor children at home will pay more attention when selecting the products. Our research findings will provide valuable insights into policy making and the wide-ranging use of Household PV systems. [ABSTRACT FROM AUTHOR]

An upsurge in Taiwan-based Mazu temple buildings has been observed in China (Tianjin, Kunshan, and Xiamen, etc.) recently. This paper applies qualitative research methods, including participatory observation and semi-structured interviews, to explore the development of Mazu temples in Tianjin, Kunshan, and Xiamen, China in terms of cross-regional connectivity, materiality, and cross-regional locality, to explore the process of transplantation and construction in the mainland. This paper finds that Mazu culture is a reproduction of the vision of "one race one culture" in the cultural space, and this spatial reproduction is realized through cross-strait religious and cultural exchanges. Informed by the perspective of the political and cultural context, three interconnected dimensions—cross-regional connectivity, materiality, and cross-regional locality—have influenced why, where, and how Taiwan Mazu temples have been transplanted and constructed. This kind of hybrid locality is an integration of urban space and religion, as well as an organic, complex process that integrates religious functions, local politics, and the cultural economy. With the ingenious localization efforts of Taiwanese businessmen, these new Mazu temples promote homogenization in the sacred space and create a unique mixed locality—a more-than-state. [ABSTRACT FROM AUTHOR]

This paper takes the layout of innovation industrial parks in Tianjin City, the economic center of circum-Bohai Sea region, as the research object. At first, based on relevant theoretical research, the paper proposes that the design of the layout evaluation indicators of the innovation industrial parks should follow the system optimization principle and the availability principle. Second, after a discussion on the alternative calculation methods, this paper selects the factor analysis and the entropy method as the main calculation methods, and investigates the inadequacies of these methods. Third, a corresponding evaluation and analysis indicator system is designed; 4 first-level indicators of location factor, infrastructure, innovation ability and social contribution, and 12 second-level indicators are devised to form an evaluation indicator system for layout of the innovation industrial parks in Tianjin; after calculation, objective comprehensive evaluation results are obtained and interpreted. Fourth, multi-criteria and multi-dimensional comparative analysis is carried out to analyze the development of these innovation industrial parks in Tianjin; and the conclusion is that the location advantage and the development status are the main factors affecting the layout of the innovation industrial parks in coastal areas. At last, from the perspective of national and related industries, combined with the results of evaluation and analysis, this paper proposes comprehensive spatial layout recommendations for the problems existing in the layout of innovation industrial parks in Tianjin from aspects of infrastructure, location advantage, and future development trends, etc. [ABSTRACT FROM AUTHOR]

The development of Xiongan New Area in Hebei Province, China, as a significant national choice, has considerable strategic significance for the integrated growth of Beijing, Tianjin, and Hebei. This paper proposes a cloud model for the suitability evaluation of the construction of Xiongan New Area based on entropy weight analysis, taking into account the geological conditions, groundwater environment, environmental geological problems, and other factors of the suitability of image city development. According to the research, the suitability evaluation findings for the project building employing the cloud model are in strong accord with those of the traditional model and have some application potential. The evaluation's findings indicate that the project construction in Xiongan New Area is acceptable, with suitable and relatively suitable sites making up 81.4% of the total area and excellent circumstances for project development, construction, and usage. This study offers helpful direction for Xiongan New Area's urban land-space design and serves as a useful point of comparison for studies looking at the viability of other deep Quaternary Plain region engineering buildings. [ABSTRACT FROM AUTHOR]

Wetlands form a crucial component of ecosystems, and wetland restoration serves as an effective strategy for promoting sustainable urban development. Spatial support is essential for wetland restoration, meaning that research on wetland spatial planning is of considerable importance. Existing studies on wetland spatial planning primarily focus on the analysis of wetland spatial distribution characteristics, with limited exploration of wetland spatial relationships. This paper aims to explore the potential of utilizing both spatial distribution characteristics and spatial relationships to identify wetland spatial issues, thereby facilitating the formulation of wetland spatial planning strategies. Using Tianjin City as a case study, this research applies nearest neighbor analysis, the geographic concentration index, the Gini index, and kernel density analysis to identify the spatial distribution characteristics of wetlands in Tianjin. Additionally, spatial autocorrelation analysis and connectivity analysis are employed to identify the interrelationships among wetlands in Tianjin. Based on the results derived from the analysis of spatial distribution characteristics and spatial relationships, wetland spatial planning strategies are proposed. The effectiveness of these strategies is validated using methods that consider both spatial distribution characteristics and spatial relationships. The findings reveal that, although wetlands in Tianjin are widely distributed, large wetland patches are primarily concentrated in areas with abundant water resources, while the six districts within the city have few or no large patches of wetlands. The spatial distribution of wetlands is highly uneven, exhibiting patterns of high–high aggregation and low–low aggregation. The number of connecting paths between wetland patches is relatively low, indicating a generally low overall connectivity. While medium-sized and larger wetland patches maintain the connectivity of existing wetlands in Tianjin, small wetlands that serve as stepping stones are lacking. Following the implementation of planning strategies, there would be an increase in the wetland area in Tianjin, accompanied by significant improvements in the spatial distribution pattern and spatial relationships of the wetlands. [ABSTRACT FROM AUTHOR]

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Climate is closely related to human life, food security and ecosystems. Forecasting future climate provides important information for agricultural production, water resources management and so on. In this paper, historical climate data from 1962–2001 was used at three sites in Tianjin Baodi, Tianjin and Tanggu districts as baseline and the model parameters were calibrated by the Long Ashton Research Station Weather Generator (LARS-WG). 2m-temperatures in 2011–2020 were verified under two scenarios, representative concentration pathway (RCP) 4.5 and RCP8.5 in different atmospheric circulation models with optimal minimum 2m-temperatures at the three sites. From 2031–2050, Tianjin will be using more moderate minimum 2m-temperatures in future simulations. Support vector machines (SVM) were used to optimize the simulated data to obtain more accurate future maximum and minimum 2m-temperatures for the three sites. The results showed that the determinant coefficient of LARS-WG simulation was 0.8 and SVM optimized determinant coefficient was 0.9 which greatly improved the prediction accuracy. The minimum and maximum future 2m-temperatures optimized under European Community Earth System Model (EC-EARTH) were relatively low and the same future 2m-temperatures optimized under Hadley Centre Global Environment Model Earth System (Had-GEM2-ES4) were high especially in the RCP8.5 scenario which simulated 2051–2070 climate. The SVM optimization showed that the maximum and minimum 2m-temperatures were in general agreement with the original simulation values. [ABSTRACT FROM AUTHOR]

Sustainability assessment of agricultural system is vital to ensure improvements in agricultural sustainability abilities. Aiming at the comprehensive evaluation of agricultural sustainability, this paper builds an input and output indicator system, from the security–economy–society–ecology dimension. Then, based on super-efficiency slack-based model and coupling model, an integration model is developed and employed to measure the regional agricultural sustainability in 30 Chinese provinces in 2017. The major findings are as follows. First, significant regional disparities are found across the provinces, Beijing and Tianjin have the highest agricultural sustainability efficiencies at 0.902 and 0.957, respectively, and Xinjiang and Gansu only achieve 0.543 and 0.539, respectively. Second, China's eastern regions had the best agricultural sustainability efficiencies, followed by the central regions and the western regions. Suggestions are provided to improve the agricultural sustainability efficiency. [ABSTRACT FROM AUTHOR]

It was an important step to understand the evolution of urban forms by clarifying the development process of spatial forms over time. In this step, the application of historical maps with rich spatial and temporal information provided an opportunity to increase the objectivity, accuracy, and repeatability of the research. On the other hand, efficient extraction of spatiotemporal information from historical maps as a basis for subsequent analysis remained a common bottleneck in the current time. What could be done to effectively extract urban spatial elements from historical maps? How could spatial elements be translated to obtain quantified data that could be used for spatiotemporal analysis? In this study, we selected historical maps and archival illustrations of the former British Concession area of Tianjin, China, as research materials to explore the extraction and digital translation methods of urban spatial elements for analyzing the evolution of urban spatial form based on historical maps. This method consisted of loading the map, selecting the registration and calibration point, correcting residual, and saving the path of calibration. The study discussed the specific operation of these steps. In addition, based on this method, this paper analyzed the road network, water area, bridges, and gardens in the former British Concession area of Tianjin, China, to verify the feasibility and accuracy of this method. This method was expected to advance the study of urban spatial morphological evolution and its mechanism with rich data of historical maps. [ABSTRACT FROM AUTHOR]

Although urban expansion statistics have been widely carried out, large-scale and rapid monitoring is still worth doing in order to improve the efficiency of statistics, as well as make up for the omissions and deficiencies of construction expansion statistics with multi-year intervals. This paper presents a study of urban expansion in the Beijing–Tianjin–Hebei plain based on ALOS Global Digital Surface Model "ALOS World 3D-30 m" (AW3D30 DSM), Shuttle Radar Topography Mission (SRTM) DSM, and Landsat 7 ETM+ images. Through the evaluation of errors and the elimination of non-building changes, a relatively objective result is derived. The neighborhood block statistics of the construction height expansion reveal that from 2000 to 2009, the largest centralized construction expansion mainly occurred between the Second Ring Road and the Fifth Ring Road of Beijing, followed by Yizhuang, Shunyi, Tianjin Central City, and Langfang. Zonal statistics also show a significant imbalance in the expansion of construction in the counties of the Beijing–Tianjin–Hebei plain. For example, Chaoyang, Dongcheng, Xicheng, Xuanwu, Chongwen, Nankai, Heping, and Hexi have a larger construction expansion; however, other counties present a relatively slow rate of building expansion. Furthermore, the correlation coefficient between the statistical average building height expansion per unit area (ABHE, by our method) and the actual average completed building floor space per unit area (ACBFS) derived from the Beijing Statistical Yearbook (BSY) is 0.9436, which proves that this method is feasible. With the continuous improvement of DSM data quality in the future, the method proposed in this paper can provide rapid and large-scale statistics to study more urban construction expansion in the world. [ABSTRACT FROM AUTHOR]

With the development of 3D technology, based on the perspective of 3D video, this paper analyzes the principle of 3D video, establishes the perspective model of 3D video, and discusses the modeling process in detail. Then, from the perspective of 3D video, this paper studies the three-dimensional intervention model of public art in Beijing, Shanghai, Chongqing, and Tianjin. Through the combination of public art and rural culture, the countryside can obtain vitality through art and popularize and promote rural culture and image. In general, this paper provides some ideas and experience for the research of public art in rural culture from the perspective of 3D video. [ABSTRACT FROM AUTHOR]

In weather forecasting, numerical weather prediction (NWP) that is based on physical models requires proper post-processing before it can be applied to actual operations. Therefore, research on intelligent post-processing algorithms has always been an important topic in this field. This paper proposes a model output deep learning (MODL) method for post-processing, which can improve the forecast effect of numerical weather prediction. MODL is an end-to-end post-processing method based on deep convolutional neural network, which directly learns the mapping relationship between the forecast fields output by numerical model and the observation temperature field in order to obtain more accurate temperature forecasts. MODL modifies the existing deep convolution model according to the post-processing problem's characteristics, thereby improving the performance of the weather forecast. This paper uses The International Grand Global Ensemble (TIGGE) dataset from European Centre for Medium-Range Weather Forecasts (ECMWF) and the observed air temperature of 2 m obtained from Tianjin meteorological station in order to test the post-processing performance of MODL. The MODL method applied to temperature in post-processing is compared with the ECMWF forecast, Model Output Statistics (MOS) methods, and Model Output Machine Learning (MOML) methods. The Root Mean Square Error (RMSE) of the temperature field predicted by MODL and the observed temperature field is smaller than the other models and the accuracy of the temperature difference of 2 °C (Acc) is higher, especially where the prediction time is in the first three days. The lightweight nature of MODL also makes it suitable for most operations. [ABSTRACT FROM AUTHOR]

With the development of global economy, the evaluation of industrial clusters has become an important method to scientifically analyze the advantages and disadvantages of industrial development. The current research model uses the traditional evaluation method, which leads to the problem of unsatisfactory evaluation results and low effect. This paper proposes an evaluation model based on the BP neural network combined with the LM algorithm, which has the advantages of fast convergence speed and strong application ability. The comprehensive evaluation model of industrial clusters is put forward from the comprehensive application of the scale, benefit, and 27 related evaluation indexes of industrial clusters. This paper takes Beijing, Tianjin, and Hebei industrial clusters for BP-LM evaluation and analysis, which fully illustrates the advantages of this method. The evaluation results show that the evaluation target value and the average error of the overall parity have obvious advantages compared with those of other models, which provides application guidance for local economic development and policy formulation. [ABSTRACT FROM AUTHOR]

Under the Beijing-Tianjin regional comprehensive transportation system, the flow of air passengers between multiple airports in the region is more frequent. The fundamental reason for the flow of air passengers is that there are differences in the level of service quality provided by airports and airlines in the region. Passengers' choice intention is the consumption and purchase decision of passengers on aviation services. By constructing a Logit model, this paper analyzes the degree of influence on the travel choice intention of air passengers in the Beijing-Tianjin region from five aspects: individual passenger demographic characteristics, travel purpose, ground transportation characteristics, airport operation capacity, and airport soft power. Passengers can effectively predict the choice of air travel mode in the Beijing-Tianjin region. The results show that Beijing Capital Airport is favored by business travelers; Beijing Daxing International Airport is favored by travelers because of its fast security check-through speed; for Tianjin Binhai International Airport, the convenience of getting in and out of the airport by car and the speed of airport security check-through are two significant factors. Indicators do not affect the selection of airports; reasonable follow-up arrangements when airport flights are delayed are the only significant but negatively correlated factor; the research design results provide new ideas for the analysis of passenger travel mode selection behavior in multiple airport areas, enriching the data-driven research on transportation choices. [ABSTRACT FROM AUTHOR]

Industrial upgrading and transfer is one of the three key areas in the coordinated development of Beijing-Tianjin-Hebei Region. Meetings, incentives, conferences and exhibitions (MICE) are important means of promoting industrial upgrading. Urban MICE industry, as an important carrier of event activities, become an important gripper for coordinated development of Beijing-Tianjin-Hebei Region. City exhibition space structure plays an dominant role in regional economic development, and it will greatly promote smooth implementation of the coordinated development strategy of Beijing-Tianjin-Hebei Region. In this paper, 13 prefecture-level cities in Beijing, Tianjin and Hebei were selected as research objects, and the data from 2012 to 2018 were selected to establish a gravity model of the attractiveness of MICE cities. With the help of UCINET software, the network density, centrality, cohesive subgroup and core-edge of nodes researches were obtained to analyze the spatial structure characteristics of the attractiveness of MICE cities in Beijing-Tianjin-Hebei Region. The influencing factors of the spatial characteristics of MICE city attractiveness are analyzed by using geographically weighted regression model. The results show that: (1) Beijing, as the overall core area, act as a prominent role. Beijing strengthens the attraction to the superior resources of the surrounding areas, but the network of MICE cities tends to be unbalanced. (2) Overall space forms a subgroup from a single independent subgroup to a subgroup that is spatially separated from each other and acts as an intermediary channel to connect each other, and the core region decreases from 3 to 2. Langfang was removed from the list, leaving Beijing and Tianjin as the core. (3) The influence of supporting facilities, urban environment and population factors on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is increasing gradually. The influence of tourism development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region is decreasing gradually. The influence of economic development level and Internet development level on the MICE city attractiveness of Beijing-Tianjin-Hebei Region remains unchanged. [ABSTRACT FROM AUTHOR]

This paper presents a promising solution to superheat of stratospheric airship with radiative cooling envelope, which has no change in pneumatic profile, structural weight, and power consumption. In this study, a multilayer nanoparticle-polymer metamaterial (MNPM) is hierarchically designed to provide reflectivity across visible wavelength and emissivity in atmospheric window. In this paper, the specimens and ball models are firstly fabricated, the cooling performances of which are tested for ground experiments. The temperatures of MNPM and silica/Ag specimens are 6.7 °C and 10.8 °C at noon in Tianjin. The inner gas and surface temperatures of MNPM scale ball are 11.7 °C and 14.6 °C, lower than silica/Ag by 4.5 °C and 4.6 °C, respectively. Subsequently, the flight experiments verify the cooling performance of MNPM, the maximum temperature of which is lower than the control group by 15.4 °C in stratosphere. Finally, the FLUENT simulations illustrate the cooling performance of stratospheric balloon and airship equipped with solar panel. The MNPM has a better cooling capacity for the internal helium and top surface throughout the day and a weak warming capacity for the bottom surface at night. Considering solar panels, the MNPM reduces the helium temperature by 8.1 °C, and the day-night superheat of the helium temperature is only 19.8 °C. [ABSTRACT FROM AUTHOR]

In this paper, the macroscopic traffic states and network traffic dynamics during the Qingming Festival holiday are explored with the Macroscopic Fundament Diagram (MFD), including the weekday before the holiday (WBH), the day of Qingming Festival (DQF), and the ordinary weekday (OW). The network is heterogeneous on the densities' distribution, and the congested areas are different in location and size. Normalized Cut (Ncut) algorithm is used to partition the heterogeneous network into multiple homogeneous subregions. The MFD of each subregion is distributed within the critical density on the WBH, and the high-density region moves from the city center to the periphery. On the DQF, high-density areas are on the central and west of the urban network. The congested branch appears on the MFD of the subregion. Then, two calibrated dynamic models, are applied to analyze the network evolution based on the partitioning results. On the basis of the calibrated model, several control strategies are proposed to relieve regional congestion on holidays. According to the simulation results, congestion on the DQF can be alleviated by controlling the external inflow ratio of subregion 2 or limiting the amount of traffic entering subregion 2 from the outside. [ABSTRACT FROM AUTHOR]

Imbalanced classification is widely referred in many real-world applications and has been extensively studied. Most existing algorithms consider alleviating the imbalance by sampling or guiding ensemble learners with punishments. The combination of ensemble learning and sampling strategy at class level has achieved great progress. Actually, specific hard examples have little benefit for model learning and even degrade the performance. From the view of identifying classification difficulty of samples, one important motivation is to design algorithms to finely equip different samples with progressive learning. Unfortunately, how to perfectly configure the sampling and learning strategies under ensemble principles at the sample level remains a research gap. In this paper, we propose a new view from the sample level rather than class level in existing studies. We design an ensemble approach in pipe with sample-level gradient resampling, that is, balanced cascade with filters (BCWF). Before that, as a preliminary exploration, we first design a hard examples mining algorithm to explore the gradient distribution of classification difficulty of samples and identify the hard examples. Specifically, BCWF uses an under-sampling strategy and a boosting manner to train T predictive classifiers and reidentify hard examples. In BCWF, moreover, we design two types of filters: the first is assembled with a hard filter (BCWF_h), whereas the second is assembled with a soft filter (BCWF_s). In each round of boosting, BCWF_h strictly removes a gradient/set of the hardest examples from both classes, whereas BCWF_s removes a larger number of harder and easy examples simultaneously for final balanced-class retention. Consequently, the well-trained T predictive classifiers can be used with two ensemble voting strategies: average probability and majority vote. To evaluate the proposed approach, we conduct intensive experiments on 10 benchmark data sets and apply our algorithms to perform default user detection on a real-world peer to peer lending data set. The experimental results fully demonstrate the effectiveness and the managerial implications of our approach when compared with 11 competitive algorithms. History: Accepted by Ram Ramesh, Area Editor for Data Science & Machine Learning. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72101176, 71722005, and 72241432], the National Key R&D program of China [Grant 2020YFA0908600] and the Natural Science Foundation of Tianjin City [Grant 18JCJQJC45900]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.1274) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2021.0104) at (http://dx.doi.org/10.5281/zenodo.6360996). [ABSTRACT FROM AUTHOR]

Saltpans extraction is vital for coastal resource utilization and production management. However, it is challenging to extract saltpans, even by visual inspection, because of their spatial and spectral similarities with aquaculture ponds. Saltpans are composed of crystallization and evaporation ponds. From the whole images, existing saltpans extraction algorithms could only extract part of the saltpans, i.e., crystallization ponds. Meanwhile, evaporation ponds could not be efficiently extracted by only spectral analysis, causing the degeneration of saltpans extraction. In addition, manual intervention was required. Thus, it is essential to study the automatic saltpans extraction algorithm of the whole image. As to the abovementioned problems, this paper proposed a novel method with an amendatory saltpan index (ASI) and local spatial parallel similarity (ASI-LSPS) for extracting coastal saltpans. To highlight saltpans and aquaculture ponds in coastal water, the Hessian matrix has been exploited. Then, a new amendatory saltpans index (ASI) is proposed to extract crystallization ponds to reduce the negative influence of turbid water and dams. Finally, a new local parallel similarity criterion is proposed to extract evaporation ponds. The Landsat-8 OLI images of Tianjin and Dongying, China, have been used in experiments. Experiments have shown that ASI can reach at least 70% in intersection over union (IOU) and 78% in Kappa for extraction of crystallization in saltpans. Moreover, experiments also demonstrate that ASI-LSPS can reach at least 82% in IOU and 89% in Kappa on saltpans extraction, at least 13% and 17% better than comparing algorithms in IOU and Kappa, respectively. Furthermore, the ASI-LSPS algorithm has the advantage of automaticity in the whole imagery. Thus, this study can provide help in coastal saltpans management and scientific utilization of coastal resources. [ABSTRACT FROM AUTHOR]

Tianjin is a coastal city of China. However, the continuous rise of the relative sea-level has brought huge hidden danger to Tianjin's economic and social development. The land subsidence is the most important factor that influences relative sea-level rise. By analyzing the current situation of subsidence in Tianjin through PS-InSAR, it was found that the subsidence rate of the southern plain of Tianjin is slowing down as a whole. In addition, Wuqing and Jinghai sedimentary areas as well as other several subsidence centers have been formed. By establishing a regular grid of land subsidence and ground water to construct a geo-weighted regression model (GWR), it was found that Wuqing sedimentary area as a whole is positively correlated with TCA. According to the relative sea-level change, it can be predicted that the natural coastline of Tianjin will recede by about 87 km2 in 20 years. Based on the research results above, this paper, by using machine-learning method (XGBoost), has evaluated Tianjin's urban safety and analyzed high-risk areas and main contributing factors. Potential risks to urban safety brought about by relative sea-level rise have been analyzed, which will improve the resilience of coastal areas to disasters. [ABSTRACT FROM AUTHOR]

Deep foundation pit excavation (DFPE) for metro stations in soft layers can cause strata deformation, impairing the safety and performance of nearby existing structures. This paper aims to explore the impact of DFPE on an adjacent oil pipeline using numerical simulations and field tests. Using the project of Xinxingcun Station of Tianjin Metro Line 4 in China as a case study, two approaches of layered excavation (LE) and bench excavation (BE) are proposed for DFPE. The deformation induced by the two approaches was analyzed using the FE method. The maximum vertical settlement of the oil pipeline caused by LE was 8.1 mm, compared with the maximum vertical settlement of 12.5 mm caused by BE. In practice, LE was selected as the construction scheme for the DFPE in Xinxingcun Station. Some field measurement work on pipeline deformation was conducted, and the results were in good agreement with the numerical simulation. Lastly, the change pattern in the pipeline-soil gap was studied. The angle of the position with peak gap width increased from 25° to 110°. [ABSTRACT FROM AUTHOR]

In this paper, a survey and two multi-attribute decision-making (MADM) models have been employed to explore critical success factors of e-exhibition in 30 Chinese provinces that is divided into 8 different regions. The research findings showed that in China, the most important success factors of e-exhibition to have green economic recovery are the presence of International collaboration (0.592), green culture (0.490), and visitor's attitude (0.439). Furthermore, "Beijing and Tianjin" is the most ideal region to promote e-exhibition in China. South Coast region ranked in second place as the most appropriate region for e-exhibition. The least ideal region of China for e-exhibition is the Southwest region that is less developed compared to other regions of China. The major practical policies are the enhancement of international cooperation to hold an e-exhibition, use of electronic exhibition capacities (synchronous and asynchronous) and creating social sustainability awareness through the media and social network. [ABSTRACT FROM AUTHOR]

The Grand Canal of China, as a traffic artery in ancient China, has exerted profound influence on the development of the cities, towns and rural settlements along it. Now, with China's rapid urbanization, numerous settlements along the canal are confronted with problems like slow cognition of the cultural heritage, loss of the local culture and damage of historical relics. Hence, research on the protection and updating of the settlement space along the canal is in urgent need. This paper, targeting the settlement space along the Grand Canal Tianjin Section, adopts such research methods as the Historical GIS analytical method, the kernel density estimation method and the average nearest-neighbor method to quantitatively analyze the evolution stage and distribution characteristics of the settlement space along the Grand Canal Tianjin Section from the perspective of cultural relics to reveal the in-situ rules of evolution of the settlement space. The research result indicates that the spatial-temporal evolution of the settlement space can be divided into five such periods of the settlements along the canal as the pre-canal period, the rudimentary period, the development period, the mature period and the transformation period. Each period features different cultural relics and settlement distribution patterns. The research shows that the natural geographical environment, the grain transportation projects and management systems, the wasteland opening, grain growing and military defense policies, the agricultural, commercial and economic growth and the migration and folk culture are the influencing factors of the spatial evolution of the settlement space along the Grand Canal Tianjin Section. [ABSTRACT FROM AUTHOR]

A short-time rainstorm exceeding the extreme historical rainfall occurred in the Jinnan District of Tianjin, China, on 3 July 2022. Due to the concentrated time period of precipitation, it caused serious water accumulation in the Jinnan District. The purpose of this paper is to study the weather mechanism of this extreme rainstorm in the Jinan District of Tianjin. By analyzing the fine observation facts, we can obtain the mesoscale weather characteristics and environmental conditions of the process. The results provide a reference for similar weather forecasting and warning in the future. Based on the 1 min interval precipitation observation data, the ERA5 reanalysis data, the CINRAD-SA radar reflectivity data of Tanggu, the cloud-top brightness temperature data of the Fengyun-4A satellite, and the Variational Doppler Radar Analysis System data, we comprehensively analyzed a record-breaking extreme rainfall process in Tianjin on 3 July 2022. The results show that the extreme rainfall process presents prominent mesoscale weather characteristics, with high precipitation intensity in a short-term period. This process is influenced by multi-scale weather systems, including the 500 hPa upper-level trough and the long-distance water vapor transport by Typhoon Chaba. The rainstorm event is caused by the combined actions of cold pool outflow produced by the upstream precipitation, the easterly disturbance in the boundary layer, the mesoscale temperature front, and the ground convergence line. Specifically, the ground convergence line is formed by the northerly wind of the cold pool outflow and the warm and moist southerly airflow from the ocean, and the temperature front is caused by the horizontal thermal difference of the underlying surface. Both the ground convergence line and temperature front contribute considerably to the triggering of mesoscale convection. The mesoscale secondary circulation is formed in the meridional direction by the meso-γ-scale convergence and its interaction with strong velocity in front of the trough, contributing to the development and maintenance of vertical motion in the Jinnan region of Tianjin and thereby leading to the occurrence and development of this extreme heavy rainfall process. [ABSTRACT FROM AUTHOR]

The goal of carbon peak and carbon neutralization puts forward higher requirements for the energy and electricity industry development in China. Jing-jin-ji region (short for Beijing, Tianjin and Hebei Provinces) as an important economic growth pole in China, its electric power industry realizing low-carbon transformation can play a good exemplary role nationwide. To clarify the key factors affecting carbon dioxide emission from electric power industry and analyze the relationship between emission and regional economic growth, the paper established decoupling effort model based on LMDI two phases decomposition model and Tapio decoupling index. Firstly, we collected the data of Jing-jin-ji region from 2000 to 2017 and conducted factors decomposition. The results show that: among the ten key factors affecting electric power industry CO2 emission, power generation and consumption ratio, fossil energy consumption coefficient and industrial structure have the most significant effect on CO2 emission reduction, with contribution rates of − 23.27, − 16.50 and − 11.91%, respectively. Per capita GDP and total population are the main positive driving factors, with contribution rates of 132.20% and 23.38%, respectively. Then from the perspective of decoupling relationship, the electric power industry in Jing-jin-ji region has entered a weak decoupling state since the Eleventh Five Year Plan with the decoupling index declined from 0.85 in 2004 to 0.38 in 2017. Excluding the influence of economic development, there are six driving factors to realize the weak decoupling, including (1) Power generation and consumption ratio effect, (2) Industrial structure effect, (3) Industrial power consumption intensity effect, (4) Fossil energy consumption coefficient, (5) Thermal power proportion effect and (6) Fossil energy power generation structure effect, in which the decoupling degree decreases in turn. The total population effect, transmission and distribution loss effect and resident power consumption intensity effect have not achieved decoupling status. At last, based on the model calculation results, we put forward suggestions to promote the low-carbon development of power industry in Jing-jin-ji region, for example, accelerate industrial structure upgrading and the adjustment of power generation structure; Strengthen electricity demand side management; Promote the construction of ultra-high voltage and smart grid as a whole. [ABSTRACT FROM AUTHOR]

Intensive land use (ILU) is a multi-objective optimization process that aims to simultaneously improve the economic, social, and ecological benefits, as well as the carrying capacity of the land, without increasing additional land, and evaluation of the ILU over long time series has a guiding significance for rational land use. To tackle inefficient extraction of information, subjective selection of dominant factor, and lack of prediction in previous evaluation studies, this paper proposes a novel framework for evaluation and analysis of ILU by, first, using Google Earth Engine (GEE) to extract cities' built-up land information, second, by constructing an index system that links economic, social and ecological aspects to evaluate the ILU degree, third, by applying Geodetector to identify the dominant factor on the ILU, finally, by using the S-curve to predict the degree. Based on the case study data from northern China's five fast-growing cities (i.e., Beijing, Tianjin, Shijiazhuang, Jinan, Zhengzhou), the findings show that the ILU degree for all cities has increased over the past 30 years, with the highest growth rate between 2000 and 2010. Beijing had the highest degree in 2018, followed by Tianjin, Zhengzhou, Jinan, and Shijiazhuang. In terms of the time dimension, the dominant factor for all cities shifted from the output-value proportion of secondary and tertiary industries in the early stage to the economic density in the late stage. In terms of the space dimension, the dominant factor varied from cities. It is worth noting that economic density was the dominant factor in the two high-level ILU cities, Beijing and Tianjin, indicating that economic strength is the main driver of the ILU. Moreover, cities with high-level ILU at the current stage will grow slowly in the ILU degree from 2020 to 2035, while Zhengzhou and Jinan, whose ILU has been in the midstream recently, will grow the most among the cities. [ABSTRACT FROM AUTHOR]

Whether the place-based industrial policy promotes regional economic growth is a hot issue in the field of regional industrial economic practice. As a major national strategy in China, the Beijing-Tianjin-Hebei industrial coordinated development policy has been implemented more than 8 years. Verifying its effect on regional economic growth and revealing the policy action path will help to further optimize the policy implementation process through feedback. In this paper, the policy effect and its differentiation are empirically studied from 'quality' and 'quantity' respectively by establishing a growth model using the Dual Differences method. The results show that the Beijing-Tianjin-Hebei industrial coordinated development policy improves total factor productivity by 2.26% in terms of 'quality', and reduces GDP growth rate by 4.65% in terms of 'quantity'. For the different region, the GDP growth rate increased by 1.28%, while total factor productivity decreased by 2.63% in Beijing, the GDP growth rate decreased by 3.17% and total factor productivity increased by 0.87% in Tianjin, and the GDP growth rate increased by 2.56% and total factor productivity increased by 1.58% in Hebei. The policy is mainly realized by fixed asset investment, capital deepening degree and enterprise scale expansion, while the effect of labor input, R&D investment and enterprise number is not significant. The policy is to give full play to the driving role of fixed asset investment such as "new infrastructure", increase investment in labor and research and development in the region, strengthen the construction of a competitive market environment, and stabilize the 'quality' and 'quantity' to further release policy dividends. [ABSTRACT FROM AUTHOR]