By taking the panel data in Chinese mainland from 1996 to 2010 for an example, this article uses the methods of ESDA, gravity center and standard deviation ellipse to analyze the spatial differences of tourism development in 31 regions of China. Finally, along with the impulse response function, it proposes the influences mechanism of spatial evolution. The results show that, the provincial tourism economy generally performances a random spatial distribution situation and the spatial differences have narrowed from 1996 to 2010. The differences of tourism development in the east of China are the largest, and differences of the middle of China are the smallest. The gravity center of Chinese provincial tourism has shifted to the northwest, the High-High district totally concentrated in Changjiang River Delta and its surroundings, the Low-Low district totally concentrated in the west of Chinese. The high-value areas of city tourism economy are broadly distributed in the right of line ‘Heihe-Tengchong’, mainly concentrated in 4 groups: 1) Bohai economic circle, including Beijing, Tianjin, Liaodong peninsula and Shandong peninsula, 2) the Changjiang River Delta economic circle and its surroundings, 3) the Zhujiang River Delta, Hainan island and its surroundings, 4) the Chengdu-Chongqing economic circle and its surroundings. It can be founded by comparative analysis in different spatio-temporal scale that the Changjiang River Delta, the Zhujiang River Delta, Beijing-Tianjin area and the Chengdu-Chongqing economic circle as well as its surroundings are the four most developed areas of Chinese tourism economy. From 1996 to 2010, the mainland’s tourism economy has been significantly improved, and generally shows a random spatial distribution. The difference of provincial tourism development totally has decreased, but that of cities has increased more significantly. Regional tourism resources and socio-economic factors are the two major factors to influence the spatial differences of tourism economy, and the objective rule and policy and institution also have a great impact on regional tourism development differences. Special events may have a certain impact on the pattern of the original; however, it cannot change the spatial pattern completely. This article only selects the time section from 1996 to 2010, other times whether like this or not still needs further study, but this research is consistent with the actual situation. Long time and multiple indexes are still a direction in the future research of spatial differences about tourism economy. It employs the qualitative and quantitative methods to analyze the mechanism of spatial differences of tourism economy, but how to quantity these factors, such as policy, institution, traffic mode et al, and how to reveal the depth impact mechanism are still need further exploring.
从人居环境系统视角出发,以大连沙河口区199个典型住宅小区为研究对象,实证探索了城市人居环境类型及空间格局。研究结果表明：① 影响城市人居环境六大主因子为居住质量、邻里关系、自然环境、生活便利度、轻轨交通、教育医疗;② 以六大因子与不同收入群体的人居活动交互作用为依据把大连沙河口区人居环境分为低收入群体&#x02014;&#x02014;居住质量差型、中等收入&#x02014;&#x02014;居住系统均衡型、高收入&#x02014;&#x02014;居住质量高和公共设施良好型、高端人士群体&#x02014;&#x02014;自然环境优越型,以及非自由选择分配住房的单位制居民&#x02014;&#x02014;邻里关系密切型;③ 5种城市人居环境类型&#x0201c;同质&#x0201d;集聚与&#x0201c;异质&#x0201d;集聚并存,形成以海岸线三圈层结构为主的南高北低态势,辅以中东部商圈高收入居住区,中西部混合异质区的复合圈层空间格局。
Applying the traditional methods of Principal Components Analysis and Hierarchical Cluster Methods, the spatial pattern and formation mechanism of human settlement type were explored from the human settlements system perspective using 199 typical residential quarters in Shahekou as the case study. These results showed that: six main affecting factors of urban human settlement in Shahekou, Dalian were identified. 1) The quality of building, neighborhood relations, natural environment, convenient degree of living, the access of light rail transit, and medical and education facilities. 2) Based on the interactions between the relationship of six main affecting factors and different income groups, this article divided Shahekou District into 5 types, which are the poor living quality type for the low-income, balanced living system type for the middle-income, high quality of housing and public facilities type for the high-income, the pleasant natural environment for the high-end groups, and the neighborhood dense type formed on the basis of &#x0201c;danwei&#x0201d;, which caused by historical house allocation policy without free choice. 3) The &#x0201c;homogeneous&#x0201d; agglomeration and &#x0201c;heterogeneous&#x0201d; agglomeration of 5 human settlement types coexist in Dalian Shahekou district. The spatial pattern of &#x0201c;homogeneous&#x0201d; agglomeration is represented by &#x0201c;Ring homogeneous gathering form&#x0201d; meaning three types of human settlement dispersed in three spheres respectively based on the southern coastline as a benchmark, and &#x0201c;homogeneous gathering forms&#x0201d; meaning the third type of human settlement hold together and push into the center of Peace Square Business Circle and Xi'an Road business circle. The spatial pattern of &#x0201c;heterogeneous&#x0201d; represents by &#x0201c;the insertion into internal spheres&#x0201d; heterogeneous region and &#x0201c;broken and mixed type&#x0201d; heterogeneous region. 4) The human settlement spatial pattern in Shahekou is a three-ring spatial pattern structure based on coastline, supplemented by high-income human settlement on the mid-east, mixed heterogeneous human settlement on the mid-west. Finally, this article analyzed the mechanism of human settlement type and spatial pattern from the point of view of the interaction among 5 main subsystems of human settlement system, the 2 main subject subsystems, &#x0201c;mankind&#x0201d; and &#x0201c;social network&#x0201d;, and the 3 main object subsystems to accelerate or slow down the formation process of human settlement classification and spatial pattern.
基于问卷调查和旅行社推介线路,获取旅游客流数据,借助社会网络结构洞理论、社会资源理论与结构角色理论,运用Ucinet和Netdraw软件,构建跨界旅游客流网络结构模型,并以川滇泸沽湖为案例地,探讨跨界旅游客流空间布局模式、网络结构及节点角色地位,试图揭示跨界旅游客流时空演变、扩散规律及内在机理,为跨界旅游区协同合作提供一定的科学依据。结果表明：① 泸沽湖跨界旅游客流网络中,丽江古城区、大玉龙景区是旅游客流网络的核心和集散中心;泸沽湖、香格里拉处于次级旅游核心和次级集散中心地位;大理古城区、苍山洱海、昆明市区、束河古镇是重要旅游目的地和旅游通道;泸山邛海是唯一位于四川的次级集散中心和重要目的地;其他旅游节点中心性指标得分较低,主要接受高等级旅游地旅游客流辐射,相互连接强度较低,为一般旅游目的地和边缘旅游目的地;② 跨界旅游区客流网络存在核心-边缘结构,边界效应极强,客流网络结构分层明显,可细分为旅游核心、云南片重要旅游节点、云南片一般旅游地、跨界旅游地和四川片重要旅游地5类;③ 旅游客流网络中存在明显的派系,泸沽湖旅游客流流动路径指向云南片区大玉龙景区、丽江古城区、香格里拉及四川片区泸山邛海,这些地区成为景区突破边界效应,带动跨界旅游一体化发展的关键。④ 川滇两省旅游行政部门共同制定旅游区发展规划,树立统一的旅游品牌形象,整合并优化资源、产品与线路,完善跨界旅游交通网络等是今后泸沽湖跨界旅游合作的重点。
Network perspective has already been applied in diverse areas. However, the adoption of innovation network formed by companies, universities and research institutes is not as common and integrated as that the academic research might have emphasized, especially the equipment manufacturing industry in the Changjiang River Delta of China. This article, using data from the national key industry patent information service platform, focuses on the structural and spatial characteristics of the innovation network from 1985 to 2010. Combining the judgment that universities have been the main forces in the field of public research since 2000, we analyze the evolution of the innovation network in terms of node type, segmented industry category and location by four stages in 1985-1999, 2000-2005, 2006-2008 and 2009-2010. Utilizing the analytical approach of the social network, there are some main conclusions drawn from the research. 1) Features of innovation network of equipment manufacturing industry in the Changjiang River Delta have changed obviously from 1985 to 2010, showing a “core-periphery” paradigm. The bidirectional interaction of cooperative innovation mechanism between universities and companies has not yet been established. It still stays at the initial stage. 2) From the spatial characteristics of the network during 1985-2010, cities have different characteristics individually. Although other cities out of the region, such as Beijing, have become a powerful knowledge pool, cities located in the region of Changjiang River Delta still tend to cooperate with local universities or research institutions. It is obvious that geographic proximity, administrative proximity and knowledge size proximity become the most important factors which influence agents to build the cooperation networks. 3) In order to promote the performance of innovation network, the article deems that we should select key enterprises, firms and factories. By supporting the central nodes, establishing the knowledge transfer platform and encouraging firms to cooperate with universities and research institutions in the process of innovation, we predict that the innovation network system of industry-university-research interaction of equipment manufacturing industry in Changjiang River Delta will become more robust and reliable. Finally, we make some key suggestions for the future research. First, the advantage of patent lies in the higher availability and controllability, but it only presents one facet of the innovation. So we must strengthen field research to get more detailed and accurate data. Second, the depiction of network graph can be conductive to express the visualization of information, but it does not involve the analysis of internal evolution mechanism. At last, it is important to build a multi-dimensional adjacent framework. The interaction effect on innovation between network and space will be the focus of research in the next stage.
Central Plains Economic Zone (CPEZ) is an important strong point in the regional economic development of China. Studies on the interaction strength among the regional cities are conducive to the analysis of cities’ economic connection degree. More importantly than all of that, this study is of great significance for urban spatial structure, spatial structural optimization of urban economy, and the development of the economic CPEZ zone. This article selected 30 provincially-administered cities from CEPZ zone to conduct analysis of Gravity Model, Potential Model, Potential Scores, and Membership Model. The the evolution process and the characteristic of the interactional spatio-temporal pattern of CEPZ cities for two decades (1990-2010) were investigated by the analysis strategy of “Line ? Point ? Surface”. Gravitational forces among different cities were calculated and symbolized into varied lines on the base of size of statistic data. Thickness of the lines represents the connection characteristics between any two cities from CEPZ. Then, the potential capability of each city was figured out by using symbolized point to identify the potential grade of each city. The symbolized point and maximum gravity joint line were linked to show the connection characteristics. Finally, seven cities were chosen to play candidate regional central role. We calculated the economic membership of the seven candidate cities. The first results of economic membership were used to select regional central cities. At the same time, the spatial dimensions were determined for each candidate city. Kriging spatial interpolation was also applied in this study to express the standardized values in spatial pattern, which is based on the potential score from each city’s economic capacity. The result shows that significant spatio-temporal differences occurred among the CPEZ cities. In “Line” level, the gravitational force has been enhanced and the count of join lines among the cities has been increased, where network structure appeared. We found that the variation of gravitational force is closely related to the count of joint lines. The same spatial pattern was observed in both of the variables. In “Point” level, “Lines” were stacked with points to perform the analysis. We also found the maximum joint line increased when the temporal-spatial difference occurred in city potential capacity. During the past two decades, the spatio-temporal differences varied significantly between selected cities. In “Surface” level, there is no change in regional central city. The other four cities, however, bear a significant change in hinterlands. Core Group—Zhengzhou Group extended in north direction in the first 10 years (1990-2000). It extended again in second 10 years (2000-2010) for eastern side. We also observed periodic characteristics of spatial shrink in the areas of high potential grade from 2000 to 2010.
中国未来城镇化的主要任务已经转变为优化结构和提高质量,而新型城镇化则是实现这一目标的必由之路。在深刻理解新型城镇化的内涵的基础上,建立了由人口、经济、空间、社会、生态环境、生活方式、城乡一体化、创新与研发8个子系统构成的新型城镇化评价体系,采用熵值法确定评价指标权重,对山东省17个地级城市新型城镇化发展水平进行测度。研究结果表明：① 山东省新型城镇化受传统城镇化影响严重,要加强生活方式、生态环境、城乡一体化以及创新与研发方面的建设。② 济南、青岛、威海、淄博为新型城镇化高水平区,东营为新型城镇化较高水平区,烟台、莱芜为新型城镇化中等水平区,泰安、滨州、日照、潍坊、枣庄为新型城镇化较低水平区,济宁、临沂、德州、聊城、滨州、菏泽为新型城镇化低水平区。
China has entered into urban society, the main task of the future urbanization has been turned into optimize the structure and improve the quality, while the new urbanization is the only way to achieve this goal. On the basis of deeply understanding the connotation of the new urbanization, the evaluation system of new urbanization was established in the article, which was composed of eight subsystems: population, economy, space, society, ecological environment, lifestyle, urban-rural integration, innovation and R&#x00026;D. The weight of index was worked out with the entropy method to improve the objectivity and reliability, and to measure the development level of the new urbanization of the 17 prefecture-level cities in Shandong Province. It was found that there were obvious regional differences in the development level of the new urbanization of the 17 prefecture-level cities: the comprehensive development index of the new urbanization in Jinan (60.26) is the highest, while which in Heze(18.16) is the lowest. The range and standard deviation are both relatively large. On the basis of the analysis, the 17 prefecture-level cities were divided into five types through clustering analysis. The distribution of the development level of new urbanization in the whole province demonstrates that the high level cities are in east and north, and the low are in west and south. The development level of the new urbanization in Jinan, Qingdao, Weihai and Zibo were much higher than the average level of the whole province, which belongs to the high level area of the new urbanization. The development level of the new urbanization in Dongying is relatively high, especially the level of economic urbanization. Yantai and Laiwu belong to the middle level area of the new urbanization, the development level of new urbanization in the two cities were slightly higher than the average level of the whole province. The relatively low area of the development level of new urbanization includes Taian, Binzhou, Rizhao, Weifang and Zaizhuang . Jining, Linyi, Dezhou, Liaocheng, Binzhou and Heze belong to the the low level area of new urbanization. In these cities the development level of new urbanization were far below the average level of the whole province, which were related to the backward economy and the low level of industrialization, and the development level of every subsystem in these cities was also low. Grey correlation analysis was used to further explore the degree of influence of each index on the development level of the new urbanization. The results showed that the new urbanization of Shandong Province was seriously affected by the traditional urbanization, the comprehensive development index of the new urbanization was closely related to economic urbanization, space urbanization, social urbanization and population urbanization. It needs to be strengthen the construction of lifestyle, ecological environment, urban-rural integration, innovation and R&#x00026;D, and promoting the quality of the new urbanization should be pay more attention to.
运用产业结构转换系数、农业多样化指数、多部门经济分析模型、能源生产弹性系数等方法,对1978~2011年榆林市农村转型发展进行深入研究。研究发现：① 1978~1991 年,榆林市三次产业结构转换速度系数为 0.123,产业结构缓慢转换;1992~1997年,伴随着中国经济改革,产业结构逐步优化;1998~2003年榆林市产业转换速度达最大值0.276;2004年后,以能源经济为主导的第二产业区域经济发展,产业转换速度有所回落。1991~2011年,榆林市产业结构变动对经济增长的贡献值平均为3.94%,GDP增长的29%是由产业结构变动造成;② 1991~2011年榆林市能源生产弹性系数维持在1.8左右,能源资源开发44.44%的价值外溢。产业结构偏离度、比较劳动生产率、二元对比系数均说明了榆林市农业生产效益较低,以能源化工为主的重工业对劳动力的吸纳能力有限。③ 1990~2011年,榆林市农村居民恩格尔系数由63.07%下降到36.70%,传统食物消费模式逐渐转变,农民生活水平提升。加快能源资源区农村转型发展,促进能源资源开发与农村经济互促发展成为榆林市当前面临的重要任务。
Using the methods of industrial structure entropy, conversion coefficient of industrial structures, agricultural diversification index, multi-sectoral model of economic analysis, energy production coefficient, the article makes intensive study on rural transformation development of Yulin City in Northern Shaanxi. From 1978 to 2011, rural development in Yulin had gone through 5 stages, which were reform and opening up, exploitation of Shenfu coalfield, promotion of market economy, the construction of energy and heavy chemical industry base and new countryside construction. The maximum conversion velocity coefficient of industrial structures in Yulin was 0.276 in 1998 to 2003, After 2004, the conversion velocity coefficient of primary and secondary industries decreased sharply while that of the second industry increased, which showed that industrial structure of Yulin was in the process of industrialization from the lower level to the higher one. In 2011, the proportion of household operating income to farmer net income decreased to 52.8%, which was the main source of rural income, meanwhile, the proportion of food consumption expenditure decreased from 63.07% in 1990 to 19.9% in 2011, which was the major expenditure of rural region. From 1991 to 2011, the average contribution degree to the economic growth of industrial structure change was 3.94%; meanwhile, the 29% of GDP growth is produced by industrial structure change. The elastic coefficient of energy production in Yulin was 1.8, the 44.44% of developed energy resources value was spilled over. All the above showed that agricultural production efficiency of Yulin is relatively low, the heavy industry’s capability to absorb agricultural labor force is limited, so the deviation of industrial structure and the employment structure is significant.
基于第三、四、五和六次人口普查资料,利用数学模型对1982~2010年广州市近30 a来的人口增长与空间分布规律深入探讨。得出以下结论：① 近30 a来广州市人口保持稳定增长,人口分布总体上趋于分散,人口变化趋于缓和,尤其是近10 a来广州中心城区人口密度缓慢降低,近郊区人口密度较快增长,远郊区人口密度逐步增加的特征更加明显;② 人口空间分布由&#x0201c;峰值单中心+外围小中心&#x0201d;结构演变为&#x0201c;扁平化多中心+外围小中心&#x0201d;;③ 广州市人口发展已进入成熟晚期阶段向老年阶段的过渡时期,但中心城区人口缺口尚未出现;④ 广州市人口郊区化始于20世纪90年代末,2000年以来郊区化明显加快,属于市中心发展型郊区化。
The growth and change of population are closely related to the urban development. The regularity of urban population changes provides supports for the policy-making concerned urban development. As the frontier region of reform and opening up, Guangzhou has experienced a rapid economic, social development, and the population change in the metropolitans is earlier than others in China. Using the data of the third, the fourth, the fifth and the sixth censuses at a Neighborhood (Jie Dao in Chinese) and Town (the NT) level by the mathematic methods of density analysis, concentration index, trend surface analysis and regression analysis model, article reveals the characteristics and law of the population growth and distribution in Guangzhou. The main conclusions are as follows: 1) the population growth of Guangzhou can be divided into three stages: the rapid growth stage, from 1986 to 1994, with annual growth rate of 1.74 %; the fluctuation growth stage, from 1995 to 2003, with that of 1.59%; and the slow growth stage, from 2004 to 2010, with that of 1.47 %. The total population has a stable increase in 1986-2010. 2) There is an obvious spatial difference for population growth at the NT level. The number of the NT with the population reduction was increase, while the NT which has rapid population growth has spred from central district to the near suburb and the outer suburb. The distribution of population in Guangzhou maintained a de-centralized regular pattern. Especially last 10 years, it become more and more obvious than the population density in central city is decreased slowly, rapid increase in near suburbs, and stable increase in outer suburbs; 3) The population distribution of Guangzhou presented to be decentralization and equalization. Population concentration index decreased gradually and the trend of population gravity migration moved eastward significantly. The spatial distribution of population has a significant change, which presents a typical &#x0201c;peak value single center + small centers outside&#x0201d; space structure before 2000. Since 2000, the population density in central district expands eastward and northward, the population density in near suburb has a rapid increase, a new population density peak was formed and then spatial distribution presents an obvious &#x0201c;flatten main centers + small centers outside&#x0201d; space structure in recent 10 years. 4) The population growth of Guangzhou was at growing stage before 1990s, was at a mature stage in 2000, and now is in the transition phase from the stage of mature late to the stage of old age, but the population gap in center city has not appeared until now; 5) the suburbanization in Guangzhou, the type of a central district development, had appeared since 1990s, and became obvious since 2000s in Guangzhou. 6) There was an obvious difference in population growth and spatial distribution between metropolitan of China and the developed countries. The population growth in most metropolitan of China is in the earlier stage of urbanization, while most of the developed countries have already moved to the stage of re-urbanization.
According to the new classical economic theory, regional disparities are the result of the unbalanced supply of inter-regional production factors. As long as the interregional flow of production factors is put back in balance and the balance of interregional factor supply is realized, regional disparities will automatically disappear. However, the balanced development of different regions in Xinjiang still has a long way to go, so we need to bring a new angle to the exploration of the spatial source and micro-mechanism resulted in regional disparities. With the basic structure of New Economic Geography theory, this article analyzed and summaried the microcosmic mechanism and the process of the formation of region gap in an intuitive way with the use of logical deduction and graphical presentation. At the same time, it introduced the concept of containing the density of space factors under the framework of new economic geography, which is the spatial agglomeration structure population-economy coordinated development index. The results found that the mismatch between population distribution and industrial concentration under an industrial concentration mechanism is the main reason that leads to the regional disparities in Xinjiang. And under the influence of this kind of concentration mechanism, the regional gap in Xinjiang now presents a significant gradient characteristic. The gap among different gradients is quite obvious, among which the mismatch between population distribution and industrial concentration between the first gradient (which includes the region of Urumqi, Karamay, Changji, Shihezi, Turpan and Kumul) , and the fourth gradient (which includes the region of Kizilsu Kirgiz, Kashgar and Hotan Administrative Offices ) is the main driver to the unbalanced development in Xinjiang. To narrow the development gap, Xinjiang should make its future’s policy design considering its special regional situations to achieve a regional coordinated development through the development of a concentrated economy and the free flow of the labor force.
基于eCogntion、ArcGIS 和IDRISI 软件,采用景观格局指数分析广东南岭国家级自然保护区1988~2009 年景观类型数量及空间格局的变化;运用CA-Markov 模型模拟流域2010年的景观格局,预测2021 年的景观格局。结果表明,研究区森林景观类型以常绿阔叶林和针叶林为主;景观破碎度增加,斑块复杂程度提高,各景观类型的分布更加趋于复杂化;CA-Markov模型预测表明,2010~2021 年景观破碎度有所降低,多样性增加。
Forest landscape pattern and its change is a comprehensive reflection of interaction with natural and artificial factors. In this article, landscape pattern changes of Nanling National Nature Reserve from 1988 to 2009 were analyzed with landscape pattern index based on eCognition and ArcGIS. CA-Markov model was adopted to simulate the landscape pattern in 2010 and to predict the landscape pattern in 2021. The results showed that the study area was mainly forest-based landscapes, more than 95% of the total area, in which, evergreen broad-leaved forest and coniferous forest were two dominant landscape types, other landscape types were distributed in the study area with scattered or gathered, and forming a rich landscape mosaic pattern. From 1988 to 2009, the area of coniferous forest decreased whereas areas of other land and construction land increased. Coniferous mixed forest, evergreen broad-leaved forest, broad-leaved mixed forest and farmland first expanded and then shrank, whereas shrubs, other forests and waters first shrank and then expanded. The level of landscape fragmentation and plaque complexity was increased, the proportion of landscape type has a larger change; landscape diversity was increased after reduced, the dominance, evenness changed little, remaining stable, the fractal dimension of landscape patches was different at different periods, and the increase tendence of human disturbance increased complex to the conversion of various types of plaque. Analysis landscape types changes of time and space, which found that the largest area ratio changes between with coniferous forest and other woodlands, evergreen broad-leaved forest and broad-leaved mixed forest transformation was frequent, also conversion frequency between mixed coniferous forest and coniferous forest, shrub and other landscape types. Construction land was mainly transformed from evergreen broad-leaved forest and coniferous forest, water, as a landscape type in the study area, mainly transformed by coniferous forest. From 2010 to 2021, with CA-Markov model, it was predicted that the area of coniferous forest and evergreen broadleaf forest would reduce, and other landscape trend would grow, of which construction land and water would grow more rapidly. Also the number of major forest landscape patches would reduce significantly, and the distribution be more concentrated, which means the degree of aggregation and connection would increase, fragmentation reduce, and landscape types distribution be towards uniformly in the future. And the level of landscape fragmentation would decline, and the level of landscape diversity would increase in the study area.
不同时空尺度下,生态承载力系统耦合协调度呈现不同差异和变化。在阐述耦合协调发展作用机理的基础上,构建了耦合协调度评价指标体系,利用容量耦合模型对洞庭湖区生态承载力系统耦合协调度进行时空分析。结果表明：① 时序变化上,2001~2012年洞庭湖区生态承载力系统耦合度和耦合协调度变化趋势基本趋同,大致呈现同步稳定上升态势,耦合度均值达0.499,处于拮抗阶段;耦合协调度均值达0.463,处于中度耦合协调阶段;年均增长率上,耦合度达3.35%,大于耦合协调度的3.05%。表明生态承载力内部系统耦合作用和协同效应明显,并且耦合作用的强度大于内部协调性。② 空间分异上,17个县域的耦合度出现了低水平耦合、拮抗阶段和磨合阶段3种状态,3种耦合状态的县域个数和区间变化呈现不同的差异。耦合协调度出现了低度耦合协调、中度耦合协调和高度耦合协调3种状态,其变化状况基本上与耦合度类似,但从协调状态的县域个数和区间变化来看,耦合协调度的变化稍滞后于耦合度的变化,空间分布与耦合度分布特征基本相似,高、低值区的空间分布由西南向东北大致呈现较低-高-低-高-较低的“M”型基本格局。③ 空间组合上,17个县域出现了低耦合低协调区、中耦合低协调区、中耦合中协调区、高耦合中协调区和高耦合高协调区5种空间组合类型,其基本空间格局是,低耦合低协调区集中分布在洞庭湖区中部和西南部,高耦合高协调区则沿京广线、石长线和常岳高速三线呈“三足鼎立”布局,其它不同组合类型则集中于高耦合高协调区外围呈“零星状”分布。
Ecological carrying capacity is a complex dynamic system including natural-economy-society, and its intrinsic coordination is the key to sustainable carrying capacity of ecosystem. In different spatio-temporal scales, the coupling coordinative degree of ecological carrying capacity presents different differences and changes. On the basis of coupling coordinative development interactive mechanism of ecological carrying capacity, the article constructs an evaluation index system of coupling coordinative degree, and analyzes the temporal and spatial difference of coupling coordinative degree of ecological carrying capacity in the Dongting Lake region by using capacitive coupling model. The results show that: 1) The trends of coupling degree and coupling coordinative degree of ecological carrying capacity in the Dongting Lake region from 2001 to 2012 seemed to be the same, and presented roughly steady upward trend. The mean of coupling degree was 0.499, in antagonistic stage; the mean of coupling coordinative degree was 0.463, in the moderate coupling coordinative phase; the average annual growth rate of coupling degree was 3.35%, greater than coupling coordinative degree, which was 3.05%. It indicated that the internal coupling and synergies of the ecological carrying capacity was obvious, and the coupling strength was greater than the internal coordination. 2) As to spatial variation, there were three states of coupling degree in three different years in 17 counties of the Dongting Lake area, which were a low coupling, antagonistic phase and running-in phase, each coupling state had different county number and interval change. The coupling coordinative degree appeared three states of low coupling coordination, moderate coupling coordination and highly coupling coordination, the variation was substantially similar to the coupling degree, however the change of the county number and interval change in coordinative state laged behind the coupling degree. The spatial distribution of coupling coordinative degree and coupling degree were similar, high and low spatial differences were mainly decided by the historical development, social and economic developmental level, traffic location and natural resources. 3) As to spatial combination, there were five kinds of spatial combination types in three typical years in 17 counties of Dongting Lake area, which were low-low, medium-low, medium-medium,high-medium and high-high. The basic spatial pattern was that low-low type concentrates in the central and southwestern of Dongting Lake area, and high-high type were along the traffic lines of Beijing-Guangzhou, Shimen-Changde and Changde-Yueyang, and the layout looked like "three pillars". Other types were focused on periphery of the high-high type, in scattered distribution. The county changes of different combination types reflected the basic law of the change of coupling coordinative degree, which coupling degree and coupling coordinative degree were not consistent; in the process of human social and economic activities, the degree of utilization of resources and disturbance intensity of the ecological environment were directly driving forces leading to the change of coupling coordinative type.
采用主成分分析综合评价方法,对1996~2011年安徽省城镇土地集约状况进行了综合评价;运用Perloff的产业结构测度模型,对安徽省产业结构的构成效应（MIX）、竞争效应（DIF）进行了测算;借鉴STIRPAT模型,采用偏最小二乘回归分析方法,从产业结构的结构效应、竞争效应考察了其对城镇土地集约利用影响,结果表明：① 1996~2011年,安徽省城镇土地利用综合指数呈递增态势,1996~2006年,城镇土地利用指数均值为53.09,2007~2011年,均值为75.2;② 1996~2011年,安徽省产业结构构成效应指数均值为0.012 4,其变化轨迹呈“N”型,而竞争效应指数整体呈上升态势,均值为0.012 8;③ 1996~2011年,安徽省产业结构构成效应、竞争效应对城镇土地集约利用弹性系数分别为-0.002 5和0.004 9。
To optimize the industrial structure is the inevitable demand of Anhui economic development at present and even in the future for a longer period. Industrial structure adjustment not only affects land resource use pattern, structure and spatial layout, but also impacts land allocation and utilization efficiency. To explore the impact law of industrial structure evolution on urban land intensive use is in favor of coordinating the contradiction between economic development and land growth demand as well as land scarcity, which can also provide references for the government to formulate the policies of optimizing the industrial structure as well as guide and promote urban land intensive use. In this article, a comprehensive evaluation was conducted for urban land intensive state in Anhui Province by using principal component analysis; with Perloff’s measurement model of industrial structure, the composition effect (MIX) and competition effect (DIF) of industrial structure in Anhui Province in 1996-2011 were measured. Based on the STIRPAT model for reference, the impacts of composition effect and competition effect of industrial structure on urban land intensive use were investigated by partial least squares regression. Results showed that: 1) Between 1996 and 2011, the comprehensive index of urban land use in Anhui Province showed an increasing trend, with an average of 53.09 between 1996 and 2006 while that of 75.2 between 2007 and 2011. 2) Between 1996 and 2011, the composition effect index of industrial structure in Anhui Province changed in a “N” type trajectory, with an average of 0.012 4, while the competitive effect index showed a upward trend overall, with an average of 0.012 8. 3) Between 1996 and 2011, the elastic coefficients of composition effect and competitive effect of industrial structure on urban land intensive use in Anhui Province were -0.002 5 and 0.004 9, respectively. These findings may provide references not only for decision-making on farmland protection, ecological construction and socio-economic sustainable development in Anhui Province, but also for similar studies in a provincial-scale.
Data missing is frequently encountered in climate variables due to many reasons, such as instrument failures in the observatory, meteorological extremes, and observation recording errors. However, several types of climatic analysis require the availability of data not only covering a long enough period of time, but also forming a complete and homogeneous series. This paper presented a novel imputation method for missing air temperature records by merging their spatio-temporal characteristics. On the basis of extending Kriging model, a nonstationary Kriging method which assumes that the mean is known and varying in study area was proposed. Firstly, the trend of air temperature in each station was attained by analyzing its time series data, and linear interpolation was adopted in this study. Then, geostatistical analysis were performed on the errors between the trend and observed values. Finally, the spatio-temporal information of air temperature was integrated into the proposed Kriging model. Three other imputation methods, including linear interpolation, ordinary Kriging based on DEM (OKD) and normal ratio, were introduced to compare with. The results show that: 1) Besides OKD, the imputation accuracy of the other three methods varies obviously in 12 months. For linear interpolation, its imputation accuracy in May and July-October is much higher than that in the rest of the month. Normal ratio has higher imputation accuracy in April-November. The proposed method has higher imputation accuracy in March-October, with mean absolute error (MAE) less than 0.2℃. 2) Normal ratio has the largest MAE (4.17℃) in December and the least MAE (0.18℃) in October, this means that it has poor robustness. Compared with linear interpolation, the difference between the maximum and minimum MAE values of OKD is much less (0.25℃), thus it has better robustness. With the difference being 0.1℃ only, the proposed method has the strongest robustness. 3) Air temperature contains the temporal and spatial characteristics together. Linear interpolation only considers its temporal characteristics but ignores its spatial characteristics, while OKD only considers its spatial characteristic but ignores its temporal characteristics. Therefore, they don't attain the satisfactory imputation results. With partly taking the spatio-temporal characteristics of air temperature into account, normal ratio can attain higher imputation accuracy in March-November. However, this method has poor robustness. When air temperature in study area varies sharply or fluctuates around 0℃, normal ratio has lower imputation accuracy. As a result, its overall imputation accuracy is still lower. Among these methods, the proposed method has the smallest MAE and root mean square error in each month and produces the best imputation results.
基于中国西北干旱区1960~2010 年70个台站逐日降水资料,采用欧盟组织(STARDEX)定义的降水极值指数,分析结果表明: ① 研究区近51 a来强降水发生频次、湿期平均长度表现出增多和增长趋势,干日数和干期平均长度表现出减少和变短趋势; ② 单次强水的强度在增加,表现为：湿日数减少,而降水的总量却显著增加。③ 湿日数减少主要是0~6 mm强度的降水日数减少,12~24 mm强度的降水日数显著增加,后者对降水总量的增加贡献较大。④ 绝大部分站点强降水（>12 mm）的雨日（量）都以上升趋势为主,表现为下降趋势的站点极少。
This article mainly analyzes the mean precipitation, the maximum consecutive wet (dry) days, the yearly extreme precipitation frequency, the mean wet (dry) spell lengths, as well as the typical value of precipitation of wet days in the past fifty years, and the long-term trends. It is based on the daily precipitation datasets of seventy meteorological stations in arid areas in the northwest of China in 1960-2010. It uses the definitions of nine extreme precipitation indices by STARDEX. The results indicate that: 1) Both strong rainfall frequency and mean wet spell lengths in the past fifty years have increased significantly, however the dry days and the dry spell lengths have decreased; 2) Both the individual strong rainfall intensity and the total precipitation increased, the latter becoming more apparent; 3) The precipitation days of 0.1-6 mm density decreased, but that of 12-24 mm intensity rose and greatly contributed to the increase of the total precipitation; 4) Most stations show the rising tendency of rain days with more than 12 mm strong rainfall, among which the typical stations, are located in mountain areas. The areas with significantly increasing precipitation are consistent with the spatial distribution of strong rainfall, and that there exists evident relevance between the yearly extreme precipitation events and the annual precipitation. All of the above demonstrates that the rising total precipitation in arid areas result from the strong rainfall increase in the northwest of China since the late 1980s.
Based on the perspective of etymology and taxonomy, studies on traditional place names or toponymy usually adopt the descriptive method to explore the origin, classification, dissemination and diffusion of specific place names. However, in social reality, place names are usually dominated by the authority, like the social elites. Social elites possess the rights of naming and renaming and thereby decide what will be remembered or forgotten. Therefore, local memory of some certain groups may be retained or erased in this process. Under the transition period in contemporary China, various spatial organizations are experiencing tremendous changes, while some other social groups are actively participating in the construction processes of social space. Place naming and renaming controversy is increasingly becoming one of the most hotspot issues. Obviously, the descriptive method cannot provide sufficient explanations for the above-mentioned controversy. The critical perspective adopted by the Anglophonic toponymy studies in the past few years may shed light on the place naming studies in Chinese cities. In the context of Anglophonic studies, the studies mainly focused on the cultural and political processes of the change of place names, the rewritten of local memory with the regime change, the privatization of public space due to the commercialization of naming rights, and so on. From the critical perspective of New Cultural Geography, this article focuses on the processes of place naming and renaming and adopts the textual analysis method to analyze the causes of naming controversies and the corresponding power relations in the process of naming and renaming Guangzhou Metro stations. It argues that the naming and renaming processes involve commercial, political and cultural factors all of which point to the core essence of naming rights. The prominent actors, including business enterprises, government agencies and general social groups, hold different positions which are based on their own interests and they actively struggle for the naming rights and continue to negotiate with other actors. The general social groups usually participate in place naming and renaming processes by expressing their dissatisfactions and doubts via the virtual network with non-resistant discourses. News media provide platforms and channels for the disadvantaged expressing their opinions and help them win some benefits through the negotiation. Nonetheless, what the place will be named or renamed still depends mainly on the authority. However, place identity will be strengthened forcefully when the government holds cultural conservation ideas. The article will make up for the “emphasizing description, but ignoring analysis” weakness of the descriptive method by way of textual analysis from a critical perspective and provide new ideas for the research on place names in China. It will also be helpful for the protection of toponymy culture, the inheritance of local cultural memory and the improvement of place identity through properly naming and renaming a specific place.
根据渭河流域关中段11个主要代表气象站点1955~2012年逐日气象数据,以FAO Penman-Monteith 公式得出潜在蒸发量,分析渭河流域关中段潜在蒸发量的时空变化特征。结果表明：① 渭河流域关中段年平均潜在蒸发量在1 073.9~1 284.1 mm,流域内多年平均蒸发量随着海拔的降低逐渐增高。② 夏季潜在蒸发量在327.6~547.2 mm,占全年的34%~42%,变化趋势与全年潜在蒸发量变化趋势高度一致。③ 渭河关中段随气温上升,潜在蒸发量减少。④ 年均潜在蒸发量与日较差、平均气温、平均风速、日照时数呈正相关,与相对湿度和水汽压呈负相关。
Based on the daily data of 11 meteorological stations of Guanzhong area in Weihe River Basin in 1960-2006 and combined with the FAO Penman-Monteith model, spatial and temporal changes of potential evaporation were quantita-tively analyzed in this study, which mainly discussed the reason of the decreasing of potential evaporation. It was showed that potential evapotranspiration in Guanzhong area of Weihe River Basin decreased significantly with the increasing of mean temperature, which is mainly because mean wind speed and sunshine time decreased significantly. The main results are as follows: 1) The annual potential evapotranspiration, gradually increased with the loss of the altitude, which range from 1 073.9 mm to 1 284.1 mm. 2) The potential evapotranspiration in spring range from 195.6 mm to 327 mm, accounted for about 19%-22% of the year, and the potential evapotranspiration in summer range from 327.6 mm to 547.2 mm, accounted for about 34%-42% of the year, which plays a leading role throughout the year. The potential evapotranspiration in autumn and winter is in 250.8-466.2 mm and 115.2-247.8 mm respectively, accounted for 24%-33% and 10%-18%. 3) The evaporation paradox actually existed in the study area, as the mean temperature increased, the potential evapotranspiration generally decreased. Linear trend rate of the potential evapotranspiration is -9.16 mm/10 a during 1955 to 2012, however, at the same time, linear trend rate of the mean temperature is 0.39℃/10 a. 4) Mean annual potential evapotranspiration and the diurnal range, mean temperature, mean wind speed and sunshine duration were positively correlated, and negatively correlated with relative humidity and water vapor pressure. The mean wind speed and sunshine time is the dominating factor leading to the decrease of potential evapotranspiration in the study area.