Table of Content

    20 September 2014, Volume 34 Issue 9 Previous Issue    Next Issue
    Orginal Article
    Spatial Pattern of Chinese Tourism Development Based on Different Spatio-temporal Scales
    Ye-lin FANG, Zhen-fang HUANG, Kun WANG, Bi-fan CAI
    2014, 34 (9):  1025-1032.  doi: 10.13249/j.cnki.sgs.2014.09.1025
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    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.

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    Spatial Pattern and Classification of Human Settlement: A Case Study of Shahekou in Dalian
    Xue-ming LI, Ying-jia ZHANG, Jia-ji GAO
    2014, 34 (9):  1033-1040.  doi: 10.13249/j.cnki.sgs.2014.09.1033
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    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 “danwei”, which caused by historical house allocation policy without free choice. 3) The “homogeneous” agglomeration and “heterogeneous” agglomeration of 5 human settlement types coexist in Dalian Shahekou district. The spatial pattern of “homogeneous” agglomeration is represented by “Ring homogeneous gathering form” meaning three types of human settlement dispersed in three spheres respectively based on the southern coastline as a benchmark, and “homogeneous gathering forms” 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 “heterogeneous” represents by “the insertion into internal spheres” heterogeneous region and “broken and mixed type” 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, “mankind” and “social network”, and the 3 main object subsystems to accelerate or slow down the formation process of human settlement classification and spatial pattern.

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    The Network Structure of Cross-border Tourism Flow Based on the Social Network Method: A Case of Lugu Lake Region
    Hong-song PENG, Lin LU, Xing-fu LU, Shan-jin LING, Zi-ming LI, Hong-bo DENG
    2014, 34 (9):  1041-1050.  doi: 10.13249/j.cnki.sgs.2014.09.1041
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    Innovation Network System of Industry-University-Research Institute of Equipment Manufacturing Industry in the Changjiang River Delta
    Guo-qing LU, Gang ZENG, Jin-long GUO
    2014, 34 (9):  1051-1059.  doi: 10.13249/j.cnki.sgs.2014.09.1051
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    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.

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    Spatio-temporal Pattern Evolution of the Interaction Among the Cities in Central Plains Economic Zone
    Jing-yu LIU, Hu-le YANG, Qiong SONG, Xiao-xia FAN
    2014, 34 (9):  1060-1068.  doi: 10.13249/j.cnki.sgs.2014.09.1060
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    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.

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    New Urbanization Measurement and Spatial Differences in Shandong Province
    Xin-yue WANG, Yang SONG, Fei-hong SONG, Shi-yuan YU
    2014, 34 (9):  1069-1076.  doi: 10.13249/j.cnki.sgs.2014.09.1069
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    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&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&D, and promoting the quality of the new urbanization should be pay more attention to.

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    Development Track and Its Effect of Rural Transformation in Energy Exploitation Area of Northern Shaanxi Province
    Qi WEN, Yan-sui LIU
    2014, 34 (9):  1077-1084.  doi: 10.13249/j.cnki.sgs.2014.09.1077
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    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.

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    The Growth and Distribution of Population in Guangzhou City in 1982-2000
    Chun-shan ZHOU, Yan BIAN
    2014, 34 (9):  1085-1092.  doi: 10.13249/j.cnki.sgs.2014.09.1085
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    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 “peak value single center + small centers outside” 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 “flatten main centers + small centers outside” 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.

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    The Mechanism and The Measurement of Regional Economy′s Spatial Distribution of Xinjiang: Based on the New Economic Geography Theory
    Jin-cun FU, Yu-xin LI
    2014, 34 (9):  1093-1098.  doi: 10.13249/j.cnki.sgs.2014.09.1093
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    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.

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    Forestry Landscape Patterns Changes and Dynamic Simulation of Nanling National Nature Reserve, Guangdong
    Fang-jun LIAO, Dong-sheng ZHAO
    2014, 34 (9):  1099-1107.  doi: 10.13249/j.cnki.sgs.2014.09.1099
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    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.

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    Spatio-temporal Difference of Coupling Coordinative Degree of Ecological Carrying Capacity in the Dongting Lake Region
    Jian-xin XIONG, Duan-lu CHEN, Bao-fa PENG, Su-ting DENG, Xue-mei XIE
    2014, 34 (9):  1108-1116.  doi: 10.13249/j.cnki.sgs.2014.09.1108
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    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.

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    Measurement and Analysis of Impact of Industrial Structure Evolution on Urban Land Intensive Use in Anhui Province in 1996-2011
    Le-qin ZHANG, Su-ping CHEN, Bao-ping CHEN, Fa-kui CHEN
    2014, 34 (9):  1117-1124.  doi: 10.13249/j.cnki.sgs.2014.09.1117
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    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.

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    A Novel Imputation Method of Missing Air Temperature Records Based on Merging Spatio-temporal Characteristics
    Feng-rui CHEN, Yu LIU, Xi LI
    2014, 34 (9):  1125-1133.  doi: 10.13249/j.cnki.sgs.2014.09.1125
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    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.

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    Extreme Precipitation Features of Arid Regions in Northwest of China
    Qi-hu LI, Qing-xun MA
    2014, 34 (9):  1134-1138.  doi: 10.13249/j.cnki.sgs.2014.09.1134
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    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.

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    Spatial and Temporal Change of the Potential Evapotranspiration in Weihe River Basin: A Case Study in Guanzhong Area
    Wen LIU, Ming-ming CAO, Hai-jun QIU, Shuai GUO, Ran LI
    2014, 34 (9):  1145-1152.  doi: 10.13249/j.cnki.sgs.2014.09.1145
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    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.

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