Journal of Urban Planning and Development

Owing to recent advances in information communication technologies, trail data, i.e., movement logs of people on the road or on trains, can be acquired on a 24-h, 365-day basis, some of which have yielded real-world applications. Generating highly granular origin-destination trip data from the operational data of mobile networks would significantly advance the methodology for actualizing and broadening the field of applications in urban transportation planning. This paper proposes a method that estimates origin-destination trips on the basis of mobile network operational data, referred to as mobile spatial dynamics. Statistics are generated using a three-step process comprising anonymization, estimation, and disclosure limitation. Unlike other studies conducted thus far, this study uses large-scale person trip survey data to validate the reliability of estimated origin-destination trips between regions. Analysis of the use cases shows that the proposed method has the potential for mobile spatial dynamics to complement person trip surveys and road traffic censuses.

The exacerbation of the concentration of population and economic activities in a few core metropolitan areas has become an urgent issue for China’s regional development, and necessitates a more polycentric spatial development pattern. Transportation infrastructure improvement can serve as a vital instrument to achieve the objective of polycentric spatial development. Focusing on the 10 megaregions of China, this research examines a fundamental issue for China’s urban and regional development in the context of massive investment in highway and railway: the impacts of road and rail network on the spatial pattern of growth and development. Using the county-level national censuses of 1982, 1990, 2000, and 2010 and the historical transport network geographic information system (GIS) data, this paper analyzes the differentiated effects of road and rail for population growth. The research results revealed the stronger positive growth impacts of rail compared with road, and further examination indicates that railway has stronger positive impacts for regional growth in the less-developed areas.

In order to improve the statistical analysis ability of green gross domestic product (GDP) development in cities, a green GDP development planning and prediction model based on an analytic hierarchy process (AHP) is proposed. Statistical variables are variables such as echo sounding, profitability, green economic development level, and residual capital of urban green GDP development. According to the variables, we used the AHP to calculate the resource and environment cost accounting, constructed the constraint parameter model of the urban green GDP development, and used the descriptive statistical analysis method to perform statistical analysis of the urban green GDP development plan and perform a paired sample test on the sample. The independent sample test uses logistic regression analysis to predict the urban green GDP development plan and a management strategy adjustment method to predict the urban green GDP development. The evaluation plan and AHP are used to quantify the green GDP development plan of the city.

The main function of the quota of construction land, which is generated through famers reclaiming their idle homesteads, is to have the land be developed in advance. The value of the quota is the added time value due to advanced development of the land. However, the quota is currently priced based on the reclamation cost, which is unreasonable and fails to stimulate farmers to supply quotas. Aiming at the characteristic of complementarity between the quota and the land, this paper develops a two-stage sequential auction model of complementary products to study the pricing mechanism of the quota. Through theoretical and numerical analyses, this paper obtains the equilibrium bidding price of the developers, and the expected income of the farmers. We found that our mechanism can make all developers reveal the true value of the quota for them and is a reasonable and feasible pricing mechanism. The bidding price of all bidders on the quota decreases with the increase of the number of bidders, but increases with the rise of the fee for idle land. The equilibrium bidding price on the land of the bidder who wins the quota increases with the rise of the fee for idle land. Therefore, the government should raise the fee for idle land, to increase the bidding price of the quota and the land. As a result, more farmers would be stimulated to reclaim their idle homesteads, and the efficacy of land use would be improved.

A smart city plays an increasing role in citizens’ daily life. A smart city has six main components, namely smart mobility, smart economy, smart governance, smart living, smart environment, and smart people. For the past several decades, government and organizations throughout the world have initiated many smart city projects. Citizens’ transportation, education, investment, and other activities have been shifted from traditional to smart models through emerging technologies and the internet. In this paper, following the pioneering work of the intelligent quotient (IQ) test, we propose a framework to measure a city's intelligence level. We also propose a definition for the intelligence of an information system. To evaluate such intelligence, 382 technology indicators have been developed. We have applied smart city IQ testing on the top 100 largest cities in the United States (according to 2017 population). In addition, the smart city IQ score is designed so that it is convertible to the age of a human being. Various text mining and data mining methods (including classification) have been applied. The results of our analysis indicate that the average smart city IQ score is like that of an eight-year-old child. We also show the breakdown of IQ scores in terms of the six main components. Although the evaluation of the smart city projects in the United States is still ongoing, the results obtained so far as reported in this paper can provide important insights for research in this particular field, as well as intelligent information systems in general.

America's Housing Affordability definition classifies those households as stressed that spend more than 30% of their net income on housing. This paper challenges the traditional economic criteria-based approach that ignores the social and environmental parameters. Authors offer a geographical information science (GIS)-based Multicriteria Decision Analysis, selecting Corvallis, Oregon to prove the applied impact of the proposed methodology. Using experiential literature and interviews with specialists, the research establishes a comprehensive set of housing stress indicators including demographic, housing quality, and commuting time variables. Raster overlay and zonal statistics were deployed to obtain the final housing stress map. The strain was highest in the low-density single-family zone that contained dilapidated housing and longer commuting times, in contrast the stress was lowest for the mixed-use residential. GIS results were then used to make recommendations for affordable housing by channelizing favorable allocation of resources through spatially targeted efforts. This innovative method has a great potential to prioritize improvements based on the accumulated stress scores for each zone and contributes toward the improvements in understanding, examining, and measuring housing stress worldwide.

This research investigation falls in the very few studies that seek the association between city development and sustainable urban planning. This study emphasized to examine and explore effects of urban village disamenity on Nanjing suburban and posh area property valuation. Globally, slums exist in almost every country; however, researchers focused less on slums’ crumbled infrastructure, crimes, and other social problems; however, few kinds of research studies covered the adverse impact on the property value. This paper plans to seek the effects of rural area migrants on Nanjing City in response to the late 1970 economic reform implementation as they aimed to extract benefits of reforms offering enhanced economic opportunities, higher rate of income and employment, and comprehensive social benefits. This study examined the negativity of urban villages on the surrounding area valuation and its impact on residential properties. The results of this study specified an adverse effect of urban villages on the value of nearby apartments; however, residential units closer to these villages experienced the worst impact compared to the residential apartments located far away. The findings revealed that urban villages' neighborhood negatively influences home selling value when compared with other houses located far away. This study is helpful for government officials and policymakers to resolve urban villages' issues.

Collaborative governance is the idea that governments, civil society, and private actors can engage in collective policy-making processes. However, which structures and practices facilitate or hinder the deliberative dimension of collaborative governance? This research is based on case studies of urban planning processes carried out in Curitiba (Brazil) and Montreal (Canada). Using 20 semistructured interviews with key informants, planning documents, and media coverage, the study identified the crucial moments and key determinants in the interactions between public and private actors. Despite their disparate histories of urban planning and management, both case studies revealed significant commonalities, namely the varying extent of collaborative interactions among stakeholders according to the type of actors involved, the arena, and the phase of the planning process. The success of the democratic reform in Curitiba was undermined by the maintenance of informal institutions, whereas consultation fatigue explained the lack of participation in Montreal. Although based on a small number of cases and plans, our findings revealed the mechanisms, factors, and processes that could help transition urban planning processes from informative/consultative practices to collaborative governance models.

Most African countries in the world currently face significant conflict on how colonial spatial planning legislation governs contemporary spatial planning practices. Spatial development is controlled by various pieces of spatial planning legislation, which include statutes and bylaws. The spatial planning legislation that was in place before Zimbabwe and Zambia attained independence influenced development and this continues to date. This paper focuses on how colonial spatial planning legislation influenced and still influences spatial development in Zimbabwe and Zambia. The methodology of this paper includes a review and analysis of published documents on spatial planning. The spatial planning legislation for both countries will be reviewed. This paper noted that British colonial spatial planning legislation was biased toward Europeans and disadvantaged Africans. This paper reveals that colonial spatial planning legislation influenced spatial development in both colonial and postcolonial Zimbabwe and Zambia. The implanted aspects of the legislation were difficult to recover from, especially in Zimbabwe. However, Zambia reviewed its spatial planning legislation in 2015 and adopted sustainable integrated development plans.

Autonomous and connected vehicle technologies have the potential to bring profound changes in travel behavior and transportation network performance with moderate to significant market penetration rates (MPRs) within the next few decades. To better understand the long-term impacts of these technologies, this study predicts the network-level effects of privately owned autonomous vehicles (AVs) and connected and autonomous vehicles (CAVs) for the Triangle Region, North Carolina, in the year 2045. Market penetration scenarios of personal AVs and CAVs along with results from microscopic mixed-traffic simulations and travel behavior assumptions are incorporated into a regional travel demand model. Results indicate that a 75% MPR of personal AVs deteriorates the performance of the network, leading to a 5.4% increase in vehicle-hours traveled, and a 17.2% increase in hours of delay. The opposite holds for private CAV adoption, which is found to result in higher peak-period link speed and less congestion. The results of this research help planners and engineers to make informed transportation planning decisions and work toward harnessing the benefits of these technologies while minimizing any negative impacts.

Recently, computer–physical systems provide a critical service together with physical and computer elements including integrated and robust medical services, a smart electricity grid, the green cloud, and air traffic control. While sustainable energy is becoming increasingly important as globally concern issues are being recognized, and energy supply and uses are becoming critical. To provide this ubiquity, energy efficient and cheap functionality to cyber physical systems, the information available from the physical environment is required under the related law. This paper describes a sustainability cyber construction resource modeling algorithm, which, via a broad range of real-world data, almost builds a smart city model with a distribution network (DN). It consists of different energy management systems models that control consumer power systems and simulate energy, loss, and tension flux in the DN. In addition, scenarios such as photovoltaic deployment and the penetration of electric vehicles estimate indices that calculate the sustainable urban model, for instance carbon emission to address social security issues. It is possible to view the tests and the interface as extremely versatile and ideal for different types of intelligent city problems.

Making cities smart is an inherent goal and challenge for contemporary cities. This phenomenon becomes more complicated when there is an urgent need to adopt smart city principles against the backdrop of visible and invisible factors that cause urban transformations with varying magnitudes. One type of visibly invisible factor is e-commerce and its expanding operation that is understood to cause changes to a city’s conventional spatial structure. However, very limited research exists about its momentum and pervasive magnitude of impact. Current literature predominantly focuses on the relationship and effect of e-commerce on transportation studies – notably, the influence of e-commerce on the direction and volume of traffic flow, the changing dynamics of logistics, and operational strategies. As a transitory variable, how e-commerce is going to influence a city's conventional spatial structure, the interwoven relationship between the city core, fringe, and rural areas, and in building smart cities remains unclear. This paper will attempt to explore the changing dynamics of a city’s spatial structure with a specific focus on e-commerce induced changes in the retail landscape. Specifically, this paper aims to theoretically gauge the nature of these changes, which include division and fragmentation, reconceptualization, and relocation of retail stores and conceptually capturing the scenarios through critical analysis. Contemporary evidence further substantiates the need to account for e-commerce induced influence on contemporary thoughts on smart cities. Essentially, this stems from the requirement for a systemic analysis that explains the path-dependency framework of the complex relationship between e-commerce and shifts in a city’s changing spatial structure. Based on the requirement for a path-dependent analysis, this paper calls for an ideological shift in the conceptualization of a smart city definition from a concept to a process. It argues that such a shift has a critical impact that determines what makes cities truly smart.

This study will estimate the impact of population size, population density, urbanization level and economy-related parameters on the proportion of trips with that have varied trip lengths for work purposes in India, which uses a fractional multinomial logit model. Data from 232 districts of India that have at least one city or town with a population >0.1 million will be used. The analysis shows the positive impact of the district's population size and economy on the proportion of trips longer than 5 km. In addition, there is a positive impact from the overall population density and a negative impact from urban density on the share of long-distance trips. This study shows that as districts in India continue to urbanize and develop economically, the propensity for traveling long distances will probably increase. This will result in an increased dependency on motorized modes of transport that negatively impacts the environment, resource consumption, and human health. This study identifies the need for the adoption of development control regulations and policies to maintain the proportion of long-distance trips at a low level as India continues to urbanize. The findings of this study could be useful to project externalities of the transport sector in future years when the urbanization pattern is considered.

The landscape character of metropolitan areas faces the problem of competition between protection and development. This study explores the synergism of management, protection, and development of landscape character diversity (LCD) under the influence of the inherent sensitivity of cities and landscape resource. An overlay analysis using elevation, topographic relief, and land cover identified 30 landscape description units in the Wuhan Metropolitan Area. A spatial distribution pattern of LCD was obtained using the Shannon diversity index and the moving window method, and urban influence (UI) was calculated using UI sources and a minimum cumulative resistance model. Overall landscape sensitivity (OLS) was determined by evaluating the inherent sensitivity factors from the resources and visual aspects of the landscape and establishing the weight of single factors. An integration framework for LCD, OLS, and UI was constructed, and five landscape character management and protection areas were described and corresponding strategies proposed. The method proposed can be used for scientific management and protection zoning, as a valuable reference for subsequent landscape policies and landscape character assessment research.

This study aims to improve the applicability of transit-oriented development (TOD), which is widely recognized as a sustainable urban land use planning approach, this study will focus on the effect of developed land blocks on undeveloped land blocks around the same metro station. A new multiobjective programming model that optimizes metro ridership, land use compactness, transport accessibility, land functional mixing degree, land use conflict degree, and environment influence will be developed to integrate land use design with transport planning. In addition, an improved immune genetic algorithm (IGA) will be designed to generate land use schemes, which takes into consideration transport impacts and environmental influence. In this study, the land use and transport conditions around a metro station in Beijing will be studied to validate the newly developed multiobjective programming model and the improved IGA. This demonstrated that the proposed multiobjective model and IGA could effectively provide more rational land use and transport integration solutions for TOD.

Consumers are becoming progressively demanding in urban commerce with the booming development of the internet and e-commerce. Recent research on location selection for commercial centers either involved the use of a variety of indexing systems to aid in decisions about site selection or the consideration of general factors, such as area and distance. However, numerous commercial centers located in superior geographical positions are still facing the issue of increasing tourist footfall, resulting in the need for renewal and reconstruction. Although existing studies have shown that the vitality of commercial districts and residential emotion are critical factors in consumer decision-making, current practices for selecting the locations of commercial centers do not involve fully taking these factors into account. This research proposes the use of a competitive location selection method to improve this situation. Multisource data, including geographical and spatial information, are used to objectively quantify commercial vitality and show individual characteristics in greater breadth and depth. Considering the current situation, from the business perspective, the vitality of commercial districts and residential emotions are combined to redefine commercial attraction. The Huff model, a representative model used for competitive location selection, is adopted to provide suggestions for the location selection of commercial competition based on the vitality of commercial districts and residential emotion factors. Furthermore, a case study is presented to illustrate that the proposed method is feasible for the selection of comparatively appropriate locations for a new commercial center. Thus, it is a reliable tool for the development of traditional commerce.

Chinese cities have experienced unprecedented growth in the past few decades. In this context, the rapid rise of housing prices in Chinese cities makes the affordability of homeownership one of the biggest challenges related to people's livelihood. As a forming part of public housing, affordable housing in China mainly targets medium and low-income urban residents who cannot afford commodity housing. The spatial site selection and layout of affordable housing, which becomes a challenge for urban planners and policymakers, is potentially related to a spatial differentiation and the spread of poverty. In this study, we propose a conceptual model of spatially subsidized benefits (SSBs) of affordable housing by combining affordable housing prices and ordinary commodity housing prices in the same or adjacent location in the city. Moreover, by integrating the multiple digital elevation models (DEMs) with geographic information systems, we design a prototype for the spatial decision support system of affordable housing, which takes into account the cost of land for government, public transport facilities, residents' spatial demand, and the prevention of spatial differentiation. Using the case of Wuhan (China), we simulate the spatial layout of the SSBs of affordable housing in the city under multiple hypothetical scenarios. Our results show that SSBs display clear hierarchical characteristics under different scenarios. The findings indicate that the quantitative spatial decision method based on SSBs can provide effective technical support for Chinese urban planners or policymakers to realize a scientific layout of affordable housing under different scenarios, avoiding the risk of spatially differentiating low-income residents. Further, it also provides some insights into the innovative application of multiple DEMs in urban planning.

This paper explores sport mega-events' impacts and their relation with urban sustainability based on physical, environmental, economic, and social–cultural dimensions. The physical impacts are singled out because, in the case of sport mega-events taking place in cities, it is advisable to incorporate this new dimension for lack of proper fit of the costliest Olympic projects in the three established dimensions: environmental, economic, and social–cultural. It examines the alignment of event planning and implementation actions with a set of urban sustainable development goals selected through 63 indicators derived from literature review spanning from 2000 to 2016 on a range of outcomes and impacts of the most recent sport mega-events. The intensity of the Olympics' impacts was assessed in the city of Rio de Janeiro, which hosted the last games, through a survey of Brazilian experts. The ranking of impact intensity pointed out that this sport mega-event had much larger negative than positive impacts in Rio in all four dimensions, especially in the environmental dimension. Weaknesses of planning and development control, high consumption of water and energy, nonrecyclable waste, and price increase of goods and services were the highest negative impacts in the city. The increase of international reputation and exposure was the social–cultural factor that received a more positive evaluation from the Brazilian experts.

Sustainable housing has been an overarching goal globally, and Ghana is no exception vis-à-vis the country’s energy and housing affordability challenges particularly in cities. Yet, its implementation has been plagued by barriers. This study assesses the influence of barriers on sustainable housing in Ghana. Forty-seven valid responses were obtained from a questionnaire survey. Confirmatory factor analysis validated three main groupings of barriers: “cost-related,” “incentive-related,” and “retrofit-related.” Partial least square structural equation modeling of the responses showed that incentive-related barriers have medium effect size (0.192) on sustainable housing while retrofit-related barriers have high effect size (0.430) on sustainable housing. Furthermore, incentive-related barriers have a significant impact on retrofit-related barriers. Cost-related barriers only had a significant impact on incentive-related barriers. Accordingly, cost-related barriers are secondary barriers to sustainable housing. The findings apprise policymakers of barriers that require efficient resource allocation for sustainable housing for sustainable built environment.

Urban shrinkage has been witnessed often throughout the history of Western cities and occurs concurrently with population loss, economic decline, neighborhood decay, and other profound changes to urban spaces and the built environment. Unlike in the Western context, urban shrinkage in China has occurred concurrently with rapid urbanization and urban growth, marking a relatively new urban phenomenon, known as regional urban shrinkage, that has recently emerged in large Chinese cities and metropolitan areas. This study aims to better understand regional urban shrinkage by identifying such shrinkage and exploring its mechanisms in Wuhan, a megacity in Central China. Drawing on population data, land-supply data, and night-time light data, this study first identifies areas of regional urban shrinkage through the dimensions of demography, land use, and economy and then conducts a qualitative investigation of Wuhan’s Qingshan District as a pilot study to explore the mechanisms and causality of regional urban shrinkage from the perspectives of antiglobalization, industrial transformation, and capital circuits. This study expands the research paradigm of urban shrinkage in the Western context to Eastern society by contributing an empirical study conducted in China and broadens current scholarship by focusing on the complexity, contextualization, and localization of urban shrinkage.

Much attention has been paid to the relationship between the built environment and walking behavior. However, the findings are mixed due to different quantitative measures based on different research purposes or at different geographical scales. Various geographical scales to define neighborhood increase spatial uncertainty, which could make research outcomes biased. Drawing upon a household travel survey in Salt Lake County, Utah, this study implements a multiscale analysis to explore the people's walking behavior. A spatial filtering method is employed to examine the determinants of the walking density of the trip ends at the block level. We also construct a destination choice model to explore the determinants of people's mobility by walking at the trip level. The results suggest that a compact design and high population density contribute to high walking density but decrease walking mobility. Furthermore, mixed-land use does not help generate walking trips but creates destinations for walking and increases walking mobility. The geographically weighted regression (GWR) model suggests that the impact of mix-land use on people's walking behavior is sensitive to the local context. We also find that air pollution and traffic volume negatively influence the walking density and mobility.

Worldwide, growing populations and increasing numbers of vehicles have caused a parallel increase in demand for parking areas. Metropolitan cities, especially, are suffering from lack of parking areas. These areas are one of the significant parts of the modern urban transportation system and have significant effects on decreasing traffic loads. Finding the best location for parking areas has become a major challenge for both urban transportation planners and policy makers. This study aims to design an exemplary geographic analytics method for determining parking demand and locating parking areas using the Pendik district of Istanbul (Turkey) as a case study. Parking demand and supply analysis was performed using map algebra in the Geographic Information Systems (GIS) environment. Parking demand was calculated by integrating multiple selected parameters simultaneously, including housing demand, workplace demand, fixed demand, and dynamic demand. After calculating and evaluating parking demand, the location–allocation methods of network analysis were implemented to allocate parking locations based on parking demand and supply. In conclusion, this approach gives a novel data-processing method that determines parking facility locations more accurately to support transportation planning and support sustainable urbanization.

Price of a housing unit can be influenced not only by cost of construction but also by the buyers' evaluations of various attributes associated with the house. It varies across space and time depending on the characteristics of houses and preferences of the potential buyers and their capabilities. This paper examines the impact of various structural, locational, and neighborhood attributes on housing demand of the residents in the town of Dimapur in Nagaland, India. A hedonic pricing technique has been employed for the purpose of estimating housing demand with individual quantitative and categorical variables, along with locational indexes as regressors. The ward-wise variation in house price has been examined by using spatial dummies. The combined impacts of all the three attribute groups on the housing prices (or rent) reveals that with respect to tenants, six structural attributes and four locational attributes significantly affect the monthly rent. In case of owner-occupied respondents, however, only three structural attributes have significant impacts on housing price. Spatial variation in monthly rent is also significant and households residing in wards closer to the main market pay significantly higher rent than do those living far away from the center of town. The findings suggest a need for an even distribution of government and other institutions across wards and also at the outskirts, with proper development of infrastructure and other facilities. It would help in appropriate spatial distribution of housing demand and maintenance of social housing environment.

The exploration of park use and its affecting factors is necessary for urban park planning and management. Using big data, 70 urban parks in Wuhan were selected as the study objects in the present study. Two groups of linear regression models were developed to examine the effects of various factors on park use. The total numbers of visits and public demands in urban parks were recorded as 1,291,894 and 4,022, respectively. Social media data reflect visits, while public demand data reflect demands. First, a large area and sufficient facilities greatly help improve park use; moreover, we should pay attention to old urban parks in disrepair. More squares need to be considered in urban parks; attention should be paid to the water pollution and safety concerns that may arise in urban parks. Second, the influence of accessibility on park use is stable. It is beneficial for park use to construct greenways connecting residential areas and urban parks. The layout of pocket parks in the city center is also a feasible way to improve park use. Third, to improve park use, we should arrange commercial entertainment facilities and services in urban parks in point of interest (POI)-rich areas, as well as facilities and services for residents’ daily activities in urban parks in population-rich areas. This study provides a way to combine multisource data that reflect the number of park visits and park demands to explore affecting factors of park use.

The users' taste preferences for the demand responsive customized bus (DRCB) and, in particular, the its mechanism of heterogeneity, which determine routing, timetabling, and even launch and cancellation of the DRCB service, have not been given enough attention. Using a stated preference experiment in the context of mode choice between DRCB and a conventional bus conducted in Dalian, China, this study investigated observed and unobserved heterogeneity in sampled commuters' taste preferences within a mixed multinomial logit model. In addition to unobserved between-individual heterogeneity in time-related preferences, the model identified gender and mode-specific differences associated with fare. A fourfold pattern of fare sensitivity was revealed, which offers useful information for pricing decisions. The model outcomes of this study, along with the market performance the empirical case, suggest that, for specific urban settings, DRCB has great potential to draw commuters from their private cars, by delivering personalized, comfortable, and affordable services.

Unlike shrinking cities in Western countries enduring prolonged disinvestment due to market liberalism, some of their counterparts in Northeast China are undergoing drastic redevelopment under state capitalism. However, the challenges and effects of implementing such redevelopment in shrinking cities remain to be seen. This study examined a specific state-led shantytown (quasi-formal settlement) redevelopment policy entitled “Regulation Methods on Shantytown Redevelopment in State-Owned Forestry Areas” that was designed and implemented in state-owned forestry areas beginning in 2010 to construct affordable housing and compensate local residents adversely impacted by the logging ban initiated in 2000. The study analyzed the implementation of this policy in Yichun, a shrinking forestry city in China’s rust belt (Northeast China). The implementation of this policy differs from China’s typical privately funded market-led redevelopment in other areas, in terms of combining the rigorous implementation of central government’s policy and funding in tandem with the discretionary actions of the local state-owned forestry bureau. Although the Regulation Methods policy has improved the living conditions of participating families’, it has been only partially implemented and is facing three major challenges: the unstable partnership between different tiers of government, social resistance from grassroots, and overdraft of local credibility and capability. This study concluded that the Yichun case represents a case of problematic state-led redevelopment (analogous in some ways to US postwar urban renewal) where state planning power does not adequately address public needs, particularly household socioeconomic considerations and thus will not save shrinking cities from population decline.

Urban green space is an important place to satisfy people's aesthetic appreciation, recreation, safety, and cleanliness. In addition, it plays a crucial role in improving the ecological quality of urban environments. How to enhance people's satisfaction and ecological quality simultaneously when planning urban green space is a new topic for urban planners. To address this issue 26 sample sites of urban green space in Xuzhou, eastern China were selected to evaluate their abilities to satisfy people by measuring four items: aesthetic preference, recreation, perceived safety and cleanliness, and ecological quality was quantified by the urban green space habitat quality index. Then, the coexistence of satisfaction and ecological quality was calculated. Further, 15 landscape characteristics that were abstracted to describe the objective features of the sample sites were evaluated. The main results showed that there is no significantly statistical relationship between people's satisfaction and ecological quality; increasing the diversity of plants and keeping natural waterscape are efficient ways to achieve people's satisfaction and ecological quality simultaneously. These results provide reliable guidance for the design and management of urban green space.

Previous housing price studies based on hedonic price modeling have mainly focused on applying various factors, including built environment variables in the analysis, without establishing a comprehensive theoretical framework as a basis for the model formulation. To address this gap, this study introduces a more systematic framework for decomposing housing prices into land prices as determined by built form, neighborhood socioeconomic characteristics and individual dwellings' physical conditions. Following this logic, this study experiments with the related variables through regression analysis, including consideration of spatial lags, as well as develops a housing price model using a random forests (RF) algorithm. A comprehensive time-series database of housing transaction data for the City of Toronto is used. Modeling results show that neighborhood socioeconomic factors contribute the most to the explanation of housing prices, while housing characteristics and accessibility measures are also significantly influential. The RF model achieves an overall accuracy of 85%, a relatively good performance in reproducing observed prices. The findings provide insights for planners concerning factors influencing housing prices and, hence, residential location decision-making.