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The accurate identification of urban functional areas is of great significance for optimizing urban spatial structure, rationally allocating spatial elements, and promoting the sustainable development of the city. This paper proposes a method to precisely identify urban functional areas by coupling Open Street Map (OSM) and Point of Interest (POI) data. It takes the central urban area of Hangzhou as a case study to analyze the spatial distribution characteristics of the functional areas. The results show that: (1) The central urban areas of Hangzhou are divided into 21 functional areas (6 single functional areas, 14 mixed functional areas and 1 comprehensive functional area). (2) The single functional areas and the mixed functional areas show the geographical distribution characteristics of the looping stratification, which means "Core-periphery" differentiation is obvious, and the comprehensive functional area is relatively scattered. (3) The mixed degree of regional function with ecological function and production function is low while comprehensive functional areas are usually associated with higher potential and vitality. (4) The identification results are in great agreement with the actual situation of Hangzhou central urban area, and the method is feasible. Therefore, this paper can provide a reference for urban development planning and management. [ABSTRACT FROM AUTHOR]

The spatial layout and optimization of social facilities for sports are related to many factors such as urban economy, transportation, population, and urban planning. With the rapid development of artificial intelligence today, deep learning came into being. It also provides a lot of methods for our in-depth research on it. To solve the problem of unbalanced layout of urban social facilities for sports and the difficulty in meeting the needs of residents under the current background, this paper adopts the methods of M-P model, loss function, and activation function. Taking Hangzhou, a sports city that is about to host the Asian Games, as an example, it carried out an experiment to optimize the layout of urban public sports services. Through various tests and data, it divides the accessibility level of social facilities for sports in Hangzhou into four levels: high accessibility point (1.0-1.5), high accessibility point (0.5-1.0), the accessibility is average (0.2-0.5), and the accessibility is poor (<0.2). It also concluded that the areas with high accessibility (1.0-1.5) are Shangcheng District and Binjiang District, and the layout of sports facilities is optimal. According to the minimum facility point model, Xiaoshan District and Yuhang District need to add 6 large-scale social facilities for sports. Through this experiment, this paper can also provide a reference for other urban layouts. This has significance for the optimization of sports facilities and the optimization of public facilities. [ABSTRACT FROM AUTHOR]

Digital economy has been given a critical mission and momentum to promote high-quality integrated development in the Yangtze River Delta of China. Based on previous research on the spatial distribution of the digital economy and urban networks, this paper creatively utilized the data on human resource needs in the digital economy to compare the urban network. Using Kriging interpolation, network density, clique analysis, GIS technology, and other tools and methods, the evolution of network characteristics and the structure of digital economy companies in the Yangtze River Delta were described. The study found that (1) the digital economy of the Yangtze River Delta cities has developed rapidly, but the industry segmentation, spatial distribution, and scale are not balanced; (2) the networked pattern of the digital economy has taken shape, and the collaborative governance effect of the digital economy network based on the human resource supply chain and the urban network is beginning obviously; and (3) the core cities such as Shanghai and Hangzhou still occupy a dominant position in the digital economy, although there have been formed several cliques, most cities in the network have not yet been able to form subclusters independently. The urban agglomeration spatial structure attracts scholars, urban managers, and policymakers. Many scholars have researched the network structure of urban agglomerations from transportation and population flow perspectives. It is a new attempt to analyze the urban system through the spatial relationship of human resource demand. In recent years, as a new development content, the digital economy has attracted the attention of urban managers and markets around the world. From the perspective of urban planning, describing the network distribution of digital economy enterprises' human resource needs in the urban agglomeration space is conducive to better grasping the structural characteristics of China's Yangtze River Delta urban agglomeration and understanding the urban system within the urban agglomeration. At the same time, it also provides a basis for the organization and resource allocation of the digital economy in space. [ABSTRACT FROM AUTHOR]

As an important part of the city's comprehensive disaster prevention and alleviation security system, city fire control system has drawn increasing attention of the community. The planning of city fire stations is an important safeguard to improve the city's fire security. Whether the planning is scientific and rational will affect the fire security of the entire city directly. In this paper, road networks were built based on GIS, the service range of fire stations was calculated based on time cost, and the planning of fire stations in main districts of Hangzhou was evaluated in terms of security, efficiency, and balance. The results showed that this planning made significant improvements in security and balance of fire fighting service provided by the main districts of Hangzhou, but few improvements were high in efficiency. On the whole, Xiacheng District did the best job in fire control, and Xihu District was expected to make efforts to improve its fire security. [ABSTRACT FROM AUTHOR]

Identifying urban production–living–ecological spaces and their interactive relationships is conducive to better understanding and optimizing urban space development. This paper took the main urban area of Hangzhou city as an example, and a two-level scoring evaluation model was constructed to accurately identify urban production–living–ecological spaces using point of interest (POI) data. Then, kernel density analysis, a spatial transfer matrix, and a bivariate spatial autocorrelation model were used to reveal the spatial patterns of urban production–living–ecological spaces and their interactive relationships during 2010 and 2019. The results showed that the proposed two-level scoring evaluation model combining both the physical area and density of POIs was effective in accurately identifying urban production–living–ecological spaces using POI data, with an identification accuracy of 88.9%. Urban production space was concentrated on the south bank of the Qiantang River and around the north of Hangzhou. Urban living space had the highest proportion, mainly distributed within the ring highway of Hangzhou in a contiguous distribution pattern, and urban ecological space was concentrated around West Lake and Xiang Lake. During 2010 and 2019, the expansion of urban production–living–ecological spaces had obvious spatial differences. Additionally, the mutual transformation between production and living spaces was more frequent during the study period and was mainly distributed within the ring highway of Hangzhou. There were significant positive spatial correlations between production and living and between living and ecological spaces, while a significant negative spatial correlation occurred between production and ecological spaces. The spatial correlations of urban production–living–ecological spaces revealed obvious spatial heterogeneity. This study proposed a two-level scoring evaluation model to accurately identify the spatial patterns of urban production–living–ecological spaces and their interactive relationships using POI data, which can provide detailed information and scientific references for urban spatial planning and management in rapidly urbanizing cities. [ABSTRACT FROM AUTHOR]

China has seen a transition from impulsive industrial development-driven urban expansion to urban planning and government control since the start of the 21st century. Urban planning attempts to ensure the sustainable development of cities and the rational use of land resources. The dual-track urbanization process does, however, often result in a significant gap between planning and actual development. This paper contends that a comprehensive dual-track urbanization research perspective is better suited for investigating urban sprawl in peri-urban areas in post-reform market economy-active regions. Taking Xiaoshan District, the peri-urban area of Hangzhou, China, as a case study, this research utilizes land use raster data from 1985, 2000, 2010, and 2020 to identify the dynamic changes in urban construction land and examines the driving elements through the logistic regression model. Based on the results, the mechanisms of market-incented and government-controlled impacts on urban expansion are explained. This study aims to (1) analyze the spatial and temporal patterns of Xiaoshan's urban expansion during 1985–2020; (2) compare the compositional characteristics of three types of urban growth (edge growth, infilling, and leapfrog development) in each phase of Xiaoshan; (3) identify the natural environment, accessibility factors, and socioeconomic aspects that promote Xiaoshan's urban expansion in 2000–2020; (4) discuss Xiaoshan's dual-track urbanization from four perspectives: regional development, private business, government control, and major events. This study advanced our knowledge of the driving mechanisms of urban land expansion in small towns, from peri-urban areas to metropolitan sub-centers, and, thus, has important implications for Chinese urban planning and the management of metropolitan suburbs, especially those located in the Yangtze River Delta. [ABSTRACT FROM AUTHOR]

Objectives: As the acceleration of global urbanization, traffic congestion and environmental degradation have emerged in the urban area. Based on the light and statistical data, this paper studied the spatial evolution between urban people and land, and revealed the significance of its coupling and coordination characteristics for the sustainable development of cities. Methods: For primary data, a series of preprocessing are needed to eliminate the problems of supersaturation and discontinuity of inter‑annual data. Based on the lighting threshold, this paper excerpted the built‑up areas of urban agglomeration in Zhejiang Province year by year, compared them with the statistical data, and analyzed the corrected data source relatively. Firstly, based on the order‑scale distribution model of urban order and urban population in Zhejiang Province from 1992 to 2020, we made a dynamic analysis on population aggregation and distribution in its development process. Then, we constructed the population‑land urbanization allometric growth model by using population and light area, as well as judged the spatialization of man‑land relationship in urban development. Finally, according to the lag phenomenon of population growth relative to land development, we proposed an allometric growth model with lag factor, and used the lag term model to judge the characteristics of unequal growth of people and land in different cities. Results: The structural system of urban agglomeration is relatively mature in Zhejiang Province, and the distribution of cities is reasonable. However, the primacy of city is gradually improved, and the population is gradually gathering. The results of allometric growth model show that the man‑land relationship of urban agglomeration in Zhejiang Province is generally low in the eastern coastal cities and high in the western inland cities, and the planning of the four metropolitan areas is reasonable. The improvement of fitting accuracy of the proposed model with lag factor obviously shows that there is lag effect between population urbanization and land urbanization, with an average increase of 6.47% and the highest increase of 12.61%. Among the influencing factors on land urbanization, the dominant factor in Hangzhou is the existing population in urban areas, while the dominant factor in Ningbo is the new population in urban areas. Conclusions: The proposed allometric growth model with lag factor can correct the model errors and improve the fitting accuracy of urban man‑land relationship. It can also effectively evaluate the temporal and spatial evolution characteristics of man‑land relationship in regional system, explore its development and put forward countermeasures. [ABSTRACT FROM AUTHOR]

Rapid urbanization has changed urban ecological environments and affected local biodiversity. An analysis of the existing literature examining changes in urban biodiversity may help with urban planning and biodiversity conservation. The present paper analysed the dynamic change of plant diversity in Hangzhou over the past four decades of rapid urbanization. It was found that although the number of plant species increased from 1,565 in 1981 to 1,799 in 2020, 101 plant species were lost. At the same time, 18 invasive species of plants and 52 ornamental plant species were acquired, with the largest increase observed in perennial herbs as a result of urban greening. A comparison of the respective Ellenberg’s Indicator Values (EIV) of lost and acquired species reveals a larger increase in the number of species for sun plants than for shade plants. The latter did not increase with the rapid increase in urban green areas. A significant increase in the number of thermophilous plant species was observed, which is closely related to global warming and the heat island effect in cities. The number of aquatic plants also increased due to urban wetland landscaping. Prioritizing land conservation in urban planning is more conducive to producing and maintaining stable urban ecosystems and practicing sustainable urban development. [ABSTRACT FROM AUTHOR]

The emerging ride-sourcing service has become an important element of urban mobility. A challenging question underlying the provision of such service is how and to what extent the built environment affects origin-destination (OD) travel flows. This paper employs the geographically weighted regression (GWR) model to analyze the OD-based ride-sourcing travel flow. It makes a comparison with the existing ordinary least square (OLS) model and spatial autocorrelation model (SAM). We have collected ride-sourcing order data in Hangzhou, China, to provide an accurate source for acquiring ride-sourcing travel flow. We investigate the effects of the residential area, points of interest (POIs), and transit stations on ride-sourcing travel flow among traffic analysis zones (TAZs). The results show the following: (a) GWR has better goodness-of-fit than SAM and OLS. (b) Residential area, enterprise, and bus stations have positive correlations with ride-sourcing OD flows, but education and subway stations have negative correlations. We have further investigated the issue and found that it is not a causal relationship between the bus station and OD flow, due to collinearity between the two variables. The bus station builds on locations with high demand, but its capacity is not large enough to reduce the ride-sourcing flow to a low level, which results in a positive coefficient. (c) Based on the estimated coefficients, the prediction of ride-sourcing flows is feasible, supporting the impact analysis for urban land use and transportation planning. This paper contributes to understanding OD-based ride-sourcing travel flow distributions and provides a framework of long-term OD flow prediction for urban land use and transportation planning. [ABSTRACT FROM AUTHOR]

Although the communicative dimension of urban development has caught the imagination of urban studies scholars, the cultural, and intercultural, nature of this discourse has received less attention than it deserves. As a case study and illustration of urban development workplace discourse from out of a Chinese/Asian/developing-world context, the present article examines the properties, problems, and potentials of the global branding practice of Hangzhou, a renowned tourist and ancient capital city on the east coastal region of China. First, after critiquing tendencies in relevant communication approaches, the paper outlines a holistic, cultural concept of urban branding of the developing world – as a culturally saturated, development-oriented, workplace discourse. Then, based on ethnographic data collected from a plethora of sites and sources (the municipality, trade association, the Internet, interviews, newspapers, street posters, museums, and historical records), the paper studies, qualitatively and quantitatively, a variety of interlocking international branding practices (municipal management, expos, festivals, exhibitions, international tours, websites, foreign language use, award-winning, etc.). In conclusion, the paper draws implications for future research and practice on urban development and branding in the developing world. [ABSTRACT FROM PUBLISHER]

As a major labor force of cities, young people provide a huge driving force for urban innovation and development, and contribute to urban industrial upgrading and restructuring. In addition, with the acceleration of urbanization in China, the young floating population has increased rapidly, causing over-urbanization and creating certain social problems. It is important to analyze the demand of urban youth and promote their social integration. With the development of the mobile Internet and the improvement of the city express system, ordering food delivery has become a popular and convenient way to dine, especially in China. Food delivery data have a significant user attribute where the ages of most delivery customers are under 35 years old. In this paper, we introduce food delivery data as a new data source in urban functional zone detection and propose a time-series-based clustering approach to discover the urban hotspot areas of young people. The work and living areas were effectively identified according to the human behavioral characteristics of ordering food delivery. Furthermore, we analyzed the relationship between young people and the industry structure of Hangzhou and discovered that the geographical distribution of the identified work areas was similar to that of the Internet and e-commerce companies. The characteristics of the identified living areas were also analyzed in combination with the distribution of subway lines and residential communities, and it was found that the living areas were mainly distributed along subway lines and that urban villages appeared in the living hotspot regions, indicating that transportation and living cost were two important factors in the choice of residential location for young people. The findings of this paper can help urban industrial and residential planning and young population management. [ABSTRACT FROM AUTHOR]

The Grand Canal has been fundamental in supporting Chinese industrialization, as evidenced in the great changes witnessed across industrial lands, but few studies have approached this issue from a cultural perspective. After an extensive industrial recession in the early 21st century, canal cities like Hangzhou have seen changes in the cultural functions of industrial lands, relocating, transforming, and demolishing factories and other constructions to develop new cultural spaces and products. A deep analysis of these cultural changes is, therefore, quite helpful to appreciate the features of and reasons for Chinese national policy setting in the cultural sections of the Grand Canal, such as the UNESCO World Heritage-recognized purpose of the Grand Canal, etc. Therefore, by focusing on the Hangzhou section of the Canal, and via the integration of high-resolution Google Earth images with a 1.5 spatial resolution, we dynamically monitored the land use of the 10 specifically selected industrial lands and interpretated the various uses of the areas from 2000 to 2020. Then, with archival data from 1950 to 2024 and fieldwork conducted over 1 year, and in consultation with major experts, we designed a mark sheet with factors and scores to comprehensively assess cultural changes in those lands. Consequently, the history of industrialization along the Hangzhou section was thoroughly analyzed with these investigations and data, and the reasons for and influence of cultural changes were presented in detail; subsequently, the outstanding problems were addressed, and suggestions were offered. This study contributes to a better understanding of Chinese cultural policy regarding cities along the Canal after the industrial decline, especially the critical implication of cultural loss within these cities. In addition, it also provides novel perspectives for cultural research, heritage conservation, and urban planning of canals or waterfront spaces for world heritage. [ABSTRACT FROM AUTHOR]

Many previous works suggested that visual indicators could be used to predict landscape preferences. Most works, however, judged the visual indicators by a subjective method, which was criticized for lack of standardization in methodology, nontransparent application of values, and lack of replicability. This paper studied the relationships between landscape preferences and 10 visual indicators, among which seven indicators were evaluated by an objective measurement. Another three indicators (years of history heritages, number of landscape elements, and impression) were evaluated by a subjective method because they depend on a human's perception. The landscape preferences were judged by undergraduate students based on the stimuli of 30 photographs taken in the two cities of Hangzhou and Suzhou in the east of China. The results show that students prefer landscape with historical heritage of 200-600 years, moderate impression, approximately 60% of open land cover and 45% of water body cover, lower plant cover, more heterogeneities, and higher naturalness; no significantly statistical relationships exist between students' preference scores and the ratio of disturbed area, building cover, or topographic variation cover. These results were confirmed by another six photographs; and last, some suggestions for landscape design were given. [ABSTRACT FROM AUTHOR]

The development of urban underground space (UUS) is an important approach to the sustainable development of modern cities. This means that assessing potential demand differences in undeveloped UUS can inform the areas that need to be prioritized for development in urban planning and development. The recent emergence of geospatial big data provides fine-grained support for capturing changes in the development of various urban subjects. However, to date, research applying geospatial big data to UUS assessment has been limited. In this study, UUS evaluation indicators were constructed using geospatial Big Data, and the weights of the indicators driving the existing UUS demand were determined based on the Geodetector model, avoiding the drawbacks of human subjective influence and the lack of reference of general methods. It also combined the linear weighting method to quantify the UUS demand in undeveloped areas within the grid based on the attribute values and weights of each indicator and used the magnitude of the resulting demand values to provide a grid-scale judgment of priority areas for future underground space development. Taking the Qiantang District of Hangzhou, China, as an example, it was verified that the high-demand areas are consistent with the existing UUS distribution, indicating that the UUS demand evaluation model based on geospatial big data established in this study is feasible and accurate, and in this way, new high-demand areas were circled in the undeveloped areas as a direction for future urban underground development. [ABSTRACT FROM AUTHOR]

This paper analyzed characteristics of railway heritage, and introduced several models for the protection and reutilization of railway heritage worldwide, and also a few cases. Taking Jiangshu Railway Relics Park and White Pagoda Park in Hangzhou City for example, the paper explored domestic cases of protecting and reusing railway heritage, and pointed out the directions for railway heritage protection and development. [ABSTRACT FROM AUTHOR]

Pre-reform Chinese cities base their uniqueness in urban transformation on Mao's duality of utopian and revolutionary ideals and pragmatic and economized approaches in practice. Through the lens of urban economy, population management, and city planning, this paper examines China's pre-reform urban transformation. By the case study of Hangzhou, this research reveals that urban development was driven by a diverse set of forces devised by the communist state to configure the urban conditions and control people's daily lives in pursuit of radical socialist goals. The controls from the state and other pertinent forces led to the actual outcomes of political-economic ambitions and spatial policy rhetoric. It was an inherent feature of the society and economy to go outside of the state's controls, and the unintended consequences were unavoidable. The state had to revise their strategies, the outcomes of which were again to be tested by time. An iterative process determined the urban transformation of Chinese cities. [ABSTRACT FROM PUBLISHER]

• An agent-based simulation is constructed to study the parking problem in an AV future. • Multiple parking strategies of AVs (park at a parking lot, cruise, and return to the origin) are considered. • The simulation model is based on the real trip data and road network. • The impact on individuals, network, and parking lots are all investigated. Autonomous vehicles (AVs) are expected to transform urban parking. AVs may not require dedicated parking spaces near their destination. Instead, AVs can drive to the optimal parking lot, cruise, or return to the origin after the passenger gets off. Previous research on AV parking strategies has largely overlooked actual trip patterns and road network conditions that can affect the effectiveness and feasibility of these strategies. In this paper, we construct an agent-based simulation model to assess the potential impacts of AVs on urban parking, focusing on new AV parking strategies. Using the real traffic network and trip data of Hangzhou, we assess the impacts on overall network efficiency, personal trip, and parking demand under different AV penetration rates. Results show that AVs could decrease the total parking cost from 23 to 6 RMB and increase parking convenience for both AVs and human-driven vehicles (HDVs). 21% of AVs will still choose to park, while 70% will return to the origin. On average, each trip with AV will generate an additional zero-occupant distance of 8.8 km, exacerbating the congestion. The findings indicate the benefits and challenges of new AV parking strategies, providing valuable insights for future urban parking planning and policy making. [ABSTRACT FROM AUTHOR]

This study aims to optimize the evaluation system of inclusive design in urban parks, emphasizing the systemic nature of sensory, cognitive, and motor capacity support and exploring its role in park design practice. Based on the capability demand model, this study constructed indicators through literature collation and focus group discussion and assigned weights through hierarchical analysis to finally construct the Park Inclusive Design Index (PIDI). Then, the PIDI was utilized to assess the inclusive design performance of 48 urban parks in Hangzhou, China. The results of this study show that the overall inclusive design level of parks is relatively low (the average PIDI < 70), especially in the provision of cognitive support (cognitive-related indicator < 4). Meanwhile, comprehensive and specialized parks performed better in inclusive design compared to community parks and leisure parks. The level of inclusive design is moderatory correlated with the park renovation time and the park area, and strongly correlated with geographic location (scenic spot parks perform better; the parks in the old city perform worse). Ten indicators in the assessment scored below 2, which reveals the current status, shortcomings, and general problems with inclusive facilities in Hangzhou's urban parks. This study integrated the needs and ability differences of people into the indicators, providing an assessment framework with broad applicability. Inclusive performance is a long-term process, and the implementation of the evaluation framework will provide a reference guide for the design, construction, operation, and maintenance of urban parks across China and even around the world. [ABSTRACT FROM AUTHOR]

Since the national urban housing reform in the 1990s, the Hangzhou Metropolitan Area in China has been experiencing a construction boom and an extraordinary growth of the residential building stock. Housing has made up an important part of the physical urban development and regional economic growth. The metropolitan area authorities aim to pursue sustainable housing development by adopting decoupling strategies emphasising efficient use of resources. However, in spite of these strategies, a study of Hangzhou's actual rates of decoupling between economic growth, housing sector growth and negative environmental impacts indicates only weak decoupling and a tendency of declining degrees of decoupling (if present at all) during the latest two decades. Limits of decoupling strategies for sustainable housing development are discussed in the light of these findings. The paper concludes with a recommendation to take growth containment into China's policies towards sustainable development, while at the same time guaranteeing a decent living standard among citizens. [ABSTRACT FROM PUBLISHER]

Sustainability studies are vital for the long-term development of ecological cities. For cities, single qualitative or quantitative evaluation studies cannot effectively illustrate the ecological and sustainable status of a city. This study employs the emergy–geographic information system (GIS) method to conduct a sustainability evaluation of a city, so as to effectively verify the evaluation results. The emergy method and GIS are both commonly used approaches to address urban issues, but their synergistic effect has rarely been considered, explored, and utilized in urban planning. This study aims to investigate this effect on Hangzhou city through comparative analysis. The results show that rain (geopotential energy) and rain (chemical potential energy) have the highest emergy values from 2000 to 2035, followed by solar emergy, wind emergy, and geothermal heat emergy. These findings are also supported by the GIS map that shows a similar pattern with renewable emergy. Using the five plots (cropland, woodland, grassland, water area, and built-up land) on the GIS map as examples, the accuracy of emergy calculation results for Hangzhou city can be verified, demonstrating the effectiveness of the emergy–GIS methodology. This research provides practical recommendations for city designers and professionals worldwide on urban sustainability. By incorporating both emergy and GIS methods, cities can make informed decisions toward achieving environmentally sustainable development. [ABSTRACT FROM AUTHOR]

As the oasis area in the city, urban park plays an extremely prominent role in the regulation and improvement of the urban ecological environment, especially the local thermal environment, and has become one of the significant ways to reduce the urban heat island (UHI) effect. Our study comprehensively considers the maximum cooling distance and spatial continuity of urban parks, takes 30 parks in Hangzhou, and analyzed their influencing factors to comprehensively explore the park cooling effect. The results showed that the land cover shifted drastically during 2000–2020, and the built-up land area increased greatly, which aggravated the UHI effect. The high UHI value of Hangzhou was concentrated in the city center and presented a spreading trend from north to south. Different types of urban parks presented different cold island effects, with comprehensive parks and ecological parks having the largest cooling area, and community parks exhibit better accumulative cooling effect. In addition, the park's own characteristics (perimeter, area, shape index) and inner and surrounding landscapes were significantly correlated with the park's cooling effect (park cooling area and park cooling efficiency). Our study comprehensively considered the cooling effect of parks from the maximum and accumulative perspectives and provides theoretical and practical guidance for the construction and planning of urban parks, thereby enhancing the well-being of urban residents. [ABSTRACT FROM AUTHOR]

A significant cause of economic recession and environmental change that has attracted the extensive attention of researchers and policy-makers worldwide is the land urbanization bubble (LUB) – a rapid and catastrophic growth and decline in urban development fueled by a mixture of misplaced exuberance and speculation. It is also an important topic for sustainable urban development and urban renewal, and is of particular interest to China, as one of the countries with the largest amount of urban land, most drastic change, and most prominent land urbanization conflicts in the world. This study analyzes the characteristics and presence of dynamic change in LUBs during China's urbanization process through a case study of the changing space-time rules in Hangzhou in Zhejiang province over the years 2004, 2007, 2010, 2015, and 2020. Based on a literature review and analysis of the mechanism driving Hangzhou's LUBs, we design a method for their classification and measurement. This reveals the existence of an overall 18.24 km2 LUB in 2010 and a predicted 40.62 km2 LUB in 2020. Locally, the Jianggan and Yuhang districts are expected to have a higher LUB risk by 2020, the Bingjiang and Xiaoshan districts a medium risk, the Shangcheng and Xiacheng districts a low risk, and the Xihu district having no LUB risk. Finally, three policy recommendations are proposed in consideration of Hangzhou's economic development and land use characteristics, comprising (1) reducing LUBs by promoting intensive urban expansion, (2) reducing the possibility of LUBs by building a market-oriented control system for construction land expansion, and (3) the dynamic control of LUB risks by differential regulation of the expansion of urban construction land. • These identified LUB areas are classified into two categories in this paper, including controllable LUB uncontrollable LUB. • This research found no LUBs in 2007 and 2015, but with an 18.24 km2 LUB in 2010 and an expected 40.62 km2 bubble in 2020. • The concept of LUB risk was introduced and calculated in this paper for decision makers' reference. [ABSTRACT FROM AUTHOR]

• The spatial dynamics of urban construction land were explored by using a hybrid Logistic CA model. • We visualize how predictions on spatial expansion will benefit urban planners and policymakers. • The model could explain the underlying mechanism of urban growth in a spatial-economic and social way. • We indicate the effective quantification of land patches can improve the compact urban growth. • Effective quantification of the construction land patches could reduce the unordered urban growth. Why does some urban area grow faster than others? Although the role of spatial optimization of urban construction land is at the core of regional economic development, the question remains to be answered so far. This paper aims to explore the spatial dynamics of urban construction land in the central urban areas by integrating Logistic regression and cellular automata models. The combination of the two modeling approaches aims to investigate the evolving dynamics of urban land use patterns and further visualize how predictions on spatial expansion will benefit urban planners and policymakers. Simulation analysis emphasized to what extent do the influencing factors promote or inhibit urban growth. Theoretical frameworks tend to explain the underlying mechanism of urban growth in a spatial, economic and social way, taking the city growth as a self-organized organism with complex actors and rules. In this paper, we present a hybrid Logistic cellular automata model to examine the city's self-organizing spatial growth process from a bottom-up perspective and interpret why non-construction land was converted to construction land for urban development purposes at Hangzhou in the past two decades. We argue that although the construction land is dispersed irregularly across the city, the logistic cellular automata model will generate the underlying patterns of urban expansion and offer more facts-based implications. [ABSTRACT FROM AUTHOR]

Under the background of stock planning, improving the quality of urban public space has become an important work of urban planning, design, and construction management. An accurate diagnosis of the spatial quality of streets and the effective implementation of street renewal planning play important roles in the high-quality development of urban spatial environments. However, traditional planning design and study methods, typically based on questionnaires, interviews, and on-site research, are inefficient and make it difficult to objectively and comprehensively grasp the overall construction characteristics and problems of urban street space in a large area, thus making it challenging to meet the needs of practical planning. Therefore, based on street view images, this study combined machine learning with an artificial audit to put forward a methodological framework for diagnosing the quality issues of street space. The Gongshu District of Hangzhou, China, was selected as a case study, and the diagnosis of quality problems for streets at different grades was achieved. The diagnosis results showed the current situation and problems of the selected area. Simultaneously, a series of targeted strategies for street spatial update planning was proposed to solve these problems. This diagnostic method, based on a combination of subjective and objective approaches, can be conducive to the precise and comprehensive identification of urban public spatial problems, which is expected to become an effective tool to assist in urban renewal and other planning decisions. [ABSTRACT FROM AUTHOR]

Optimizing the location of physical activity spaces (PAS) to ensure health, equity and efficiency has long been an important issue in urban planning. Given the health benefits of urban green spaces (UGS), taking Gongshu District in Hangzhou as a case, we examine the issue of where such PAS should be located to optimize three objectives: (1) minimize the distance between PAS and UGS; (2) maximize the accessibility of PAS and (3) maximize the population that falls within the coverage range. This study develops a multi-objective optimization of physical activity spaces model (MOPAS) based upon multi-objective particle swarm optimization to yield a set of non-dominated Pareto optimum solutions that can be used to determine the most practical tradeoffs between the conflicting objectives. It compares the advantages and disadvantages of the Pareto solutions and evaluates the construction situation of locations and the implementation feasibility. Decision-makers can choose the best solution according to subjective preferences and objective conditions. The MOPSO holds great promise for improving the location optimization of PAS and the methods applied can be adapted to support multi-objective optimization of facilities in urban planning globally. [ABSTRACT FROM AUTHOR]

The Chinese New-type Urbanization (NTU) Plan indicated a major shift in planning towards compact development. This study developed an integrated framework to estimate the effectiveness of planning in promoting compact development in rapidly growing cities. We analyzed the coherence and conformance of planning, as well as the development outcome from a multi-dimensional perspective of compactness. Spatial data of both private and public development projects and big data of POI were employed for analysis in the case of Hangzhou. The findings indicate that land development efficiency and intensive urban functions at the local scale were significantly promoted after NTU planning's initiation. However, the planning was inefficient in leading a more centralized development at the city scale. This could be attributed to the inability of the planning to resolve conflicts between growth pressure and compact goals, which is reflected in the incoherent control between the master and local plans. The inefficiency is further underlined by the insufficient connection between city-wide and subject plans, as well as the permanent planning of the Urban Development Boundary without specific tools. Particularly, planning performed weaker in controlling public projects due to dual-track planning institution. These conclusions suggest the urgency of enacting a planning system that dynamically links plans of different scales and functions as a crucial element for implementing compact development in rapidly growing areas. [ABSTRACT FROM AUTHOR]

Understanding the dynamic distribution of residents' socioeconomic status (SES) across neighborhoods within cities is essential for urban planning and policy-making aligning to the Sustainable Development Goals 2030. Whereas the promise in explicitly linking geographical features to SES has been highlighted fairly clear in previous works, scholars hold an eclectic attitude in their outlook, given the absence of theoretical ground, the heavy reliance on nontransparent proprietary data sources and the relatively coarse resolution predictions. Drawing on a case study of Hangzhou metropolitan in China, this paper aims to address these problems by demonstrating a novel approach to neighborhood SES inference based on online housing advertisements. We first revisit the theoretical debates on the linkage between neighborhood SES and online housing advertisements. Then, the Naïve Bayes classifier is employed to semantically identify the topics from online housing advertisements and the associated sentiments are quantified using the lexicon-based approach. Following that, seven commonly used machine learning algorithms are compared and utilized to infer the fine-grained neighborhood SES at residential quarters scale based on the housing attributes and extracted topics from online housing advertisements. Results show that machine learning algorithms vary with predictive ability and the tree-based algorithms are much more powerful in inferring neighborhood SES. More specifically, we distinguish 8 reliable features which not only present relative high importance estimated by all the machine learning algorithms but also exhibit great robustness in inferring neighborhood SES and show promising potential to being applied for unraveling social inequalities. We also observe noteworthy spatial heterogeneity in neighborhood SES across the research site. The demonstrated approach not only enables the policymakers to take stock of deprived neighborhoods in a timely manner, but also lays firm ground for framing contextualized strategies of urban governance. This study is among the first attempts to bridge the theoretical interpretation of housing attributes with the proxy indicator -based approach for fine-grained neighborhood SES measurement. [ABSTRACT FROM AUTHOR]

The removal and reconstruction of urban villages can improve the residential environment in the vicinity and promote the willingness of buyers to pay. A detailed investigation of the price effects on nearby housing generated by urban village redevelopment helps to capture the added value of public investment. Previous studies often ignore the temporal variation of the price effects. Furthermore, they confuse the price effects from the removal of dilapidated housing and the construction of new buildings. Based on the listing prices in 2017–2018 and transaction data in 2015 of secondhand residential housing in Hangzhou, China, this paper built a multi-period difference-in-differences model to examine the multi-period price effects from urban village redevelopment on nearby housing and to isolate the removal effects of old buildings and the amenity effects of reconstruction. The results show that (1) An anticipatory effect of up to 13% occurs before the urban village redevelopment; removal and reconstruction will bring a total premium of 20% to nearby housing prices; and the total price effects gradually increase in time and slightly fall back after four years. (2) Less than 15% of the added value comes from the removal of dilapidated housing in an urban village, while more than 85% comes from the reconstruction of new buildings. (3) The price effects of large-scale urban village redevelopment are much more obvious. • A multi-period difference-in-differences is used to investigate the temporal variation of the price effects. • An anticipatory effect up to 13% occurs before the redevelopment and an average price effect of 20% exists after the redevelopment. • Nearly 85% of the average price enhancement comes from reconstruction of new buildings and only 15% from the urban village removal. • Large-scale urban village redevelopment invites greater price premium while small-scale generates no significant effects. [ABSTRACT FROM AUTHOR]

Urban villages, namely villages encircled by urban environments, are unique phenomena that proliferated during China's rapid urbanization process, as well as important development issues for many Chinese cities at present. This article focuses on two planning approaches for urban villages, dominated by the government's uniform and formal planning and villagers' spontaneous and informal planning practices, aiming to examine which planning approach is more conducive to urban village development. The two planning approaches for urban villages have simultaneously appeared in Hangzhou, a Chinese metropolis with a combination of high-speed economic growth, a unique geological environment, and a long cultural history, providing appropriate comparative study cases for this research. Two urban villages, Luojiazhuang and Yangjiapailou, located in plain and hilly areas in Hangzhou, respectively, and developed through the two planning approaches were selected as study cases. Primary data were collected based on field investigations, semi-structured interviews, and questionnaire surveys. The villagers' rental income, shopkeepers' business benefits, and tenants' residential satisfaction were investigated to compare the development of the two urban villages. Results indicate that compared with the formal planning-dominated approach, the informal planning-dominated approach achieves continuously rising rental income, more stable business benefits, and higher residential satisfaction, better suited to urban village development. This study contributes to coordinated urban–rural interaction in the urbanization process and enriches the formality–informality debates from a spatial planning perspective. [ABSTRACT FROM AUTHOR]

Commuting pattern is one of the most important travel patterns on the road network; the analysis of commuting pattern can provide support for public transport system optimization, policy formulation, and urban planning. In this study, a framework of the key commuting route mining algorithm based on license plate recognition (LPR) data is proposed. And the proposed algorithm framework can be migrated to any similar spatiotemporal data, such as GPS trajectory data. Commuting pattern vehicles are first extracted, and then, the spatiotemporal trip chains of all commuting pattern vehicles are mined. Based on the spatiotemporal trip chains, the spatiotemporal similarity matrix is constructed by dynamic time warping (DTW) algorithm. Finally, the characteristics of commuting pattern are analysed by the density-based spatial clustering of applications with noise (DBSCAN) algorithm. Different from other researches that analyse the commuting pattern using machine learning algorithms based on all data, this study first extracts commuting pattern vehicles and then designs a key commuting route mining algorithm framework for commuting pattern vehicles. Taking Hangzhou as an example, through the framework of mining algorithm proposed in this study, the commuting pattern characteristics and key commuting routes in Hangzhou have been successfully excavated, and policy suggestions based on the analysis results have also been put forward. [ABSTRACT FROM AUTHOR]

Urban resilience is an attractive concept among academies and governments with the increasing severity of climate change and relevant disasters in cities. Few studies have been conducted to compare the key elements of attentions for enhancing urban resilience among Asian cities, although resilience is context-dependent. This study aims to compare the key elements of attentions for enhancing urban resilience among Singapore, Hong Kong and Hangzhou. A comprehensive literature review and expert interview validation were used to solicit the preliminary elements of attentions for enhancing urban resilience. Planners and researchers in the field of urban planning were surveyed to assess the significance level of the preliminary elements in the three case cities, as professional knowledge is required in the survey. Statistics were used to identify the key elements of attentions in the three case cities. Results demonstrate that the three cities have various elements of attentions for enhancing urban resilience despite sharing many similarities, which also demonstrate the guidance limitation of the general urban resilience framework. It also provides a reference for other international comparisons. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines features and driving forces of urban sprawl in Hangzhou from 1995 to 2005 by using urban expansion classification, density analysis, spatial metrics, and geospatial analysis. We classified Hangzhou''s urban development into three types: infilling, edge, and leapfrog growth, and used a leapfrog development index to indicate the extent of this type of urban expansion. We defined a sprawl index that takes both urban land expansion and population density into account to measure the magnitude of sprawl at the street-town level. Further, we employed landscape metrics to describe the change of spatial pattern of Hangzhou''s urban expansion. To assess the inconsistency between actual urban expansion and planning, we compared the current urban land use with the latest urban land planning. Based on our findings, we identified features of urban sprawl of Chinese cities that are distinct from those identified in cities of western countries and discussed the role of critical policies that have affected urban sprawl in Hangzhou. [Copyright &y& Elsevier]

• Online housing advertisements are used to unravel how landscape amenities are capitalized into rental prices across five Chinese megacities. • 'Landscape amenities' is a typical topic and 'park' is a typical component in the five megacities. • Strength of the sentiments associated with the 'landscape amenities' topic varies with megacities. • The capitalization effect of landscape amenities is not significant for all the megacities. • To what extent landscape amenities contribute to residential rental prices is unveiled. Real estate premium associated with landscape amenities is a well-studied topic with a primary focus on housing prices. Presumably, the willingness-to-pay for landscape amenities should be very different between homeowners and tenants. Thus far, how landscape amenities affect residential rental prices is not well understood. This paper takes advantage of the big data of online housing advertisements to unravel how landscape amenities are capitalized into rental prices across five Chinese megacities (Beijing, Shanghai, Shenzhen, Hangzhou and Wuhan). Natural language processing, the latent Dirichlet allocation in particular, is first employed to semantically analyze the geo-textual advertisements. It reveals that 'landscape amenities' is a typical topic and 'park' is a typical component for housing advertisements in the five megacities. The lexicon-based sentimental analysis further shows that the strength of the sentiments associated with the 'landscape amenities' varies with cities. A series of hierarchical hedonic models based on the extracted semantic and sentimental aspects are then established for each megacity after segmenting the rental market into submarkets. The capitalization effect of landscape amenities is significant in Beijing, Hangzhou and Wuhan, while it is not significant in Shanghai and Shenzhen. Finally, variance decomposition analysis and marginal implicit price calculation unveil to what extent landscape amenities contribute to residential rental prices. Based on these findings, we discuss several major implications for urban planning. Our study unsettles the popular presumption that landscape amenities are key determinants of real estate values. It renews our understanding of the economic values of landscape amenities theoretically and methodologically. [ABSTRACT FROM AUTHOR]

Rapid urbanization leads to a disorder land use pattern, posing severe threats to natural resources with high-quality ecosystem service (ES), hence, it is necessary to delineate ecologically constrained urban growth boundary (UGB) for containing sprawling urban expansion. The ecological constraint based on the assessment of specific or comprehensive ecosystem function provides little information about how the ecological correlation within different ESs affecting urban growth probability. This paper defined the strictest conservation with the least cost of total ES value as ecological constraint through excluding ESs trade-offs areas from potential urban development area, and the ecological constraint was further integrated into cellular automata (CA) to develop the ES-CA model for acquiring a win-win simulation between urban development and natural environmental protection. The case study of Hangzhou was implemented for the model application. Equivalent ES value was adjusted by spatial difference assessment to evaluate and visualize ES. Spearman correlation coefficient was adopted to retrieve the relation mechanism among different ESs and extract ESs trade-offs areas. Two alternative scenarios whether conserving the ESs trade-offs areas were established to investigate the unique advantages of the ES-CA model over the traditional ecological constraint-based CA. The comparative analysis using habitat quality and landscape metrics indicated that the urban growth pattern where the ESs trade-offs areas were prohibited for construction performed more effective in reducing habitat degradation, promoting land use compactness, and controlling sprawling urban expansion. According to the win-win scenario, the UGB having a polycentric spatial structure was delineated. In contrast with the planned UGB determined by socio-economic development policies, the proposed UGB demonstrated that the ES-CA model could play a more important role in growth management for ecological fragilely developing regions. [ABSTRACT FROM AUTHOR]

Inequity in education is a serious social problem in developing countries. This study aims to explore an integrated model and evaluate the spatial equity of primary school facilities based on GIS technology in terms of three perspectives including accessibility, facility quality and supply–demand relationship. In this study, an integrated equity evaluation was established. Then an ideal spatial distribution of schools was described, and the equity of primary schools in Hangzhou's urban central area was measured. Meanwhile, the relationships among the equity of primary schools and urban population change, urban land expansion, housing price distribution and urban spatial structure were analyzed. The results revealed the spatial inequity of primary schools in Hangzhou. Specifically, (1) the high-quality educational outcome significantly related to student–teacher ratio, per capita financial expenditure for education, and land cost. (2) The accessibility of primary schools did not match the population suburbanization. (3) Inequality in the quality of education worsened social stratification since the quality of primary schools affected regional housing prices. (4) The population flow based on the quality of educational facilities influenced the supply–demand relationship of educational facilities. Our study is believed to deepen the understanding of spatial equity in education based on the urban spatial structure in urban planning. It offers new insights for educational facility planning. [ABSTRACT FROM AUTHOR]

Accurate monitoring of urban regions and urban sprawls is critical to the detection and assessment of regional development. The nighttime light images of Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) provide us direct solutions to make spatial descriptions of urban regions. Unfortunately, accurate monitoring of urban regions is apt to be hampered due to the shortages of the DMSP/OLS data. In this study, we utilized a new urban region extraction strategy based on the edge-detection method which is widely applied in automatic digital image processing. The edges of urban areas in Zhejiang province were identified based on the distributions and values of pixels. Compared with other traditional methods, the urban regions extracted in this study present a higher overall accuracy and kappa coefficient (OA = 93.1409%; Kappa = 0.8755). Two periods of the urban dynamic process and urban sprawl pattern in Zhejiang from 1992–2013 were further detected by the proposed method. At city level, the drastic increase in urban areas was found in cities of Hangzhou and Ningbo. This study provides an objective and convenient solution to the accurate identification of urban regions, which is also an important step to better understand the urban dynamics and urban development. [ABSTRACT FROM AUTHOR]

Bicycle sharing has become an increasingly popular transportation option for promoting non-motorized transport and reducing automobile dependence. Hangzhou, China currently has the largest bicycle-sharing program in the world; however, this program faces challenges from the dynamic and unevenly distributed demand for public bicycles and docking spaces. In this study, we propose an approach for understanding the spatiotemporal patterns of bicycle sharing activities by analyzing bicycle usage data streams from approximately 1500 bicycle stations collected at one-minute intervals for the entire month of October 2012. To extract useful information from this large dataset, we extract the spatiotemporal dynamics of public bicycle usage and apply a fuzzy clustering algorithm to cluster bicycle stations into various types based on temporal distribution of usage over a day. We then employ spatial regression models to assess the relationship between the type of stations and corresponding locational characteristics after controlling for the spatial dependence of neighboring stations. The proposed approach offers useful insights that could support the operation of bicycle sharing programs. The study also demonstrates the enormous potential of mining emergent big datasets, such as urban sensing data streams, for improving transportation infrastructure management and urban planning practices. [ABSTRACT FROM AUTHOR]

As an important element of urban landscapes, park plays an important role in building environmentally sustainable cities. Thus, it is important to examine park accessibility and how it changes over time in relation to community deprivation so as to provide all residents with equitable services. Using the Gaussian-based 2SFCA (two-step floating catchment area) method, this paper analyzes dynamic park accessibility from 2016 to 2018 for communities within the Hangzhou metropolitan area in China and then quantifies the relative role of local contributors to park accessibility changes (population, park and transport network). A machine learning algorithm, which handles the interdependences of deprivation dimensions, is further employed to determine the relationship between community deprivation and park accessibility changes. Results show that park accessibility continued to grow during the study period, and most communities achieved excellent park accessibility by 2018. Population decreases and park increases contribute positively to improved park accessibility, while transport network changes have had less of an impact. Deprived communities have observed a rising trend of park accessibility, while the elderly concentrated communities are more likely to experience declined park accessibility. Our study provides a new methodological framework, which integrates the geographical accessibility model, economic chain substitution model and machine learning algorithm, for understanding the dynamic park access and associated social inequalities in rapidly urbanizing regions. The lessons learned from this study should be insightful for urban planning. [ABSTRACT FROM AUTHOR]

In early modern China, several modern construction plans were carried out in Hangzhou's ancient city centre and West Lake, leading to the formation of a lake-city combined urban form, which is now valued for its uniqueness and characteristically Chinese cityscape aesthetic. The catalyst for this process of combining the ancient city and West Lake was a plan titled ‘Building a New Market’ (1914), developed on the basis of a draft presented in the Zhejiang provincial assembly during the late Qing Dynasty, striving for urban renewal by promoting West Lake. After the Xinhai Revolution, seizing the opportunity of physical and temporal changes, local officials successfully implemented this plan by using pioneering planning methods to strengthen the link between the ancient city and West Lake. The steps of this plan's implementation, namely ‘pull down the city wall – build roads – construct new market’, widely influenced other cities in the early 1920s. Also, this plan led to two subsequent projects, the Circling Road plan (1920) and West Lake Expo (1922/1927), furthering the urbanization reform of West Lake aimed at making it part of the city. [ABSTRACT FROM PUBLISHER]

China is undergoing one of the most intense and rapid processes of urbanisation in the world today. It also has one of the most centralised planning systems, which is driven by a Soviet-style, five-year plan. Edward Denison looks at the relationship between China's highly systematised planning process and the high-density, standardised form that urban development typically takes. Amidst this formal context, he locates a 'whisper' of change afoot for architects. [ABSTRACT FROM AUTHOR]

With rapid urbanization in recent decades, more and more urban renewal has taken place in China. Meanwhile, the early developed areas without change have become old towns, which need special attention in future city planning. However, other than field surveys, there is no specific method to identify old towns. To fill this gap, we used time-series image stacks established from Landsat Surface Reflectance Tier 1 data on the Google Earth Engine (GEE) platform, facilitated by Global Urban Boundary (GUB), Essential Urban Land Use Categories (EULUC) and Global Artificial Impervious Area (GAIA) data. The LandTrendr change detection algorithm was applied to extract detailed information from 14 band/index trajectories. These features were then used as inputs to two methods of old town identification: statistical thresholding and random forest classification. We assessed these two methods in a rapidly developing large city, Hangzhou, and subsequently obtained overall accuracies of 81.33% and 90.67%, respectively. Red band, NIR band and related indices show higher importance in random forest classification, and the magnitude feature plays an outstanding role. The final map of Hangzhou during the 2000–2018 period shows that the old towns were concentrated in the downtown region near West Lake within the urban boundaries in 2000, and far fewer than the renewed areas. The results could serve as references in the provincial and national planning of future urban developments. [ABSTRACT FROM AUTHOR]

Urban land use is constantly changing via human activities. These changes are recorded by imprint data. Traditionally, urban dynamics studies focus on two-dimensional spatiotemporal analysis. Based on our best knowledge, there is no study in the literature that uses imprint data for better understanding urban dynamics. In this research, we propose a spatial–temporal–semantic triple analytical framework to better understand urban dynamics by making full use of the imprint data, toponyms. The framework includes a text classification method and geographical analysis methods to understand urban dynamics in depth. Based on the inherent temporal and spatial information, we enrich semantic information with street names to explain urban dynamics in multiple dimensions. Taking Hangzhou city as an example, we used street names to reproduce the city changes over the past century. The results obtained through analysis of street names may accurately reflect the real development process of Hangzhou. This research demonstrates that imprint data left by urban development may play a pivotal role in better understanding urban dynamics. [ABSTRACT FROM AUTHOR]

The long-term changes of the relationship between nighttime light and urbanization related built-up areas are explored using nighttime light data obtained from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS, data before 2013) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP/VIIRS, data after 2012) and information of the spatiotemporal heterogeneity of urban evolution. This study assimilates two datasets and diagnoses the spatial heterogeneity in administrative city scale based on built-up area tendencies, temporal heterogeneity in pixel scale based on nighttime light intensity tendencies, and GDP associated spatiotemporal variability over the Yangtze River Delta comparing the first two decades of this century (2001–2010 versus 2011–2019). The analysis reveals the following main results: (1) The built-up areas have generally increased in the second period with the center of fast expansion moving southward, including Suzhou-Wuxi-Changzhou, Hangzhou, Ningbo, Nanjing, and Hefei. (2) Urban development in the original city core has saturated and is spilling over to the suburbs and countryside, leading to nighttime light intensity tendency shift from a "rapid to moderate" and a "moderate to rapid" development (a "hot to cold" and a "cold to hot" spatial clustering distribution). (3) The tendency shifts of built-up area and nighttime light intensity occur most frequently in 2010, after which the urban development is transforming from light intensity growth to built-up area growth, particularly in the developed city cores. The urban agglomeration process with nighttime light intensity reaching saturation prior to the urban development spreading into the surrounding suburbs and countryside, appears to be a suitable model, which provides insights in addressing related environmental problems and contribute to regional sustainable urban planning and management. [ABSTRACT FROM AUTHOR]

Urban energy simulation can provide valuable information to urban planning, urban energy management, and urban emission reduction. Therefore, urban energy simulation has become an active research discipline. Various urban energy simulation methods and techniques have been developed and applied to cities on different scales. A review is conducted to categorize these methods and techniques and to analyze their pros and cons. Several representative methods and techniques are compared for their data inputs, suitable scales, accuracy, and computing speeds. Hangzhou South Railway Station area, which contains 522 buildings, is used as the case to evaluate the effectiveness and challenges of different urban energy simulation methods. [ABSTRACT FROM AUTHOR]

Urban land-use information is important for urban land-resource planning and management. However, current methods using traditional surveys cannot meet the demand for the rapid development of urban land management. There is an urgent need to develop new methods to overcome the shortcomings of conventional methods. To address the issue, this study used the random forest (RF), support vector machine (SVM), and artificial neural network (ANN) models to build machine-leaning methods for urban land-use classification. Taking Hangzhou as an example, these machine-leaning methods could all successfully classify the essential urban land use into 6 Level I classes and 13 Level II classes based on the semantic features extracted from Sentinel-2A images, multi-source features of types of points of interest (POIs), land surface temperature, night lights, and building height. The validation accuracy of the RF model for the Level I and Level II land use was 79.88% and 71.89%, respectively, performing better compared to SVM (78.40% and 68.64%) and ANN models (71.30% and 63.02%). However, the variations of the user accuracy among the methods depended on the urban land-use level. For the Level I land-use classification, the user accuracy was high, except for the transportation land by all methods. In general, the RF and SVM models performed better than the ANN model. For the Level II land-use classification, the user accuracy of different models was quite distinct. With the RF model, the user accuracy of educational and medical land was above 80%. Moreover, with the SVM model, the user accuracy of the business office and educational land classification was above 75%. However, the user accuracy of the ANN model on the Level II land-use classification was poor. Our results showed that the RF model performs best, followed by SVM model, and ANN model was relatively poor in the essential urban land-use classification. The results proved that the use of machine-learning methods can quickly extract land-use types with high accuracy, and provided a better method choice for urban land-use information acquisition. [ABSTRACT FROM AUTHOR]