Regulatory oversight of toxic emissions from industrial plants and understanding about these emissions' impacts are in their infancy. Applying a research design based on the openings and closings of 1,600 industrial plants to rich data on housing markets and infant health, we find that: toxic air emissions affect air quality only within 1 mile of the plant; plant openings lead to 11 percent declines in housing values within 0.5 mile or a loss of about $4.25 million for these households; and a plant's operation is associated with a roughly 3 percent increase in the probability of low birthweight within 1 mile.

This study estimates the economic value of externalities related to waste transfer stations in Israel. Most externalities are associated with local disamenities experienced by residents living in close proximity to transfer stations - including noise, odor, litter, vermin, visual intrusion and any associated perceived discomfort. Following the mapping of all active transfer stations in Israel, problematic sites near residential areas were identified. Four of these sites were selected for detailed examination. The study involved estimating the economic value of disamenities using the Hedonic Price Method, which examines the impact of disamenities on property values. The results indicate that the maximum spatial extent of the impact occurs about 2.8km away from a transfer station with an increase of about $5000 in housing price for each additionalkm away from the site. Alternatively, an increase of 1% in the average distance of a house from the local transfer station is associated with a 0.06% rise in the price of the average house. These figures, representing the relationship between changes in environmental quality and property prices, indicate that transfer stations create externalities that should be taken into account in location and clean-up policies for transfer stations as well as in potential compensation policies.

近年来,随着城市扩张,垃圾处理设施的布局逐步和城市居住空间相交叠,影响居民生活品质。目前人们对于北京市垃圾处理设施“围城”问题的认知多来自新闻媒体的宣传报道,存在一定的认知误差。以北京市六环内及周边街道为研究范围,分析垃圾处理及转运设施对房价的影响程度,以及垃圾处理设施对周边住宅价格影响的空间范围,在此基础上分析北京市最大的垃圾处理中心——阿苏卫对周边房价的影响范围。结果表明：① 北京市大型垃圾处理设施对周边房价影响的空间作用范围平均为6 km左右,这一距离远超市政建设要求的大型垃圾处理设施与居住区距离500 m的邻避标准。以此空间距离为基准测算,北京有800多个社区、约70万户居民处于大型垃圾处理设施的影响范围内。② 案例研究显示,阿苏卫垃圾处理中心对周边房价的影响范围接近14 km,远大于垃圾处理设施的平均空间作用距离。由于阿苏卫周边分布着回龙观、天通苑等大型居住区,受该设施影响的居民多达几十万人。

In recent years, with the expansion of cities, the distribution range of garbage disposal stations has gradually overlapped with urban living spaces, and affected the quality of residents' lives. In the past, people's perception of the problem of garbage sewers in Beijing came only from sensory impressions. In fact, garbage disposal sites and facilities only accounted for a small part of the “encirclement of the city”, but the scope of its impact on the living space is relatively large. The specific impact degree and scope need to be analyzed quantitatively to reach an objective conclusion. Taking the streets within the Sixth Ring Road of Beijing as the research scope, this paper analyzes the impact of waste treatment and transfer facilities on the housing price, as well as the spatial scope of the impact of waste treatment facilities on surrounding housing prices. On this basis, the impact range of Asuwei waste treatment center on the surrounding housing prices is analyzed. The results show that: (1) on average, large-scale waste treatment facilities in Beijing will affect the price of residential buildings within a distance of 6 km. This result is consistent with the previous results derived by scholars. There are 810 residential areas and nearly 700 thousand households in the affected area. (2) The impact of Asuwei waste treatment center on the surrounding housing prices reaches 14 km, which is far beyond the average impact range of waste treatment facilities and the protection distance specified in the construction standards.

城市发展过程中,大型公共基础设施的建设运营与居民居住空间品质的优化提升之间的矛盾日益突出。随着城市更新的不断深入,实现规划用地高效合理利用与人民生活宜居和谐的双赢目标成为城市规划建设的重中之重。由于机场设施存在较为明显的负向外部性,其邻避效应对周围住宅价格产生影响。本研究对首都国际机场运用特征价格模型分析“同邻避设施的距离”对住宅价格的影响,表征了在不同要素影响下邻避设施空间效应的量度,同时分析得出其对住宅价格的影响范围半径。主要研究结论如下：① 首都机场设施对周边住宅价格存在负面影响。在一定范围内,到机场设施的距离每减少1%,住宅价格平均降低0.586%。不同要素的影响力也存在差异。② 机场设施对住宅价格的空间影响范围为10 km,其空间效应随“同机场风险源距离”的增加而表现出减弱的趋势。此外,影响范围内的小区有149个,83.2%的小区分布在顺义区,受影响的户数约为13万。③ 机场设施的邻避效应空间影响存在方向异性,位于机场西部和南部的区域对周边住宅价格的影响范围整体大于位于机场北部和东部的区域。

In the process of urban development, the contradiction between the construction and operation of large-scale public infrastructure and the optimization and improvement of residential space quality has become increasingly prominent. With the continuous urban renewal, it has become the top priority of urban planning and construction to realize the win-win goal of efficient and rational use of planned land and livable and harmonious life of the people. The Beijing Capital International Airport has negative effects on surrounding residents due to its electromagnetic radiation, noise and solid pollution. As a result, it has been subject to constant complaints from residents and long-term petitions for decision. Due to the obvious negative externalities of airport facilities, its NIMBY (Not In My Backyard) has an impact on the prices of surrounding houses. This research uses the Hedonic Price Model (HPM) to analyze the impact of "distance from NIMBY facilities "on the housing price of Beijing Capital International Airport, characterizes the measurement of the spatial effects of NIMBY facilities under the influence of different factors, and analyzes the range of influence on residential prices of Beijing Capital International Airport radius. The main research conclusions are as follows: (1) The capital airport facilities have a negative impact on the price of surrounding houses. Within a certain range, for every 1% decrease in the distance to airport facilities, the price of residential houses will decrease by 0.586% on average. The influence of different factors is also different. Among them, the noise level also has a greater influence on the price of housing, with an influence coefficient of 2.145. The distance between the residence and the subway station and bus station also has a greater impact on its own price. (2) The spatial impact of airport facilities on residential prices is 10 km, and its spatial effects show a weakening trend as the "distance from the airport risk source" increases. In addition, there are 149 communities within the affected area, 83.2% of which are located in Shunyi District, and the number of affected households is approximately 130,000. (3) The spatial influence of airport facilities on NIMBY effect has different directions. The areas located to the west and south of the airport have an overall greater impact on surrounding residential prices than the areas located to the north and east of the airport.

以广州都市区1 361个社区的第六次人口普查住房数据为基础,从住房的建成年代、建筑结构、户均建筑面积、住房生活设施4个方面构建居民住房条件评价体系,分析其空间分异格局与形成机制。结果表明：① 广州市居民住房条件由中心向外围逐渐提升,具有“圈层基础上的多核心”式空间分异结构;② 户均建筑面积和建成年代是决定其住房条件差异的2项重要指标,旧城的住房条件异质性最高;③ 城市发展的历史进程、互换效应和过滤效应、高房价和高地价影响和强化了住房条件分异格局,制度性因素、政府决策和市场力量同时起到了引导和推动作用。

The housing issues of China’s urban residents have always been the focus of academic circles. The issues regarding housing conditions in China's megalopolises are important topics of research for building livable cities, resolving the housing shortage, and solving the urban problem. The inequality of urban housing conditions is also an indispensable issue. However, to date, specific research on the differentiation pattern and spatial structure of housing conditions in China's cities is rare. Therefore, based on housing data from the newly available sixth census of 2010 for Guangzhou’s metropolitan areas, we established a comprehensive system for evaluating housing conditions that is composed of housing years, building structure, building area per household, and housing facilities and explored the spatial differentiation pattern of housing conditions. Furthermore, we analyzed the spatial cluster and heterogeneity of housing conditions by using the ESDA and GDI index. Finally, we summarized the spatial differentiation model and formation mechanism. The results are as follows: 1) The housing conditions of Guangzhou, gradually improving from the center to periphery, show significant imbalance and spatial cluster characteristics. Regions with better and worse housing conditions have specific location directions. Housing years and building area per household are two core indicators that decide the differentiation of housing conditions. 2) The housing conditions of the evaluation subsystem are distinct among different urban circles. In the old city, the scores of housing years, architectural structure, and building area per household are lower. In the core area, scores of the building area per household and housing infrastructure are higher than in other regions. In the central area, the level of the architectural structure is highest. In the suburbs, the housing years are the lowest. In addition, the heterogeneity of housing conditions in the old city is the highest. 3) The historical process of urban development, housing exchange and filtering effects, and high housing and land prices influence and enhance the spatial differentiation pattern of housing conditions in Guangzhou. Institutional factors, government decision making, and market forces also play a role in guiding and promoting the pattern. Thereto, institutional factors include the urban-rural dual-land system, housing dual-supply system, and housing demolition requisition system. Government decision making mainly refers to the urban development strategy and urban planning. Market forces reflect relationships between housing price, housing conditions, location, and household income.

研究房价、遥感影像等多源数据,采用邻域分析法和地理加权回归模型分析大连市中山区绿地可达性及其与房价之间的空间相关性。结果表明：① 房价均价14 745.35元/m²,呈环状分布,由沿海向内陆衰减、桂林街道起中心向外围递减;② 研究区内可达性最好的绿地类型是街旁绿地,绿地可达性总体水平最高街道是桂林街道;公园绿地可达性最好的住宅区分布在昆明街道和桃源街道,街旁绿地可达性最好的住宅区分布在桂林街道,附属绿地可达性最好的分布在老虎滩街道,其他绿地可达性最好的分布在桃源街道。③ 不同类型绿地可达性对房价影响作用程度递减排序为：附属绿地、街旁绿地、公园绿地和其他绿地;附属绿地、街旁绿地和其他绿地与房价呈现空间正相关,随着到达绿地距离降低,房价呈现增长趋势;公园绿地与房价呈现负相关,随着到达公园绿地的距离降低,房价呈现衰减趋势。

This article studies the relationship between urban green space accessibility and house prices in Zhongshan District, Dalian, by near analysis, geographically weighted regression model and multi-source data (e.g., house prices and green space). The results are as follows: First, the average house price is 14 745.35 yuan/m2, and reveals a declining trend from coastal areas to inland areas, except Guilin Street, which demonstrates a local peak of house prices that decreases from the center of the street to its periphery. Second, street park green spaces show the best accessibility, and the overall accessibility of the green space for Guilin Street is the highest; The residential areas of best theme park green space accessibility are located on the Kunming streets and the Taoyuan streets; The residential areas of best street park green space accessibility are located on the Guilin Street; The best accessibility of attached green space is distributed on the Tiger Beach streets; With the best accessibility of other green space distributed on the Taoyuan streets. Third, the influence of green land accessibility on housing prices decreases with green land types as attached green space, street park green space, theme park green space, and other green space; Attached green space, street park green space and other green space show the significant spatial correlation coefficient between green space accessibility and house prices, house prices show a trend of growth as the distance to the green land falls; There is negative correlation between theme park green space and house price, with the arrival of scenic parks green spaces decreased, house prices showed the decrease trend.

选取上海市区7家三级甲等综合性医院,运用特征价格模型和多元回归分析方法,实证分析它们对周边住宅价格的空间影响效应。研究结果显示：① 总体上,相比其他环境区位因素,三甲医院对周边住宅价格的影响程度较小,而建筑面积、物业管理费、学区房、轨道交通、建筑楼高、至 CBD 的距离等因素的影响程度较大。② 三甲综合医院对周边住宅价格产生负面影响。在相同情况下,住宅离医院距离越近,则价格越低。住宅与医院的距离每缩短50 m,住宅价格平均下浮0.602%。③ 由于三甲综合医院区位各不相同,距离CBD远近不一,对住宅价格的影响也存在空间差异。一般来说,距离CBD越近,住宅价格受医院的负面影响也越小。

How to evaluate the impacts of urban public resources and facilities on the price of real estates has been the research topic in academic circles for a long time. Relative to the other urban public facilities such as subway stations or rail transit, large-scale parks and greenbelt, landscape water, universities or key primary and middle schools and so on, the relationship between hospital and housing prices has not caused enough attention. In this article 7 Class 3A comprehensive hospitals in Shanghai urban central areas were selected, using the Hedonic price model and multiple regression analysis method, to conduct an empirical analysis of the spatial effect of these hospitals on residential property prices. The results show as follows: 1) Generally speaking, compared to other environmental factors, the less impacts of Class 3A comprehensive hospitals were corducted on the surrounding residential property prices, and the factors such as building area, property management fees, school-nearby houses, rail transit, height of buildings, the distance to the CBD have greater influence on housing prices. 2) Class 3A comprehensive hospitals have a negative impact on the surrounding residential property prices. And in the same circumstances, as shortening the distance of houses to the hospital each 50 m, the average housing price fell 0.602%. 3) Because of the different location and distance to the CBD of Class 3A comprehensive hospitals, there is a spatial differencine in their impact on housing prices. In general, the closer distance to CBD is, the less negative influence housing price is affected by the hospital.

城市住宅价格空间分异,是居住空间资源非均衡配置的市场化表达,映射出不同阶层社会群体对城市住宅的选择倾向与需求差异,与居住空间分异在机制和格局上存在一定耦合关联。以南京主城区商品房社区为研究对象,构建起住宅价格特征变量指标体系,采用地理加权回归模型,分析导致房价空间差异的主要因素、组合关系及时空演变特征。研究发现：社区服务档次、学区资源、环境区位、景观稀缺等能够体现居住群体经济实力、生活方式与文化品位的因素,是影响房价分异的主导要素并随时间不断强化;南京房价总体上呈现“圈层+扇形+飞地”的空间结构,高房价主要分布在城市中心、名校学区、高档封闭社区和山水景观别墅区;房价分异与居住分异在作用机制和空间格局上表现出显著的关联耦合特征。城市房价空间分异不止于表达,同时也是推动居住空间分异与再分化的重要驱动机制,并能够预判未来一段时期内城市居住空间分异格局演变的基本走势,可以为城市社会空间研究提供具有前瞻性的观察视角和分析工具。

Spatial differentiation of urban housing prices is the marketization expression of the non-equilibrium allocation of residential space resources, which reflects the contrast between social groups belonging to different social classes in selection preference and demand for housing. There is a certain degree of correlational coupling between urban housing prices' spatial differentiation and residential spatial differentiation with respect to the mechanism and the pattern. The paper chooses 1204 commercial housing communities in Nanjing's urban center as its research object and constructs a characteristic variable index system of housing prices. The GWR model is used to analyze major factors that lead to spatial differentiation in housing prices, as well as their combination relationship and spatial-temporal dynamics. Results demonstrate that: (1) there are various factors affecting housing prices, their subsequent spatial differentiation, and they are likely to evolve over time. The dominant factors are the level of the community, school district resources, quality of the landscape, access to leisure facilities, and so on. These may mainly reflect housing consumers' earning capacity, values, residential environment demands, life style and cultural tastes. (2) The pattern of housing prices in Nanjing generally shows the spatial pattern of "circle + fan-shaped + enclave". High priced housing mainly includes new apartments and gated communities in the inner city, communities in elite primary and secondary school districts, high-grade gated communities close to the Ming City Wall, housing in the center of Hexi New Town, and landscaped villas in the urban periphery. (3) Differing types and strata of housing communities attract and gather consumer groups with specific economic and social attributes, which makes housing price differentiation notable correlational coupling with residential differentiation in acting mechanisms and spatial patterns. As the degree of urban housing marketization is continuously deepening and the cultural characteristics and residential preference of social classes become increasingly mature, the spatial differentiation of urban housing prices is more than just an expression. It is also an important driving mechanism to promote residential spatial differentiation and re-differentiation, and can also predict basic trends pertaining to urban residential spatial differentiation in the future. Therefore, the spatial differentiation of urban housing prices can provide a prospective observational and analytical tool for the study of urban social space. It can further make up the time-lag defect which arises in traditional social space research using census data, as well as helps to predict and identify future trends regarding urban social spatial differentiation.

2014、2015年教育部接连发文要求落实“免试就近入学”政策,由此公立初小的入学资格与住房紧密挂钩。在此背景下,初小教育资源如何影响住宅价格,并带来怎样的城市社会空间变化是有意义的科学问题。论文基于安居客、链家、百度开放平台及问卷访谈等数据,综合运用特征价格模型、地理加权回归模型等方法,以武汉市武昌区为实证区域,探索学区对住宅价格的真实影响,并尝试从“空间生产”入手,探究学区引发的城市社会空间重构。研究发现：① 学区特征对住宅价格的影响已超过传统区位、建筑、邻里特征等的影响;② 学区房提供了资本由二级循环进入三级循环的便利路径,形成了学区空间生产与社会空间新分层的宏观基础;③ 微观层面,对优质学区的争夺产生了“学区人”和“学区空间”,进而出现学区飞地,对传统城市社会空间产生影响;④ 不同于“单位人”与“社区人”,“学区人”并不主要依靠职业或收入划分,而是因相似的家庭生命周期发生关联。

Since the Ministry of Education of China issued a series of documents requiring the implementation of the policy of nearby enrollment without entrance exam in 2014 and 2015, the enrollment qualifications of public primary and secondary schools have been linked to housing property. In this context, it is of significant value to explore how the primary and secondary school education resources affect housing prices and how the resulting urban socio-spatial restructuring takes place. Based on the data from open platforms of Anjuke, Lianjia, and Baidu and survey questionnaire and interview data, this study took Wuchang District of Wuhan City as the case area to explore the real influence of school districts on housing prices through adopting the hedonic price model, geographically weighted regression (GWR) model, and other technical methods. Moreover, starting with the concept of "production of space", this study explored the effect of school districts on urban socio-spatial restructuring. The results show that: 1) The impact of the characteristics of school districts on housing prices has exceeded the traditional housing characteristics, such as location, architecture, and neighborhood. 2) Housing within the high school district provides a convenient path for capital inflow from secondary to tertiary circuits, forming a macro basis for the production of school districts as well as a new stratification of social space. 3) At the micro scale, the competition for high-quality school districts has produced "people of school districts" and "space of school districts", and then enclaves of school districts have emerged, which has an impact on the traditional urban social space. 4) Unlike the "danwei (workplace) people" and "community people", the definition of "people of school districts" does not mainly rely on occupational or income divisions, but is associated with families of similar life cycles.

为探索不同空间插值方法得到的DEM如何影响土壤侵蚀模拟效果,本文选择金沙江干热河谷区典型冲沟为研究对象,利用野外测量高程数据,采用反距离加权(IDW)、析取克里格(DK)、局部多项式(LPI)和张力样条函数(ST)4种方法构建高精度DEM。基于USPED模型模拟冲沟的土壤侵蚀,对比不同空间插值方法的精度、土壤侵蚀的空间分布,采用相对差系数对比不同插值在土壤侵蚀研究中的相似性。结果表明：DEM空间插值的精度排序为ST

Digital elevation models (DEMs) have been widely used in soil erosion simulation, but how different interpolation methods affect the simulation results is not well researched. In this article, a typical gully in the dry-hot valley of the Jinsha River was selected as the case study area. First, field measurement of elevations of the gully was preformed. Inverse Distance Weighted (IDW), Disjunctive Kriging (DK), Spline with Tension (ST), and Local Polynomial Interpolation (LPI) methods were then used to produce high-precision DEMs of the gully. The United Stream Power-based Erosion Deposition (USPED) model was used to simulate the spatial distribution of erosion and deposition in the gully. The coefficient of relative difference was used to analyze the similarity of USPED results. The result shows that the precision of DEMs from high to low is: DK, LPI, IDW, and ST. The results of USPED simulation show that DK revealed the main distribution pattern of erosion and deposition, but IDW highlighted the details, and LPI and ST were in-between. The coefficient of relative difference shows that IDW was similar with other interpolation methods in soil erosion simulation, but when the layout of sampling points is reasonable and the density of the sampling points is sufficiently high, IDW is more suitable for soil erosion simulation using USPED.

重点镇是小城镇发展的龙头,形成科学合理的重点镇布局对优化中国城市化战略格局有重要意义。论文以2004年和2014年分别公布的1887个和3675个全国重点镇为样本,对其分布及效应的变动特征进行探究,进而在地级尺度对重点镇布局的影响因子及其作用进行地理探测和局部空间回归。结果表明：① 经增补调整,中国重点镇布局及建设效应的均衡性增强,主要集聚区西移北扩,冷热点的分布突破“胡焕庸线”,经济辐射效应的分化程度减弱,体现出政策因素的有力影响。除县际均衡和区域倾斜政策外,重点镇的分布还受到海拔高度、公路网密度、常住人口城镇化率等因子的显著作用。② 因子探测器、GWR模型和交互作用探测器的结合能更精准地刻画影响因子的作用方式、方向、路径和强度。中国重点镇的布局不是5个显著性因子均匀、独立、直接作用的结果,而是影响均具空间异质性的各因子两两交互作用后增效的产物。③ 县际均衡政策与其他因子的协同作用是形成现有重点镇分布格局的主导力量;区域倾斜政策的效果总体较好,但目标区域还需更准确。

National key towns are the leader in the development of small towns. The formation of scientific and reasonable national key town layouts is of great significance for optimizing China's urbanization strategy. Taking the 1887 and 3675 national key towns published in 2004 and 2014 respectively as samples, this study used geodector and the geographically weighted regression (GWR) model to explore the changing characteristics of their distribution and analyze the influencing factors of national key town layouts and effects at the prefecture level. The results show that: 1) After the adjustment by the government, the balance of the layout and construction effect of national key towns is enhanced. The main gathering areas moved westward and northward, the distribution of cold spots and hotspots break through the "Hu Huanyong Line", and the degree of differentiation of economic radiation effect is weakened, reflecting the powerful influence of policy factors. In addition to the inter-county balance and regional preferential policies, the distribution of national key towns is also significantly affected by factors such as altitude, road network density, and resident population urbanization rate. 2) The combination of the factor detector, the GWR model, and the interaction detector can more accurately characterize the mode of action, direction, path, and intensity of the influencing factors. The layout of national key towns is not the result of the uniform, independent, and direct effect of the five significant factors, but the product of the synergistic effect of the interaction of the factors with spatial heterogeneity. 3) The synergy between the inter-county balance policy and other factors is the dominant force in the formation of the existing layout of the key towns; the effect of the regional preferential policy is overall positive, but the target areas need to be more accurately identified.

中国城市房价快速增长背景下,城市房价、收入与房价收入比空间格局既有相似性,也表现出差异性,其空间异质性与空间依赖性特征显著。本文以中国337个地级行政单元为研究对象,运用泰尔指数、位序-规模和空间马尔科夫链等方法,对2009—2018年中国城市房价、收入和房价收入比的时空分异格局、整体稳定性和空间依赖性特征进行分析发现：① 中国城市房价增长呈现出波动性特征,整体分异程度增强,房价城市体系呈现“金字塔型”结构,收入则表现出平稳增长态势,整体分异度降低,城市体系呈现“橄榄型”结构,在房价与收入共同影响下,房价收入比整体差异性显著加强;② 城市房价空间格局表现出“地带性”与“等级性”差异并存,而收入更多表现出“地带性”差异,房价收入比则以“等级性”差异为主;③ 城市房价和收入类型的稳定性和空间依赖性较强,高、低水平城市存在两极分化与“俱乐部收敛”现象,房价收入比稳定性相对较弱。对中国城市房价、收入和房价收入比时空分异格局和空间关联效应的分析,可以为探索中国城市房价收入比空间分异模式与机理提供必要研究基础。

Amid the fast-growing housing price in Chinese cities, the spatial pattern of urban housing price, income and housing price-to-income ratio shows both similarities and differences, characterized by internal spatial heterogeneity and spatial dependence. This paper targets 337 prefecture-level administrative units and applies the Theil index, rank-size and spatial Markov chain to the analysis of the spatiotemporal differentiation pattern, overall stability and spatial dependence of Chinese urban housing price, income and housing price-to-income ratio from 2009 to 2018. It finds the following results. Firstly, the growth of Chinese urban housing price is phase-based and fluctuated. When the overall differentiation enlarges, the urban system of housing price takes on a structure of “pyramid” and income shows sustained and stable growth. When the overall differentiation shrinks, the urban system presents a structure of “olive”. Under the combined influence of housing price and income, the overall differentiation of housing price-to-income ratio is obviously strengthened. Secondly, housing prices, income and housing price-to-income ratios in Chinese cities are all spatially heterogeneous and agglomerated. The spatial pattern of housing price is different in both zonality and hierarchy, while income is particularly different in zonality and housing price-to-income ratio is particularly different in hierarchy. Due to the coexistence of similarities and differences between housing prices and income patterns in Chinese cities, the housing price-to-income ratio pattern presents a more complex and discrete structure. Thirdly, the stability and spatial dependence of urban housing price and the type of income is stronger, while the stability of housing price-to-income ratio is relatively weak as there are polarization and club convergence in cities at different levels. Housing prices to the north of the "Hu Huanyong Line" shifted downwards, income shifted upwards, and the housing price-to-income ratio declined. In the southern regions, housing prices generally rose rapidly, with income shifts showing stable in the east, downwards in the central region, and upwards in the west, leading to the discrete and broken pattern of housing price-to-income ratios. Moreover, the type shifts of urban housing price, income and housing price-to-income ratio are not spatially independent, but related to the neighboring cities. The analysis of the spatiotemporal differentiation pattern and spatial correlation effect of Chinese urban housing price, income, and housing price-to-income ratio lays a foundation for research on the spatial differentiation pattern and mechanism of Chinese urban housing price-to-income ratio.

旅游生态效率评估及空间格局研究是揭示中国省域旅游业发展质量与态势的重要基础。论文以“自下而上”法核算中国省域旅游能源消耗与碳排放为基础,综合运用考虑非期望产出的Super-SBM模型、Malmquist指数及探索性空间数据分析等方法,探究节能减排约束下2000—2017年中国省域旅游生态效率及其空间分异、收敛和关联格局。结果表明：① 旅游能源消耗与碳排放总体呈先增长、后下降的倒“U”形演化趋势,支持环境库兹涅茨曲线(EKC)假说;② 旅游生态效率总体呈波动增长趋势,并有较大增长潜力,纯技术效率驱动生态效率优化发展;③ 旅游生态效率在省域、地区尺度上均呈现空间分异格局,但趋向收敛平衡发展;④ 旅游生态效率呈现由强到弱的正向空间关联格局,其发展模式以低—低集聚为主,低—高集聚次之,空间集聚模式待优化。各省区应以生态效率水平较高的地区为基准,通过要素流动、规模效应、技术进步及环境规制等手段,实现旅游业高质量协调发展。

The study on the evaluation and spatial pattern of tourism eco-efficiency is an important basis for revealing the quality and state of tourism development at the provincial level in China. Based on a bottom-up approach to calculate tourism energy consumption and carbon emissions at the provincial level in China, this study used the Super-SBM (slacks-based measure) model, Malmquist index, and exploratory spatial data analysis to explore the spatial differentiation, convergence, and correlation patterns of tourism eco-efficiency at the provincial level in China in the context of energy conservation and emission reduction. The results show that: 1) Tourism energy consumption and carbon emissions generally show an inverted U-shaped trend that first increases and then decreases, which supports the environmental Kuznets curve (EKC) hypothesis. 2) The overall tourism eco-efficiency shows a fluctuating growth trend, and has great growth potential. Pure technical efficiency drives the optimized development of eco-efficiency. 3) At the provincial and regional scales, tourism eco-efficiency presents a spatial differentiation pattern, but tends to convergence and reach balanced development. 4) Tourism eco-efficiency presents a positive spatial correlation pattern from strong to weak, and its development model is dominated by low-low agglomeration, followed by low-high agglomeration, and the spatial agglomeration model needs to be optimized. All provinces and regions should take the areas with higher eco-efficiency as the benchmark, and realize the coordinated development of tourism with high quality by means of factor flow, scale effect, technological progress, and environmental regulation.