Urban signs characterize the state of development and operation of a city, including construction conditions of built environment,driving force of urban economic and social development, operational status of facilities and urban activities of individuals in the city, etc. The diagnosis of urban signs equals to the health examination of urban development and operation, by which sticking points are recognized. A set of reliable and practical urban diagnostic indices is required not only to comprehensively reflect correlative sub urban systems that are static or dynamic, but also illustrate the status of urban system through quantitative methods and geo-visualization. Using traditional data and big data from different sources, this paper constructs a system of diagnostic index of urban signs based upon the integration of urban activity-travel system, urban population system, urban operation system, and urban environment system. The diagnostic index system is decomposed into 4 dimensions including fundamental force, driving force, pressure and vitality. The fundamental force index is used to describe basic attributes of land use and population; the driving force index reflects the state of development of spatial units through development of enterprises and quality of the environment; the pressure index is used to monitor the running status of the urban system, and as such, it plays a role in risk-evaluation and risk-warning; the vitality index reflects the real vitality of the spatial units by demonstrating the dynamic characteristics of the activity system and flows in time and space. 12 spatio-temporal scales are acquired through intersection of 4 levels of the spatial units（municipal Shanghai , district, Jiedao, census tract）and 3 levels of temporal scales（annual,daily and real time levels）. The index weight is determined by fuzzy hierarchy analysis. Taking April 6, 2016 as an example, we calculate both comprehensive and dimensional diagnostic index of urban signs of Jiedaos (subdistrict that is sub-divided into several residential communities or neighbourhoods) in Shanghai and elaborate on how the diagnostic index of urban signs corresponds to actual state and facilitates detection of urban problems. Results show that comprehensive diagnostic index varies slightly while considerable variations emerge in diagnostic index of each dimension. Fundamental force index, driving force index and vitality index decline gradually from inner city to suburbs. On the contrary, pressure index increases from inner city to suburbs. Through visual and real-time analysis and evaluation, the diagnostic index of urban signs has huge potential for implementation in urban grid management, pressure warning and other needs of urban governance.
In developed and developing countries alike, scholars have endeavored to theorize and test the impacts of urban spatial restructuring—from city-scale suburbanization to neighborhood-scale land use change—on individual commuting and daily travel behaviour. This article tried to provide empirical evidences of residential mobility and home-work links of the moderate to low-income urban residents in Beijing. Based on a 492 household surveys of nine typical neighborhoods which were mainly located in the traditional city centre as well as suburban districts, we compared home-work links and commuting pattern among different moderate to low-income groups, using the measurement of home-work distance and commuting time. Specifically, we used regression models to examine the impacts of institutional factors (such as access to housing, affordable housing policy, different types of work units, HUKOU, home ownership, gender etc.) on low-income residents' job accessibility. The results firstly showed that those who worked for state-owned enterprises (SOE) and these who worked for other non-SOE enterprises, compared to these worked in administrative institution and public sectors, experienced significantly longer home-work separation, which reflected the legacy of DANWEI. Secondly, as to the residential move opportunity, these who were relocated by the governmental housing program tend to endure greatest home-work separation while these who moved by personal reasons had shorter home-work distance. As we expected, those who lived in the suburban neighborhoods had significant worse job accessibility than their counterparts lived in inner city. Thirdly, these who had Beijing HUKOU, who were not household head, male commuters had longer home-work distance. Besides, we found that there was a significant positive correlation between personal monthly salary and home-work distance, which suggested that the job market began to play an important role. Finally, we pointed out special attentions should be paid to the spatial implications of low-income residents’ job accessibility and employment outcomes after passive relocation of their homes as well as their work units.
利用2016年在广州典型大型零售商业中心进行的客流量监测和居民消费行为问卷数据,分析基于客流时间变化的广州大型零售商业中心消费活动时变模式,构建多项Logistic回归模型,从消费者社会经济属性、消费活动特征和商业中心建成环境3方面探讨该时变模式的影响因素。结果显示：① 广州不同的大型零售商业中心内消费活动存在明显的时变特征差异,可分成稳定型、下午高峰型、傍晚高峰型和不规则波动型4类时变模式;② 这种时变模式受到消费者社会经济属性、消费活动特征和商业建成环境等变量的影响。其中,消费者社会经济属性和消费活动特征影响有限且影响差异较大,以稳定型为参照组,在广州居住时间、居住区位和家庭月收入等社会经济属性,以及消费结构、出行路径、交通方式和出行距离等消费活动特征能区分稳定型和下午高峰型商业中心,但只有在广州居住时间和出行距离、交通方式3个变量能显著地解释稳定型和傍晚高峰型商业中心的差异;建成环境是影响零售商业中心时变模式的首要因素,商业网点密度、用地混合度、公交与地铁站点密度、商业中心区位特征、到市中心距离等变量均对各个类型商业中心的形成作用显著。期望为城市零售商业中心的分类和评价提供一个新思路,为预测商业中心可能的消费活动时变模式、消费者属性和活动特征提供理论依据,对城市商业规划和商业中心开发运营有一定的现实指导意义。
Paying more attention to the space dimension, the studies on retailing center hierarchy seldom consider the temporal characteristics and patterns of consuming activities in retailing centers, and fail to reveal the influencing mechanism of temporal diversities of consuming activity and its impact on retailing centers deeply. Based on a survey data collected in 39 large retailing centers in Guangzhou and a multiple logistic regression model, this article attempts to explore the temporal patterns of consuming activity in different retail centers and their influencing factors. The results are shown as follows: 1) The time-varying characteristics of consuming activities in different large retail centers are different obviously, and the retailing centers can be divided into four patterns, such as ‘stable’,‘peak in the afternoon’, ‘peak in the evening’ and ‘irregular fluctuation’. 2) Both of the consumers’ social and economic attribute and the characteristics of consuming activities are limited and different effects on different patterns of retailing centers. In the one hand, living time, housing location, family monthly income, consuming structure, trip chain, mode of transportation and travel distance can distinguish the ‘stable’ retail center and the ‘peak in the afternoon’ retailing center. In the other hand, there are only three variables, such as living time, travel distance and mode of transportation, which can significantly explain differences between the ‘stable’ and the ‘peak in the evening’ retailing centers. Built environment is the primary factor forming the patterns of retailing centers. Density of commercial centers, mixed of land use, density of bus stations and subway stations, location and distance to downtown have significant effects on the formation of various patterns of retailing centers. This study provides a new way to classify and evaluate urban retailing centers, and the conclusions can be regarded as the theoretical basis to predict the potential consuming activities time-varying model, consumer attributes and activity characteristics. Last but not least, the conclusions of this article give advice to urban commercial planning and development of commercial center.
休闲行为的产生条件一直受到国内外地理学者的重视,邻里建成环境作为结构性制约因素,在休闲行为研究的交叉学科中开始受到重视,但是关注其对休闲行为影响的时间差异的研究严重不足;此外相关研究多从是否产生休闲行为或活动量的角度去验证,缺乏建成环境对休闲空间特征影响的衡量。基于时间地理学理论,以广州市为案例地,结合居民的出行活动日志调查与人口普查数据、土地利用数据、建筑POI普查数据,探讨居民休闲行为时空特征及居住地的邻里建成环境对其产生的影响。研究发现：工作日,居民外出型休闲活动时间呈现出高度集中特征,高度集中于12:00~14:00,活动集聚的时空区域是12:00~14:00、4 km内;休息日,居民外出型休闲活动时间集聚的集中性减弱,活动持续时间增长;活动集聚的时空区域是9:00~20:00、1 km内。邻里建成环境的不同维度指标对休闲活动距离的作用时段与影响程度存在差异。工作日上午并无影响显著的因素;中午,休闲距离主要受到道路交叉口数量和商业中心可达性的负向影响;下午,休闲距离受到道路交叉口数量先负向后正向的影响。休息日上午,休闲距离主要受开敞空间用地比例的负向影响;中午,受开敞空间用地比例、公交站点数和到最近开敞空间距离的负向影响,土地利用混合度则是呈现先正向后负向的影响;下午,受道路交叉口数量和公交站点数的负向影响、休闲设施数量的正向影响。从作用机制来看,休息日是休闲机会和时间成本作用占主导,工作日是休闲环境作用占主导。
The conditions of leisure activity has been payed much attention to by geographers.Neighborhood built environment, as a structural restriction factor, has been paid attention to in the interdisciplinary study of leisure behavior. However, there is still little study to consider the time difference of the influence of the built environment on leisure behavior. Most researchers believe that the built environment has an impact on leisure behavior, and the related researches are mostly from the perspective of whether there are leisure activities, and lack of measure of the spatial dimension of leisure behavior. Based on the theory of time geography, this paper takes Guangzhou as an example and use residents’ activity dairy, census data, land use data and building POI(position of interests) data to explore the spatial-temporal characteristics of residents' out-of-home leisure behavior and the neighborhood built environment impact.We find that on weekdays, the out-of-home leisure time of residents showed a high degree of agglomeration. The space-time areas highly concentrated are from 12:00 to 14:00 within 4 km. On weekend, the degree of time agglomeration is weakened, but duration of the activity is increased. The space-time area highly concentrated is from 9:00 to 20:00 within 1 km. Residents' leisure activities are constrained by factors such as the neighborhood built environment, the time length of the leisure activity, the distance from the workplace, and so on. These effects are higher in the weekdays than in the weekends. The constraints are higher in the morning and at noon than in the afternoon on weekdays. On weekends, the constraints are high in the morning and low at noon. There are differences in the time and the degree of influence of the different dimensions of the neighborhood built environment on out-of-home leisure activity distance. On weekday: There is no significant factor of the built environment in the morning. The leisure distance is mainly affected by the negative impact of the number of road intersections and the accessibility of the commercial centers at noon. In the afternoon, leisure distance is affected by the number of road intersections, and at first it is positive effect and then negative effect. On weekend: In the morning, the leisure distance is mainly affected by the negative impact of the proportion of the land use of the open space. At noon, it is affected by the positive effect of the land use ratio of the open space, and negative effect of the number of bus stations and the distance to the nearest open space. The land mix index has a positive and then negative effect. In the afternoon, the leisure distance is affected by the negative impact of the number of road intersections and the positive impact of number of bus stations.From the point of view of the mechanism, residents are restricted mainly by the neighborhood built environment on weekends, while the work place mainly on weekdays. The opportunity for leisure and time costs are dominant roles on weekends, while the recreational environment is the dominant role on weekdays.
Given that long commuting duration is considered as a crucial problem of urban transportation, urban planners and geographers explored the impacts of built environment on commuting duration in order to reduce long commuting duration and alleviate traffic congestion. However, the findings on the connection between population density and individual commuting duration are inconsistent. Some literature showed that population density and individual commuting duration have a negative correlation, while others found a positive correlation or an insignificant relationship. Secondly, previous literature on individual commuting duration paid little attention to the conditional effects of population density. Just as Jane Jacobs remarked at The Death and Life of Great American Cities, “No concentration of residents, however high it may be, is ‘sufficient’ if diversity is suppressed or thwarted by other insufficiencies”, the impact of population density on commuting duration may depend on the other built environmental attributes. Furthermore, previous studies focused mainly on the cases in developed countries and far less on developing countries especially China whose urban built environment is characterized by larger population size and higher density. Based on a sample of 1 605 individuals from the “the Yangtze River Delta Social Transformation Survey (FYRST)” Project in Shanghai in 2013, this study examines the impacts and conditional effects of population density at the sub-district spatial level on individual commuting duration by using hierarchical models. Controlling individual socioeconomic attributes, commuting modes, and other built environmental attributes including diversity, design, accessibility to transit and distance to the job center, the random intercept model estimations show that individual commuting duration is positively associated with population density at the sub-district spatial level. One possible reason is the traffic congestion resulting from extremely high density and the job-housing imbalance. Moreover, this effect of population density on commuting duration is conditional on the “design”, the “accessibility to metro”, the “distance to the job center”, and the “commuting mode”. Specifically, higher road network density and highway density, shorter distance to the job center, higher metro stations density, and encouraging commuting by metro instead of driving could diminish the duration increasing effect of population density. But the expected conditional effect of “diversity” is not significant and not supported by this article. Thus, it is feasible to reduce commuting duration and traffic congestion by optimizing built environment and adjusting population density. Firstly, it’s necessary to point out that the advocated concept of compact development should orient at reasonable high density instead of over-concentration. Secondly, planners should pay more attention to encouraging job-housing balance, including both quantitative and structural balance. Last but not least, it is important to expand the underground space to encourage commuting by metro and to construct the highway to shunt the traffic flow for the sake of shortening commuting duration and improving traffic efficiency.
Urban agglomeration, Development zone and Industrial cluster are the most dynamic economic geography phenomenon and process in rapidly rising China, and the hot topics and frontiers of economic geography and other related disciplines. Under the background of the acceleration of the city regionalization, the regional urbanization and the integration of regional development, the relation among urban agglomeration, development zone and industrial cluster is becoming much closer. It is necessary to make joint research to reveal the complex relationship among them on a deeper level. This article analyses the overall train of thought, research content and method of interaction on urban agglomeration-development zone-industrial cluster. It finds that the urban agglomeration-development zone-industrial cluster is the complex network system with mutual coupling and the study of which should follow the analytical framework of analyzing the interactive factors, identifying the interactive mode, revealing the interactive mechanism, measuring the interactive intensity and coordination degree, exploring the interactive mode and designing integrated development path, with the method of multiple-discipline comprehensive research, Big Data analysis, GIS spatial analysis, modeling of multi-agent systems and cellular automaton, etc.
构建教育城镇化水平测度方法,利用变化弹性系数、变异系数、多元回归模型分析了1987~2014年中国省际教育城镇化的时空特征及影响因素。研究表明：① 教育城镇化水平稳步上升,整体呈现“快-慢-快”的时序变化特征。② 教育城镇化变化弹性系数波动显著,教育城镇化提升速度整体高于人口城镇化。③ 教育城镇化水平区域差异明显,省际教育城镇化差异度逐渐减小,省际均衡性明显提升。④ 人口城镇化水平、城乡发展差距、城乡教育制度二元化3个主要影响因素的时空变迁及其叠加作用的变迁共同推动了中国教育城镇化时空格局演变。
This article analyzes the temporal and spatial characteristics of urbanization and the influencing factors of urbanization in China in 1987-2014, using the variation elasticity coefficient, coefficient of variation and multiple regression model. The results show that: 1) the level of urbanization of education has steadily increased, and the whole shows the characteristics of “fast-slow-fast”. In 1987-2014, China’s educational urbanization rate is divided into four stages: the low-level rapid growth period in 1987-1993, the slow rise period in 1994-2004, the steady increase period in 2005-2010, and the high-speed high-growth period in 2011-2014. 2) The change of elasticity coefficient of education urbanization fluctuates significantly, and the rate of urbanization is higher than that of population and urbanization. 3) The regional differences of educational urbanization are obvious, the degree of urbanization difference in provincial education is gradually reduced in 2000-2010 and 2010-2014, and the reduction rate was the fastest. The provincial balance is obviously improved. 4) The spatial and temporal changes of the three major influencing factors, such as the level of urbanization, the gap between urban and rural development, and the dualization of urban and rural education system. In terms of influential factors, institutional factors have a greater impact, followed by population factors, urban-rural economic gap factors, both of them have promoted the evolution of urbanization in China.
‘New Southward Policy’of Taiwan,China has been concerned widely since it was put out. Based on the perspective of foreign trade and the trade data from 2001 to 2015, after the analysis of economic dependence and international competitiveness, the paper analyzed the status of Mainland China in the trade network and its impact on Taiwan ,China through social network analysis, and discussed the influences on the economy of Taiwan, China according to the foreign trade date between ‘New Southward’ countries, Mainland China and Taiwan,China through the VAR impulse response function. The results show that: For the ‘New Southward’ nations, the degree of its economic dependence on Mainland China is much higher than that of Taiwan,China, and the trade status of Mainland China is far higher than that of Taiwan,China; for Taiwan,China, the degree of its economic dependence on Mainland China is significantly higher than that of the ‘New Southward’ countries, and the trade status of Mainland China is significantly higher than that of the ‘New Southward’ nations; for the ‘New Southward’ countries, the foreign trade status of Mainland China is irreplaceable by Taiwan,China. Meanwhile, for Taiwan,China, the foreign trade status of Mainland China is irreplaceable by the ‘New Southward’ nations; Mainland China is the central of the trade network pattern, which plays an important role in promoting Taiwan,China status in the trade network; the positive effect of foreign trade between Mainland China and Taiwan,China on the economic development of Taiwan,China is significantly higher than that of the ‘New Southward’ countries. In order to boost economy, the Taiwan authority should adhere to the‘1992 Consensus’, and vigorously promote the integration of‘New Southward policy’and ‘The Belt and Road Initiatives’, strengthen the economic and trade cooperation and exchanges with Mainland China.
After 30 years of development, national-level economic and technological development zones have become an important engine of China’s economic development as an advanced manufacturing industry gathering area and regional economic growth pole. National-level economic and technological development zones in Beijing-Tianjin-Hebei are not noly the scientific and technological innovation source, the pilot industry gathering area and economic growth locomotive of the coordinated development of Beijing-Tianjin-Hebei, but also bear an important mission of science and technology leading, industrial support and economic driving in the process of the transformation from a big manufacturing nation to a creating power and economic power in China. Constructing an indicator evaluation system for the satus and function of national-level economic and technological development zones in Beijing-Tianjin-Hebei from three dimensions: science and technology leading, industrial support and economic driving, this article utilizes comprehensive graphic method for all arranged polygons to measure the status, function and evolution trend of 13 national-level economic and technological development zone in Beijing, Tianjin and Hebei from 2011 to 2014. The research shows that each economic and technological development zone in Beijing-Tianjin-Hebei continues to optimize, and their development gradually enter a new stage of the depth adjustment, transformation and upgrading; The development of each economic and technological development zone has its own merits and short board, and their development initially form a development pattern of differentiation and non- equalization; The gap between economic and technological development zones gradually has been narrowed, and their development initially show a development trend of comprehensive rising, collaboration going hand in hand; The development index and the order will continue to adjust, but the overall development pattern will not be much changed. The study found that the development of economic and technological development zones in Beijing-Tianjin-Hebei is also facing some outstanding problems, such as the low efficiency in intensive use of resources, the slowness in industrial transformation and upgrading, the lack in power of enterprise innovation, the disparity in regional development gap. To this end, national-level economic and technological development zones in Beijing, Tianjin and Hebei should activate the innovation ability of enterprises to enhance the leading ability of science and technology; promote the development of industrial cluster and intension to speed up the transformation and upgrading of itself; and cultivate a new kinetic energy of economic growth to play a leading role of regional development.
基于企业微观主体视角,运用UCINET社会网络分析和ROST内容分析法,对杭州市企业迁移的空间模式和区位选择进行探讨,并揭示其影响机制。研究表明：① 杭州市企业迁移分为平缓波动期、低速增长期、大规模迁移期、迁移成熟期4个阶段,与杭州市跨江发展历程基本相契合。② 杭州市企业总体迁出呈中心-外围衰减分散布局模式,迁出地点主要集中于西湖区、下城区及拱墅区,迁出企业主要为制造业,批发零售业等;总体迁入呈中心、外围集聚模式,迁入地主集中于西湖区、余杭区及滨江区,迁入企业主要为信息技术服务业、科学研究和技术服务业。③ 企业的自身属性与外部环境对杭州市企业迁移有着重要影响,企业异质性在很大程度上决定着企业迁移的方向;跨江发展战略中的政府推动、市场运作、企业参与、文化根植等外部因素对企业迁移的空间选择有着极其重要的作用。
Based on the enterprise’s microcosmic perspective, the paper discussed the spatial pattern and location selection of Hangzhou enterprise migration by using UCINET social network analysis and ROST content analytical method, and revealed its influence mechanism. The research shows that: 1) Hangzhou enterprise migration can be divided into: gently fluctuating period, slow growth period, mass migration period and migration mature period, which are basically consistent with the river-crossing development history in Hangzhou. 2) The general migration of enterprises in Hangzhou has been presented in a dispersed layout of decentralized attenuation. The enterprises in the manufacturing industry and wholesale and retail industry have been mainly moved from the West Lake district, the Xiacheng district and Gongshu district. While the overall immigration has been presented in a central and peripheral agglomeration pattern. The enterprises in the scientific research and technical service industry have been mainly moved in the West Lake district,Yuhang district and Binjiang district. Enterprise migrations in various industries have their own features, forming migration patterns with their own uniqueness. 3) The enterprise's own attributes and external environment have important influences on migration of enterprises in Hangzhou. The enterprise heterogeneity largely determines the direction of enterprise migration. The planning and control, market operation, enterprise participation and cultural root in the river-crossing development strategy have been directly affected spatial selection for enterprise migration, further promoting enterprise migration. The research not only lays a foundation for revealing the process and mechanism of spatial reconstruction for urban development spanning the river, but also provides scientific references for the formulation of urban planning and other related policies.
以长江三角洲核心区为例,利用1990、2000、2010年3期遥感影像解译获取土地利用变化数据,按照“生产-生态-生活”土地利用主导功能分类,通过土地利用转移矩阵、生态环境质量指数、土地利用转型的生态贡献率等方法,定量分析长江三角洲地区土地利用转型、时空格局特征与生态环境效应。结果表明：① 1990~2010年,长三角地区基于“三生用地”的土地利用转型表现为生产用地减少,生态用地稳定,及生活用地快速增加。② 长三角地区生态环境质量指数从1990年的0.470持续降至2010年的0.444,整体质量有所恶化,较高质量区和高质量区面积与比重保持稳定。③ 1990~2010年,长三角地区同时存在生态改善和恶化的两种趋势,生态环境改善小于环境恶化的趋势。城镇和农村生活用地、工矿生产用地对农业生产用地的挤占则是导致生态环境质量恶化的重要原因。
According to land use classification based on leading function of production, ecology and living, we take the Yangtze River Delta as a case and made use of land use change/cover data in 1990, 2000 and 2010 respectively by remote sensing interpretation obtained from Landsat TM and ETM+. And then we quantitatively analyze the characteristics of land functional structural and spatial transformation as well as its eco-environmental impacts. The methods discussed in the article include land use transfer matrix, index of regional eco-environmental quality and ecological contribution ratio of different kinds of land changes. The results show that: 1) Land use changes in the Yangtze River Delta is chiefly manifested as the area decrease of productive land, stability of ecological land and increase of living land. Main types of transformation are the conversion from agricultural productive land into urban and rural living land, and that from water and pasture ecological land into agricultural productive land, which makes land use structure maintain the dynamic balance. 2) The index of eco-environmental quality in the Yangtze River Delta has been reduced from 0.470 in 1990 to 0.444 in 2010, therefore the overall quality has deteriorated. The percent of the lower mass area is about 45%, which constitutes the main body of land use environment quality. The proportion and the size of higher quality and high quality regions remain stable. And then, due to the rapid expansion of urban and rural living land, make the expansion of low mass region as “hot spots”. The regions of relatively low quality and quality mainly distributed in the periphery of the hot zone, and form the “core - periphery” structure with the low quality region in space. 3) From 1990 to 2010, there are two trends of ecological improvement and deterioration in the Yangtze River Delta region. In the whole, the eco-environment quality of land use pattern declines slightly. The critical factor of eco-environmental improvement is the conversion from agricultural productive land into woodland, water and pasture and that of eco-environmental degradation is the large occupation of agricultural productive land by rural and urban living land.
Although abundant studies on tourism efficiency have been made both at home and abroad, few of them have explored and analyzed the dynamic mechanism of tourism efficiency from the perspective of spatial nonstationarity. Based on DEA model, this article analyzes the features of travel agency efficiency spatial differentiation of the 31 provincial-level regions in China. And by using GWR model initially, the spatial differentiation of regional travel agency efficiency influenced by the five driving forces, i.e. transportation, capital, human resource, informatization, and economy has been explored in this article. Compared with the ordinary least square(OLS), GWR model extends the traditional regression framework by allowing the estimation of local rather than global parameters. The results show that: Firstly, the distribution of China travel agency efficiency shows evident positive correlation and spatial dependence; and as time goes on, this dependence increases. Secondly, in space differentiation, the difference between east and west China is increasing, the difference between north and south China is narrowing, and the role of central and south region becomes more significant to some extent. Due to the influence of these changes, the spatial pattern oftravel agency efficiency transforms from a three-vertical-line type to a three-vertical-and-one-horizontal-line type. Thirdly, the test result shows that the GWR model is more suitable than the ordinary OLS model in terms of seeking the driving forces of the regional travel agency industry efficiency since the coefficient of each driving force has spatial nonstationary property. What’s more, the spatial distribution of the regression coefficients of different driving forces shows some complexity. Although capital and human resource driving forces have negative and positive impact on travel agency industry efficiency respectively, the spatial distributions of regression coefficients of these two factors exert much more influences in the south than that of the north. On the contrary, the regression coefficient of the economy driving force decreases from north to south. The regression coefficients of transportation and informatization driving forces show the features of two belt distributionsin the east and in the west respectively, and their influences are just the opposite. Transportation force plays a more important role to boost the travel agency efficiency in the central and west regions than that in the east; On the contrary, informatization force is more significant to enhance the travel agency efficiency in the east region, which indicates that the extent of informatization exerts more influences on the travel industry in the east region. In conclusion, priority should be given to choose and perfect the more powerful factors according to the different influences exerted on the local travel agency industry efficiency by different dynamic factors so as to boost the efficiency of the travel agency industry.
以东北地区34个地级市为研究对象,利用灰色关联模型和耦合度模型,对东北地区人口结构与经济发展的耦合关系进行分析,结果表明：① 人口结构与经济发展整体处于中高等关联水平,人口文化素质和城市化水平对东北地区经济发展的驱动作用明显;② 自2000年以来,东北地区人口结构与经济发展耦合关系整体经历了波动上升、平稳下降、缓慢上升的过程;③ 人口结构与经济发展相互影响、相互制约,在经济发展的不同阶段,经济发展与人口结构均处于协调发展状态,但是协调水平高低不同;④ 各省人口结构与经济发展耦合度变化差异较大,辽宁省两系统的耦合度呈现出与整个东北地区大致相同的变化趋势。
As the important old industrial base in China, the Northeast China facing the pressure of economic downturn and seriously population problem. Researching the coupling relationship between population structure and economic development is significant for making the population and economic policy. This article measured the correlation degree and coupling degree of Northeast China, and then analyzed the temporal and spatial evolution and exploring the relationship characteristics of the two systems by using the grey relationship analysis. The results show that: 1) The population structure and economic development in the upper elementary level. The population cultural quality and urbanization drive the economic development obviously in Northeast China; 2) During the fifteen years, the population structure and economic development experienced the fluctuant rising -fallen fairly-rising slowly. 3) Population structure and economic development affect and interact each other, and the two systems in the stage of coordinate in various economic development phases. The rationalization of the population structure will be higher when the economy developed well, at the meanwhile, the rational population structure will drive the economic development, which makes the two systems at the coordinate condition. And if not, population structure and economic development will in the state of lower coordination. 4) The coupling relation of population structure and economic development in Liaoning Province is the mainly cause of the Northeast China.
以贵州南部地区为例,对涵养水源、固碳释氧、净化大气环境、保育土壤和生物多样性保护5个功能类别共14项指标的生态系统服务物质量进行了区域尺度和县域尺度上的估算。结果表明：① 贵州南部地区林草生态系统年调节水量145.41×108m3,年固碳量和年释氧量分别为819.96×104t和1 538.48×104t,年提供负离子达2.32×1025个,年吸收二氧化硫(SO2)、氟化物(F)、氮氧化物(NOX)分别达到58.07×104t、1.29×104t和7.76×104t,年滞尘量1.04×108t,年固土总量9.07×108t,年保育N、P、K以及有机质量分别为184.81×104t、59.26×104t、1 138.80×104t以及4 045.85×104t,平均生物多样性综合评价指数为54.87;② 各类生态系统服务物质量均表现出明显的空间分布趋势,整体表现为东高西低,南高北低;③ 县域尺度上,黎平县、榕江县、从江县和望谟县提供的生态系统服务物质量最多,普定县、三穗县、长顺县和丹寨县则最少;就生态系统服务供给能力而言,雷山县、望谟县、榕江县和从江县最强,兴仁县、普定县、长顺县和贞丰县则最弱。
Quantitative assessment for ecosystem services(ES) is perceived as the basis of decision-making to optimize the allocation of regional environmental resources and to formulate eco-compensation policies. Using physical assessment method (PAM) to estimate regional ES could surmount the limitation of traditional valuation method which was effected deeply by price factor and incapable of reflecting the dynamic characteristic of ES. In addition, exploring the variation of ES at county scale is important to reveal spatial inequality of regional eco-resources, therefore to optimize ecosystem spatial structure and harmonize regional economic development. Based on the PAM, this paper estimated the physical quantity of main ES within southern Guizhou Region, which was specialized into fourteen indices of five categories consist of water conservation, carbon fixation and oxygen release, atmosphere environmental purification, soil conservation and biodiversity protection, at both regional and county scale. Plenty of methods including the rainfall storage capacity method, revised universal soil loss equation (RUSLE), and biodiversity composite assessment index method were employed. The results indicated that the forest and grassland ecosystem in Southern Guizhou regulates water 1.45×1010m3/a, fixes carbon 8.20×106t/a, releases oxygen 1.54×107t/a, supplies negative-ions 2.32×1025/a while absorbing of sulfur dioxide(SO2), Fluoride(F), Nitrous oxides(NOX) and dust 5.81×105t, 1.29×104t, 7.76×104t and 1.04×108t per year, respectively. The soil conservation approaches 9.07×108t/a, reducing loss of N, P, K and organic matter 1.85×106t, 5.93×105t, 1.14×107t and 4.05×107t per year, respectively. The average biodiversity composite assessment index reaches 54.87. It presented a pattern of high in east and south, low in west and north as a whole in the spatial distribution of physical quantity at each categories of ES. At county scale, Liping, Rongjiang, Congjiang and Wangmo were estimated to have provisioned the most physical quantity of ES, while Puding, Sansui,Changshun and Danzhai being the less ones. In terms of the capacity of provisioning ES, the strongest counties were Leishan, Wangmo, Rongjiang and Congjiang, and the weakest ones were Xingren, Puding, Changshun and Zhenfeng.
通过构建人口健康脆弱性评价指标体系,利用集对分析法对中国31个省级行政区（不含港、澳、台）的健康脆弱性指数进行测算,同时引入障碍度模型考察脆弱性指数分布差异的影响因素,并对各省区主要障碍因子进行识别。研究发现：① 2014年中国人口健康脆弱性省际差异较大,总体上处于中、高水平,在空间上呈现明显的“西高、东低、中部居中”分异格局,与健康敏感性、应对性指数的地域分布不尽一致;② 各省区健康脆弱性指数分布的地域级差化特征明显,低脆弱省市均分布在东部地带,高脆弱省区均分布在西部地带,中度和较高脆弱水平的省区数量最多,在三大地带上均有分布;③ 健康脆弱性降低的主要障碍因子存在较大地区差异,促进经济发展、增加社保支出、加大卫生投入、改善医疗条件和优化生态环境对降低脆弱性尤为重要。
Health is a person's basic rights, is also the important content of well-off society construction in our country. Regional population health system is an essential subsystem of man-land relationship territorial system. Chinese residents’ health system has become more unstable, complicated and vulnerable due to industrialization, urbanization, population aging and changes of disease spectrum, worse environment and unhealthy lifestyle. By establishing an assessment index system of population health vulnerability, this article employed the set pair analysis method to measure the health vulnerability index of 31 provinces in China. In addition, the obstacle degree model was introduced to investigate the influencing factors of the vulnerability index distribution differences and the main obstacle factors. This article used the authoritative data, both from the statistical yearbooks and statistical bulletins published by government department. The findings showed that: 1) In 2014, the health vulnerability of Chinese residents varied vastly on a provincial level. Top five provinces were Guizhou, Xinjiang, Gansu, He’nan, and Yunnan. Among them, most were located in West China except He’nan province, while the last five ones were Liaoning, Jiangsu, Tianjin, Shanghai and Beijing, all in East China. From an overall perspective, the health vulnerability of Chinese residents was strong in the west, middle in the central area and weak in the east, which coincided with the distribution of health sensitivity index. The response index, however, was different in space distribution which was strong in the east, middle in the west and weak in central China; 2) According to the mean and standard deviation of vulnerability index, 31 provinces fell into four categories of degree, which were weak, middle, middle strong and strong respectively. Figures suggest that regional difference of the health vulnerability index among the provinces was apparent. The provinces of weak vulnerability were all distributed in the eastern area while the strongly vulnerable provinces were located in the western area; the middle and middle strong vulnerability provinces had lion’s share, distributed in all three areas. The sensitivity index, response index and their relationships were different among different vulnerability level provinces; 3) To promote residents’ health and reduce health vulnerability. it is important to maintain economic growth at a middle or high speed, increase residents’ income steadily and invest more in social security, public health, health care and environmental protection to improve the coping capacity of society. According to the “Healthy China 2030” plan issued in October of 2016, the next 15 years is an important period with strategic opportunities of construction of healthy China. This paper succeeds in drawing meaning full and practical conclusions by applying pair analysis method to study the health vulnerability. Meanwhile, the findings also expand and develop the theory and methodology for the health geography.
基于统计数据,采用对数平均迪氏分解模型,从全国和省域2个尺度研究农作物播种面积、单位面积产值、增加值率、价格变化等因素对2003~2014年中国种植业增加值的影响方向与程度,以期为农业政策调整和差别化的种植业生产策略制定提供依据。结果表明：① 12 a间种植业增加值增加了25 608.4亿元;农产品生产价格指数的提升、单位面积产值的快速增加叠加上农作物播种面积的稳定增长,导致研究期间种植业增加值的明显上升;种植业增加值呈现“北进中移”的发展趋势,长江中下游区、黄淮海区、西南区等省域的种植业增加值明显增加。② 各因素对各省域种植业增加值的作用方向和作用强度呈现出一定的差异性,农产品价格指数的明显提升和单位面积产值的快速增加是大部分省域种植业增加值快速增长的主要推动力,而农作物播种面积的稳定增加也起到比较明显的正向促进作用;新疆和内蒙古农作物播种面积的正向效应明显,北京、上海和浙江农作物播种面积的负向效应明显;东部沿海省域和直辖市增加值率的负向效应比较明显。
In the context of tight resource and environmental constraints, it is an urgent task to realize the sustainable utilization of agricultural resources and the steady growth of planting industry. Since 2004, what is the growing trend of planting added-value in China? What are the main factors that lead to the change of the planting added-value in China at the country level and at province level respectively? And how much the influence? Based onthe statistical datathat sourced from "China agricultural products cost-benefit compilation" (2005-2015) and "China Rural Statistical Yearbook" (2005-2015), applied the logarithmic mean weigh division index method, in which direction and to what extent such factors as the sown area of crops, unit area yield, value-added rate and agricultural price fluctuation affect the added value of crop farming in China in national and provincial dimension from 2003 to 2014 are investigated in this article. The results show that: 1) The added value of crop farming has increased 25 608.4×108 yuan(RMB) over 12 years; the increase of agricultural price index, rapid growth of unit area yield and steady increase of sown area of crops have led to a significant increase in the added value of crop farming during the investigation; the added value of crop farming “transferred to central and northern China” and significantly rose in the middle and lower reaches of the Yangtze River, Huang-Huai-Hai Region and some southwestern provinces. 2) The impact of each factor on the added value of crop farming differs in direction and extent; the significant increase of agricultural price and rapid growth of unit area yield constitute the main driving force for the rapid growth of added value of crop farming and the steady increase of sown area of crops also has significant, positive impact; the positive impact of sown area in Xinjiang and Inner Mongolia is significant, the negative impact of sown area in Beijing, Shanghai and Zhejiang is significant and the negative impact of added value rate in coastal provinces of eastern China and municipalities is also significant. The results provide references for the adjustment of agricultural policies and the formulation of differentiated planting strategy in China.
基于主要温室气体（CO2、CH4和N2O）强迫因子和石笋δ18О观测资料（1~2002 年）,分别利用关联性耦合模型和非线性统计-动力学方法,分析温室气体强迫与东亚亚热带季风演变耦合度的时序规律和定量反演模拟温室气体强迫对近2 000 a东亚亚热带季风演变影响的非线性趋势和相对贡献。研究发现：① 温室气体与季风演变耦合度的高低对应季风的强弱变化,即两者耦合作用越强,东亚亚热带季风越强;反之,两者耦合强度越小,东亚亚热带季风越弱;耦合度峰谷值对应季风极强降水和极端干旱时段。② 时序演变规律为：N2O和CO2相互作用与季风演变间耦合效应最强,成为东亚亚热带季风演变的主要驱动力。其次,N2O一次项和CO2非线性项对季风演变起主要的负反馈调节机制。③ 时序演变阶段上有所不同：1~180年,CH4因子对季风演变主要起负反馈调节机制;180~1760年和1760~2002年,对季风演变起主要的驱动和调节机制分别为CO2因子和N2O因子;但1900年后N2O和CO2相互作用与季风演变的耦合驱动效应近百年来明显增强,耦合度在中等-较强（或极强）之间来回波动转换,耦合作用明显增强,在耦合度由较强（或极强）转弱至中等时,东亚亚热带季风也随之减弱。
Based on the observed data of the main greenhouse gases (CO2, CH4 and N2O) and stalagmites δ18О (1-2002), the correlation coupling model was used to analyze the coupling degree temporal variation rule of greenhouse gas forcing and the East Asian monsoon,and the nonlinear statistical-dynamics method was used to simulate the nonlinear trend and relative contribution of greenhouse gas forcing to the East Asian subtropical monsoon evolution over the last two millenniums, which provide the new scientific insights for the assessment of East Asian monsoon evolution. The results show that: 1) The coupling degree of the greenhouse gas and the East Asian monsoon is corresponding to the intensity of the East Asian monsoon, i.e. the stronger the coupling effect is, the stronger the East Asian monsoon is; on the contrary, the weaker coupling strength is, the weaker East Asian monsoon is; the peak-valley value of coupling degree is correlated with extreme strong monsoon precipitation and extreme drought period. 2) The coupling effect betweenthe interaction of N2O and CO2 and the evolution of East Asian monsoon is the strongest, which is the main driving force of East Asian subtropical monsoon evolution. Additionally, N2O and nonlinear term of CO2 plays the main negative feedback regulation mechanism for the monsoon evolution. 3) The temporal evolution phases are different: the CH4 has a negative feedback regulation mechanism on the East Asian monsoon in 1-180. The CO2 and N2O play the main driving and regulating mechanism role in the monsoon evolution in 180-1760 and 1760-2002, respectively. But the coupled driving effect of N2O and CO2 interaction and monsoon evolution is evidently enhanced after 1900. The coupling degree fluctuates back and forth between medium and strong (or very strong), and the coupling effect is obviously enhanced. The East Asian monsoon also weakened when the coupling degree weakened from strong (or stronger) to moderate period.