Exploring Determinants of Housing Prices in Beijing: An Enhanced Hedonic Regression with Open Access POI DataPublished: 15 November 2017 by MDPI in ISPRS International Journal of Geo-Information
The housing market in Chinese metropolises have become inflated significantly over the last decade. In addition to an economic upturn and housing policies that have potentially fueled the real estate bubble, factors that have contributed to the spatial heterogeneity of housing prices can be dictated by the amenity value in the proximity of communities, such as accessibility to business centers and transportation hubs. In the past, scholars have employed the hedonic pricing model to quantify the amenity value in relation to structural, locational, and environmental variables. These studies, however, are limited by two methodological obstacles that are relatively difficult to overcome. The first pertains to difficulty of data collection in regions where geospatial datasets are strictly controlled and limited. The second refers to the spatial autocorrelation effect inherent in the hedonic analysis. Using Beijing, China as a case study, we addressed these two issues by (1) collecting residential housing and urban amenity data in terms of Points of Interest (POIs) through web-crawling on open access platforms; and (2) eliminating the spatial autocorrelation effect using the Eigenvector Spatial Filtering (ESF) method. The results showed that the effects of nearby amenities on housing prices are mixed. In other words, while proximity to certain amenities, such as convenient parking, was positively correlated with housing prices, other amenity variables, such as supermarkets, showed negative correlations. This mixed finding is further discussed in relation to community planning strategies in Beijing. This paper provides an example of employing open access datasets to analyze the determinants of housing prices. Results derived from the model can offer insights into the reasons for housing segmentation in Chinese cities, eventually helping to formulate effective urban planning strategies and equitable housing policies.
Based on the global land cover data at 30 m resolution (GlobeLand30) in the year 2000 and 2010, the urban expansion process of 320 cities in China was analyzed using lognormal regression, and the expansion model were established. Three metrics were presented for the models, including the peak position, the full width at half maximum, and the skewness. It was found that the three metrics could reveal different patterns of the urban expansion process of cities with different sizes. Specifically, cities with larger size tend to expand outward strongly, and their expansion intensity and influence are likely to be higher. Moreover, most cities’ expansion occurs around the urban core with spatially limited influence. In addition, it was also found that the city’s expansion intensity is related to the city size. These results showed that the lognormal regression model could describe the distribution of urban expansion with effectiveness and robustness.
<p>The resource-based city shows a gradually decline behind the external prosperity in China. It has been identified that there were 262 resource-based cities in China <span>. According to the different stages of development</span>the, <span>the resource-based cities were divided into four types: growing, maturing, exhausting and renewing. Currently, 23 of them which have entered the exhausted post-transition phase of resource were called renewing cities. Thus, the focus of this paper is on the smart growth of renewing cities, whose core elements can be extracted from the essential characteristics showed in the process. Based on the thought of “smart growth” and aspects of “moderate exploitation”, “green ecology” and “social comfort”, the analytic framework of "smart growth", with 9 goals and 40 sets of variables relationships established, is formed. According to the statistical description and analysis of the existing data, in 40 sets of variables, there are 22 sets in line with the "smart growth" requirements; while 15 sets not ; and another 3 sets can not be judged. Finally, based on the results of the analysis, the path of “smart growth” for renewing city can be explained from aspects of city infrastructure supply, land development and utilization, energy saving and emission reduction, environmental protection and city agglomeration promotion, which are the key ares that government should focus on as well. </span></p>
Urban Density, Accessibility and Energy Consumption in the Transport Sector: Analysis of 30 Cities in ChinaPublished: 08 June 2015 by MDPI AG in 8th Conference of the International Forum on Urbanism (IFoU)
<p>The growth and diversification of transport demand accompanied with social and economic development led to increasing energy consumption in transport sector. In order to find a way that can not only contribute to reducing transportation energy consumption but also fully meet the transport demand, the research firstly formulated three indicators. Urban density implies population size and intensity of social and economic activities that is related to transport demand. Accessibility is defined by per capita road area and average bus numbers of ten thousand people and reflects transport conditions of private and public traffic. Per capita energy consumption in transport sector was used to characterize environmental effects. The data of urban density and accessibility was collected from the National Statistical Yearbook, while the data of transport energy consumption was obtained by conversion of DMSP/OLS (Defense Meteorological Satellite Program/Operational Lines-can System) night lighting data which is a sign of human activity. Secondly, considering the different levels of transport infrastructure and economic development in different regions of China, only 30 provincial capital cities were selected to analyze the relationships of the three indicators mentioned above. Based on relationship analysis, 30 cities were divided into three patterns. It was founded that the first pattern would be optimal because of a good match of transport demand and supply coupled with low energy consumption. The second pattern is non-ideal, since it is at high level of energy consumption and less balanced between transport demand and supply. The third pattern should improve accessibility and reduce energy consumption. Finally, some suggestions about urban transport development that are suitable to local conditions were proposed for different urban patterns.</p>
Site planning for parks consists of synthetic strategies to improve visitors’ experience and appreciation of park features. An important aspect in site planning is to coordinate visitor flows in order to avoid excessive congestion that may depreciate visiting experience. An emerging need in the coordination strategies is to personalize visiting routes and enhance the enjoyment of the tour for individual visitors. On the individual level, visitors have diverse preferences for park attractions. Scheduling a tour to visit attractions is restricted by not only the layout of park facilities but also the uncertainty of waiting induced by different lengths of lines at attractions. This paper proposes a tentative solution to optimize the logistics of individual tours by considering the dynamic nature of waiting time at park attractions derived from empirical data. The optimal solution is achieved using the branch-and-bound algorithm and is implemented in a real-world case of Beijing Zoo, a metropolitan zoology park in Beijing, China. The case study provides corroborating evidence for studying the logistical routing of park tours that: (1) visitors arriving at the park earlier can avoid crowds and excessive lines whereas visiting at midday would encounter excessive waiting and (2) the shortest tour route may not necessarily be the most efficient; strategically scheduling the visit to popular exhibits in their off-peak hours could effectively shorten overall tour time. This problem, called the Traveling Salesman Problem with Waiting Times (TSPWT) increases the realism of the routing problem while shedding new light on personalized routing strategies for improving individual touring experience.
Decentralization development and changing urban form will increase the mobility and contribute to global CO₂ emissions, in particular for developing countries which are experiencing rapid economic growth and urban expansion. In this paper, an integrated analytical framework, which can quantify the impact of changing urban form on commuting CO₂ emissions, is presented. This framework simultaneously considers two emission dependent factors, commuting demand and modal share based on the concept of excess commuting and accessibility analysis, and ensures its applicability to other cities where the detailed individual travel data is not available. A case study of Beijing from 2000 to 2009 is used to illustrate this framework. The findings suggest that changing urban form in Beijing did have a significant impact on commuting CO₂ emission increase. Changing to a more decentralized urban form in Beijing had a larger impact on commuting distance and increased usage of cars, which resulted in a significant rise in CO₂ emissions. There is a larger space and an urgent need for commuting CO₂ emission reduction, in 2009 in Beijing, by planning and by strategic measures in order to promote sustainable transport.
The problem of emergency facility location is a critical component in evacuation planning. The emergence of geographic information systems (GIS) has provided a useful operational platform to assist this issue. A previously overlooked facet is the consideration of a hierarchical structure in the placement of emergency shelters. Due to the fact that survivors' needs change over time during post-disaster evacuations, shelters have now been categorized on a temporal scale based on their functions at different evacuation phases. This article proposes a three-level hierarchical location model for optimizing the placement of earthquake shelters by taking into account this temporal variance. The article not only scrutinizes the modeling procedure but also implements the model in a planning area with many real-world details. Based on the optimization results derived from a GIS context, we have found that the quality of the earthquake response procedure is not only dependent on the placement strategy of shelters, but more importantly on the financial constraints imposed on the planning and construction of these shelters. A discussion has been proposed to balance the trade-off between budget planning and evacuation efficiency. As the first attempt to model the hierarchical configuration of emergency shelters with specific focus on evacuees' escalating sheltering demands, this article will be of great significance in helping policy makers consider both the spatial and financial aspects of the strategic placement of emergency shelters.