New product promotes the sustainable growth of the local economy. Evolutionary economic geographers believe that the emergence of new products is based on local original products and related industries, saying that the development of new industries demands access to local capability. Local capability is the key source of technological and industrial diversification, which provides potentials for regions to diversify into new technologies and industries. Organizational routines are core concept in an evolutionary approach. Economic evolution can then be understood as the selective transmission of routines among organizational entities. However little attention has yet been paid to the role of spillovers from neighbor regions for industrial diversification. Regions are in an associative network but not absolutely isolated, especially for the neighbor regions. Knowledge spillovers may occur across regions and successful routines may be transferred to neighbor regions by the way of population mobility and spinoff. So this article discusses whether the evolutionary process can cross space and administrative boundaries based on the current evolutionary theories. To answer this question, we analyze the development of new products in Chinese prefecture-level cities during the period 2002-2013 using the HS 4-digit classification data on exports. The results show that the evolution of product can occur across administrative boundaries between neighbor cities, but only when the local has a good foundation of relevant industries. And the decentralization between provinces is a significant barrier for cross-boundary evolution. Besides, taking into account of the different knowledge attributes of products and the regional difference of economic development, there exist significant differences among regions and products in cross-boundary evolutionary mechanisms.
对比中美两国海洋经济总产值（海洋经济增加值）发现, 2011年开始,中国海洋经济总产值（海洋经济增加值）（2 849.73×108美元）,已超过美国海洋经济增加值（2 779.02×108美元）（实际GDP）。重点分析2005~2012年,中国海洋产业超过美国的演进过程,并以两国共同的6个海洋产业部门为例,分析了中国与美国海洋产业发展历程。为了体现中美两国海洋经差异的特征与规律性,应用标准差、变差系数、集中化指数（基尼系数）、锡尔系数等方法,分析了中、美两国在海洋经济总值（海洋经济增加值）、海洋产业与区域海洋经济的差异与特征。
China and the United States are two big marine powers in the world, both of which boast long coastlines, vast waters, and abundant marine resources. The ocean is lifeline supporting coastal development and the thoroughfare leading to the world market. The sea and marine resources in both China and the United States has a very important role in their perspective economic development. Starting in 2011, China's marine economic output (marine economic value added)（2 849.73×108 US＄） surpassed the United States Marine Economic Value Added （2 779.02×108 US＄）(real GDP). This article focuses on the evolution process of China surpassing the United States in the marine industry lasting from 2005 to 2012. Among six marine industry sectors, China started ahead of the US only in one of them, but now the US is stronger than China only in the sector of ocean mining (mainly offshore oil and gas exploration industry). In order to demonstrate the features and patterns of the differences in marine economy between the two countries, standard deviation, coefficient of variation, concentration index (Gini coefficient), Theil indes, to analyze the differences in marine economic output (marine economic value added), marine industry and regional marine economy between the two countries. Taking into account the future development trend of these two marine economies.
基于1997~2010年的全国省级、地级市和县级多尺度社会经济发展数据库,采用GIS与空间统计学相结合方法,揭示了中国经济发展的空间格局及其动态演变特征及时空格局的尺度依赖性,并对未来经济发展空间格局进行合理预测。结果表明：① 1997~2010年中国经济的空间中心位于河南省境内,并呈现出西北移动的趋势,出现沿海-大陆共生的经济空间格局并逐步均衡化。② 经济发展空间格局具有较为显著的尺度效应,其分布重心、形状和方位在不同尺度上发生变化;总体而言,空间尺度越小,其经济重心越偏向西南方向,其空间分布形状越接近于正圆,主轴方位越偏东。③ 预测结果表明未来10~20 a中国经济重心会继续向北移动,略微偏向东部地区,京津冀、长三角等沿海城市群仍是未来中国经济发展的主要增长引擎。研究结果可以为各级政府制定区域发展政策提供科学的理论依据。
The issue of regional inequality has attracted much attention of geographers and economists. The interdisciplinary research has been reflected in a spatio-temporal hierarchical structure, that is, the multi-scalar nature of economic development and its dynamics. With the advent of the new economic geography, the role of space is emphasized in the field of regional science. Spatial pattern and its dynamics provide a significant prospective for understanding regional development in China. Spatial pattern statistics has been adopted to explore the multi-scalar spatial patterns of regional development in China and to investigate the corresponding scaling effect. Especially the forecast of spatial pattern of economic development allows the government to make effective policies. First, the standard ellipse is employed to explore the multi-scalar globe spatial pattern and its dynamics so as to investigate the scaling effect. Second, grey forecast model and Geographic Information System are utilized to predict and visualize the future spatial pattern in 2020 and 2030. The study area is composed of 2 254 county-level units including city districts/counties/county-level cities (not including Hongkong, Macao and Taiwan of China), 333 prefecture-level units and 31 provincial-level units. Major results are listed as follows: 1) Economic gravity in China is situated in Henan Province from 1997 to 2010, accompanied by a shift towards northwestern China, demonstrating co-developing spatial pattern of the coastal and inland regions. It contributes to the effective implementation of western development and rise of central China. Foreign direct investment starts to leave the Zhujiang River Delta and concentrate in Bohai Rim and the Changjiang River Delta. 2) 66% of economic development mainly happens in most eastern and central parts as well as one third of western region. Spatial pattern of economic development shows obvious scaling effect in economic gravity, shape and direction. Overall, the finer the spatial scale, the more southwestern-oriented economic gravity is. Its shape of standard ellipse tends to be circled and its direction is by east. 3) It is forecasted that economic gravity will continue to shift northward and slightly towards the east, indicating Beijing-Tianjin-Hebei and the Changjiang River Delta as the major growth engine for economic development in the future. 4) It has been demonstrated that spatial pattern of regional development has obvious scaling effect. The county level is better to understand the finer spatial structure and spatial laws.
Since the proposition of “Belt and Road Initiative”, researches on trade between China and countries along the Initiative area have increased. However, it is relatively rare to study trade network taking China and those countries as a whole. In this article, we utilize a social network analysis method to analyze the characteristics, trade groups as well as core-periphery structure and its evolution of this trade network. Then we analyze the structure of sub trade network of China and the Southeast Asian countries. The results show that density of the trade network established by China and countries along “Belt and Road Initiative” areas has increased, coupled with growing number of core countries. Meanwhile, China’s core degree in this trade network has increased with China being the most important core country in 2013. What’s more, China becomes the core country in the sub trade network of China and the Southeast Asian countries as well. Based on this analysis, we propose that during the process of promoting “Belt and Road Initiative” construction, China should rely on policy communication to reduce trade barriers and improve trade facilitation with countries along the Initiative area. In particular, it should be set as the priority to facilitate trading conditions with core countries in the Initiative area trade network for further enhancing China’s core position in this network. What’s more, China should make good use of the advantage of being the core position in the network, play an active role of being the area core country and promote the construction and development of “Belt and Road Initiative”.
系统回顾了中国流动人口的省际变动与集疏格局,包括总体特征与演化趋势,基于迁出地和迁入地属性差异的省际流动人口模式以及基于城市规模的流动人口分布特征,采用趋势分析和马尔科夫链方法预测了中国省际流动人口的空间迁移趋势,由此提出了中国流动人口的市民化路径与建议如下：① 人口的跨区域流动重塑着中国的人口空间格局,东部地区应审慎而稳妥地推进市民化;②积极稳妥地推进中西部地区的城镇化进程,重点推进省内流动人口的就近市民化;③ 不同地区要制定不同的政策,因地制宜地推进市民化进程。
Since the reform and open policy, the development of productivity and the institutional change of population policy have a deep influence on the rural labor force which can migrate to the cities when there are no many things can do in the countryside. With the implementation of the new urbanization strategy, it has become a general trend to promote the urbanization and citizenization of floating population. Therefore, it is urgent to discuss the optimal path and promotion idea of citizenization of floating population in China accurately based on the comprehensive review of spatial pattern and difference of floating population in China. In this study, a systematic review on organization structure change and interprovincial population migration have been carried out, including the following aspects: 1) the characteristics and evolution trend of floating population; 2) emigration and immigration model based on provincial differences of the attributes and features; 3) floating population distribution characteristics of floating population based on the city scale; and 4) spatial migration trend has been predicted. Based on these analyze, citizenization path and suggestions have been proposed which can provide references to guide the of population flow according to its classification orderly and form the reasonable layout the floating population in China.
以2000年、2010年人口普查数据和2008年珠江三角洲外来农民工问卷调查为基础数据,以街道为单元,运用数理统计分析和GIS空间技术揭示深圳农民工集聚空间演变特征及其影响机制。研究发现：① 深圳农民工以青年为主体,具有受教育水平高、职业转型模式多样、留城意愿较低和社会空间分异度较高等特征。② 农民工规模呈现西北部最高、中部其次、沿海最低的地带性分布规律,农民工高密度地区主要分布在工业集中区和城市中心区;热点区（高聚集区）集中在西部和北部的宝安区和龙华新区,冷点区（低聚集区）则分布在南部的中心城区,与传统制造业布局相一致。③ 农民工空间演化格局相对稳定,全市农民工分布重心逐步向西北偏移;全市农民工集中度略有上升,热点区基本稳定,冷点区有所扩大;农民工人口密度高值由“1个高中心+1个外围中心”逐步演变为“1个高中心+2个外围中心”;农民工空间变化差异较大,增长演变类型呈多样化。④ 深圳农民工分布的时空演变特征与常住人口存在较为明显的差异。⑤ 农民工集聚空间的分布演变受住房因素、就业机会、交通条件、社会网络、城市规划共同影响。
Based on the fifth and sixth census and the question survey of migrant workers in the Zhujiang River Delta in 2008, and using the methods of mathematical statistics analysis and GIS spatial analysis, this article attempts to bring out a systematic understanding of migrant workers in Shenzhen, including their social-economical features, spatial distributions, spatio-temporal changes and the factors that lie behind such changes. And five discoveries have been made through this study. First, the majority of the migrant workers in Shenzhen are well-educated youngsters with diverse vocational transformations, low willingness to live there as a city dweller, and high level of segregation. Second, the distribution of migrant workers in the city is characterized by a high degree of regularity. The density is highest in the northwest part, diminishes in the central area, and is lowest in the coastal regions. High density regions are found to be around the downtown areas and industrial concentration areas. “Hot zones”, i.e. high density areas, lie mainly in the district of Baoan and Longhua, which are in the western and northern part of the city respectively, while “cold zones”, i.e. low density areas, are around the downtown areas in the southern part of the city, which is also the place where traditional manufacturing industries are located. Third, the change in the spatial distribution of migrant workers has been stable over the years. In addition to the slight growth in their density among the whole population of the city, their concentration has been shifting towards the northwestern part. While “hot zones” remain almost unchanged, “cold zones” have extended a little bit. The spatial distribution of their population density is changed from “1 high center + 1 peripheral center” to “1 high center + 2 peripheral centers”. In so far as different blocks are concerned, the change in their spatial distribution, together with the type of growth in their total number, varies greatly. Fourth, migrant workers differ sharply from permanent residents in the change of temporal and spatial distribution. Fifth, the factors that lie behind such changes, according to the order of importance, are housing and employment, traffic conditions and social networks, and urban planning.
基于春运人口流动大数据,选取对外联系度、优势流、城市位序-规模分析等方法对转型期中国城市网络特征进行分析。结果显示：① 城市网络层级结构中蕴藏着位序-规模规律,但与理想的帕累托分布有所区别,城市规模彼此差异相对较小;② 空间距离与城市等级在城市网络联系中发挥支配性作用,保证了城市网络的层级性与有序性;③ 中国城市网络核心联系呈现“两横三纵”特征,该特征与铁路大动脉的空间分布高度吻合;④ 东部地区城市网络联系更加密切,而西北、西南地区则相对稀疏,基本上以“胡焕庸线”为界,而“兰新线”是突破这一限制的潜在力量;⑤ 中国东北地区未形成明显的区域性中心,城市联系形成带状网络;⑥ 华北与华南地区的“灯下黑”现象值得警惕,缓解这一问题的可行办法是核心城市功能的对外疏散,加强核心城市与周边城市之间的联系;⑦ 带状区域发展或许将成为未来中国区域经济发展的流行模式和中坚力量。总体上看,针对于揭示转型期中国城市网络结构特征,春运人口流动数据具有一定的研究价值,是城市与人口研究领域一个值得深入挖掘的重要数据源。
The space of flows theory proposed by Manuel Castells has given birth to the network perspective of city network. In contrast with the traditional perspective of urban system which is based on the central place theory, city network perspective pays more attention to the interactions and linkages between cities and regions. Thus, the city network is becoming one of the new and hot topics in the field of urban geography. “Chunyun” is a well-known socio-economic phenomenon unique to transitional China, which refers to a blooming of population flows during the Spring Festival, or refers to the period when the blooming happens. Previously, the real population flows data in “Chunyun” were difficult to obtain. The situation had not changed until the “Big data on human migration during the spring festival from Baidu map” (“Baidu migration data” in short) came up. The big data were gathered from the locations provided by hundreds of millions smart phone users through Location Based Service (LBS) Baidu map data source, and was published in the form of interactive heat map that displays people’s travel routes in China during the Chunyun period. Based on Baidu migration data, using degree of external linkages, dominant flows and network-based rank-size analysis, the spatial pattern of city network in transitional China was studied in this article. The study process certificates that Baidu migration data is indeed a high quality data sources for the study of city network, and has turned up some interesting results: 1) The distribution of external linkage degree of cities in China follows Zipf’s law, but differs from the ideal Pareto distribution. 2) The factor of spatial distance and city level play key roles in the formation of urban network of China, and ensure the hierarchy and regularity of the network. 3) The spatial distribution of core linkages in the city network could be summarized as “Three-horizontal & Two-longitudinal”, which almost coincides with the rail arteries in China. The “Three-horizontal & Two-longitudinal” linkages are skeletons of the city network, which matter a great deal in building the interregional contact and coordinating the interregional relationship. 4) In overall, the strength of interactions within the city network differs between East and West China, and Hu's line is apparently the dividing line. As potential powers, the linkages along the Lanzhou-Xinjiang railway line have the opportunity to break the Hu's line. 5) Northeast China lacks regional centers and the linkages between cities forms a bunchy network. 6) There is a phenomenon of “near field deprivation” in North China and South China, that is, the core city have strong interactions with outer regions, but the smaller cities in its near field have poor external linkages with the core city and outer regions. 7) Belt-shaped region may become a popular mode and the future backbone of regional economic development in China.
In order to explore effects of urbanization on energy consumption in China, the Spatial Dubin Model is used to analyze the influence of urbanization on energy intensity according to panel data in 2000-2012. After the spatial spillover effect is estimated, the total effects are decomposed to direct effects and indirect effects by partial differentiation. Results show that urbanization is an importance factor on the increase of energy intensity and the influence indicate obvious difference among three regions. Indirect effects of urbanization influencing energy intensity are significantly positive for all provinces. But direct effects are not obvious and present different patterns among three regions. Then theoretical mechanism of urbanization influencing energy consumption is analyzed. The influence of urbanization on energy consumption is the combined action of scale effects, technology effects, structure effects, stage effects and spatial effects. The direct effects of urbanization affecting energy consumption are the result of scale effects, technological effects, structural effects and stage effects, including direct and indirect paths. The indirect effects of urbanization affecting energy consumption are mainly derived from spillover effects between the regions. The results of this article show that urbanization plays an important role in the growth of energy consumption. Nowadays, Chinese government is accelerating the pace of urbanization, which may need more energy demand. Thus, studying the relationship between urbanization and energy consumption is very important to draw up urbanization planning and energy policy. Some recommendations are put forward to promote economic transformation and upgrading, accelerate the construction of ecological civilization. The following research will pay more attention to the nonlinear effects of urbanization on energy intensity and the effects of different types of city on energy consumption, which can provide constructing suggestions for government policy.
在生态文明建设与服务经济转型的背景下,作为中国工业化阶段能源基地的资源型城市,正面临着经济、社会与生态环境多位一体的全面转型。选取成熟型煤炭资源城市淮南为案例,基于社会空间视角划分城市地域功能结构,构建社会-经济-空间多维因素的互动框架推进资源型城市的科学转型。研究发现：淮南市社会空间包括6个主因子,各主因子的空间集聚和街区分布均具有显著的异质性。基于不同街区的功能属性划分出5个空间功能组团,包括：政府机关、企事业单位组团;居住、商业、生活服务组团; 煤炭开采与加工工业组团; 非矿点区域、乡村区域组团;经济新增长点培育、转型发展组团。城市地域功能结构特征表现为：① “城”、“矿”功能的隔离与排斥,② 连绵型低收入农业空间的嵌入,③ 城市服务功能空间的紧缩,④ 煤炭开采与初加工的空间共位,⑤城市转型尚未形成规模与联动效应。在此基础上,进一步剖析了地域结构的形成原因及优化路径。
China has undergone a rapidly increasing service economy growth over the past decades. In the context of ecological civilization construction and service economy transition, resource-based cities which functioned as the energy base in the stage of Chinese modern industrialization are facing the economic, social, and ecological comprehensive transformation. This article takes Huainan City as an example of coal resource-based city in mature period. To promote the scientific transition of resource-based cities, we take on to set up the urban area functional structure of Huainan from the perspective of social space. We try to build an interactive frame including multidimensional factors such as economy, society, and space. This research points out the social space of Huainan contains six principal factors. The cluster and block distribution characters of each principal factor are significantly heterogeneous. It maps out five spatial functional groups based on the features of each block, field surveys, and relevant document literature. The first group is government agencies, enterprises, and public institutions. The second group is housing, commerce, and consumer services. The third group is coal mining and processing industries. The fourth group is non-mining areas and rural areas. The fifth group is urban economy new developing points and transitional development. Further, it summarizes the urban area functional structure as five respects: 1) segregation and exclusion of urban areas and mining areas; 2) embeddedness of continuous low-paying agricultural areas; 3) compression of the space of urban service role; 4) co-location of coal mining and preliminary processing areas, and 5) scale effects and connected effects of urban transition, not formed yet. In addition, we further analyze both the formation reasons and ideal paths of the urban area functional structure.
基于非负张量分解方法(NTF方法),依托 2004年1月至2012年12月江苏省高速公路网络的三维OD海量交通流数据,展开网络时空特征的解析、提取与挖掘,尝试解决现有数据分析方法无法有效解析交通流网络时空演化的动态性与多维性问题。结果表明：① 重构网络对原始网络的空间构型与格局具有很好的重现能力,基本刻画了原始网络的倒“不”字型空间结构;② 分解的网络可提取出基本不变型、渐变型和突变型3类时变规律,且每类时间特征有各自耦合对应的局部空间格局,体现内在组织的时空统一性;③ 倒“不”字型空间结构由分解的沿沪宁线横向子网络叠加过润扬大桥沿扬溧线、过江阴大桥沿京沪线和过苏通大桥沿沈海线的三大纵向子网络等具有明确地理含义的多个局部空间系统共同构成,体现全局由局部组成的特性。
The present researches on the spatio-temporal characteristics of the evolution of traffic flow network have paid less attention to the high-dimensional features and dynamic features. This article aims to analyze the spatio-temporal structure of expressway traffic network in Jiangsu base on the decomposition and reconstruction of the non-negative tensor factorization (NTF) method, and supported by a three-dimension matrix of “Origin-Destination-Time”, which consists of expressway traffic flow between 59 counties and time-evolving series from January 2004 to December 2012. The conclusions can be drawn as follows: 1) The reconstructed network has a good ability to reproduce the spatial construction and network pattern of original network. The spatial structure of both reconstructed network and original network are depicting a reverse “不” structure. 2) With the NTF method, there are three time-varying patterns at the study period which are essentially immutable pattern, gradually rising gradual pattern and rapidly rising mutational pattern. Each time-varying pattern has its own coupling and corresponding local spatial pattern respectively, which reflects the internal organization of spatio-temporal unity. 3) The reversed “不” spatial structure of the origin network consists of four clear geographical meaning systems. The Shanghai-Nanjing expressway connecting network acts as the horizontal axis of reversed “不” structure, the Jiangyin Changjiang River Highway Bridge along Beijing-Shanghai expressway connecting network acts as a vertical axis of reversed “不” structure, the Sutong Changjiang River Highway Bridge along Shenyang-Haikou expressway acts as the other vertical axis of reversed “不” structure, and the Runyang Changjiang River Highway Bridge acts as the last vertical axis of reversed “不” structure. The analysis reveals that each system is a local mode of the whole spatio-temporal network.
Ocean is an important factor affecting the development mode and the city spirit of the coastal cities, and also has strong influence on people’s regional identity. Based on explaining the definition of the coastal cities Maritime Characteristics, this article has summed up 13 influencing factors of coastal cities Maritime Characteristics. Furthermore, this article has analyzed qualitatively the progressive relationship between these factors using Interpretative Structural Modeling (ISM) on the basis of the degree of how directly these factors impact on regional identity. The results show that the ocean landscape, ocean-related employment, marine employment and marine products and services consumption have mostly impacted on coastal cities regional identity .Marine culture and marine industry production serves as a connecting link between the preceding and the following. Other factors are the basic elements of the system. According to the results, this article has constructed an evaluation system of coastal cities Maritime Characteristics. Evaluate and sort the seven typical coastal cities in China useing fuzzy comprehensive evaluation method. The results showed that Dalian > Ningbo > Shanghai > Xiamen > Tianjin > Shenzhen. Through the analysis and evaluation, this article hopes to provide a reference for the construction of Maritime Characteristics in our coastal cities, and give a preliminary study for the discussion of “Marine City” conception.
Evaluation of efficiency of regional tourism cooperation is an important way to reveal the current state, degree and level of tourism cooperation. It is useful to promote regional tourism cooperation through efficiency evaluation. This article analyzes tourism cooperation efficiency and constructs the evaluation model for regional tourism cooperation underpinned by structure of transportation network. Then, using the methods of comprehensive evaluation and analytic hierarchy process from three dimensions, the transport network density, accessibility and traffic network, this article takes an empirical analysis on the tourism cooperation efficiency from two perspective of time and space. The results show that the gap of efficiency of regional tourism cooperation in the western Hunan has arisen from 0.07 in 2004 to 0.75 in 2014 resulting from improved transport network. Efficiency of regional tourism cooperation within the western Hunan varies from regions. There is a coordinated relationship between efficiency of regional tourism cooperation and density of transport network or advantage of transport network arising from regional economic development level, traffic network conditions and its spatial layout. The gap of tourism cooperation efficiency of different prefecture region increased from 0.03 in 2004 to 0.21 in 2014. They are different in quality of traffic, degree of transport facilities and accessibility of transport. These inputs of transport affect investment of productive factor and allocation of resource, which lead to different level of tourism cooperation efficiency. It need to intensify construction of transportation network, continuously improve the quality of traffic construction and utilization rate, and optimize the structure of transportation network layout, for improving the efficiency of regional tourism cooperation.
选取山东省具有代表性的104处乡村休闲旅游地作为研究样本,运用最邻近点指数、地理集中指数、地理联系率、核密度等方法研究乡村休闲旅游地的分布规律及影响因素。结果表明：① 山东省乡村休闲旅游地类型丰富,可以划分为休闲观光类、农事体验类、农业科技类、乡村文化类、特色村镇类5个一级类型,农业观光示范园、自然风景区等17个二级类型;② 山东省乡村休闲旅游地整体空间分布趋于集聚,空间结构属于凝聚型;③ 五大类型中特色村镇类和乡村文化类集聚程度高,休闲观光类和农业科技类数量多、布局分散;④ 经济基础、资源禀赋、人口密度、交通区位是影响乡村休闲旅游地分布的主要因素。
With the development of urbanization and the improvement of living standard, the rural tourism has become more and more popular. The article constructs the classification system of rural leisure tourism destinations, and selects 104 representative rural leisure tourism destinations in Shandong Province as the research sample. The article explores the distribution pattern of rural leisure tourism destinations and studies the factors affecting the distribution of rural leisure tourism destinations by the methods of the nearest point index, geographic concentration index, geographical connection rate, nuclear density and so on. The conclusions are as follows: 1) There are 5 primary types of rural leisure tourism destinations in Shandong Province, respectively as follows: leisure tourism, farming experience, agricultural technology, rural culture and characteristic village, and 17 second-stage classes; 2) The distribution type of rural leisure tourism destinations in Shandong Province is agglomeration on the geographic space; 3) The species about leisure tourism and agricultural technology have a large number, and their layout is scattered, however, the rural culture and characteristic village tourist destinations have a high concentration. 4) The distribution of rural leisure tourism destinations are influenced by economic foundation, resource endowment, population density, traffic location and so forth. Economic basis is the important condition of tourism activities, it can influence the spatial distribution of rural leisure tourism destinations and their evolution, different levels of economic regions have different types of rural leisure tourism destinations, for instance,the tourism destinations of farming experience class mainly distribute in developed and less developed areas, the scenic spots about agricultural technology and rural culture always distribute in middle-income region, characteristic villages mainly distribute in developed areas, the distribution of leisure tourism destinations have the characteristic of equilibrium. The development of rural leisure tourism destinations should strengthen the cooperation among different economic regions, in order to make their respective advantages complementary to each other. There are strong correlation between the distribution of rural leisure tourism destinations and the distribution of famous scenic spots. Once the rural leisure tourism destinations distribute around the edge of the scenic spots, they can take advantage of the scenic spots. The distribution of rural leisure tourism destinations have a strong dependence on dense populated areas, leisure tourism is an obvious class. The distribution of rural leisure tourism destinations has great correlation with transportation network, and farming experience, rural culture and characteristic town show stronger dependence obviously. Purpose of this article is that giving the government of Shandong Province some reasonable advices in the construction of rural leisure tourism destinations. The rural leisure tourism destinations will play important roles in the process of building a new socialist rural and beautiful countryside in the near future.
Tourist satisfaction is the core concept of tourism management and tourism research. As this concept is introduced from the American Customer Satisfaction Index (ACSI) in business discipline, which can be summarized as the “Expectations-Value-Quality” theory. ACSI’s suitability, especially its antecedents section, in tourism discipline is questioned in this article. The definition of the traditional tourist satisfaction and its according assessment have fallen into a serious risk of simplicity. This article points out that it needs to put tourism in its place, which is a characteristic human-land phenomenon, while not to put tourism just in business. The tourist satisfaction of a specific tourist place requires a specific index system. The positive research on the Ancient Waterfront Towns in the south of the Changjiang River, demonstrates that we should put tourist satisfaction in the specific tourist place. The index system of the positive research is made up of 5 dimensions, i.e., the heritage value dimension, the tourist function dimension, the psychological satisfaction dimension, the place environment dimension, and the negative evaluation dimension. The casual relationships among the 5 dimensions and the dependent variable—tourist satisfaction, are exploited with the partial least-squares regression. As for the specific case of the Ancient Waterfront Towns in the south of the Changjiang River, the descending order of the 5 dimensions’ relative importance is as follows: the heritage value dimension, the place environment dimension, the tourist function dimension, the place environment dimension, and the negative evaluation dimension.
On the basis of the geostatistical method and in combination with GIS technology, a research is being carried out on space distribution pattern and spatial correlation of regional tourist scenic spots in the very paper, with South Anhui international cultural tourism demonstration area as the studying sample. In the first place, it has calculated the semivariogram of the number of tourists in the tourist attractions which have been under monitor from 2009 to 2014 with the help of statistical data, so that a semivariogram model has been matched. After that, it starts to interpolate spatial data in it and draws the Kringing maps on number of tourists to the scenic spots in accordance with the optimal semivariogram model which has been matched. In the end, an analysis is done in the paper on the semivariogram and the kringing maps on the number of tourists to scenic spots in different specific years. In the light of the results coming from the above analysis, there exists a significant spatial correlation between the east part and the west part of South Anhui international cultural tourism demonstration area. In the initial stage, it appeared a clustering distribution in the area, while the spatial heterogeneity being mainly affected by random factors which gradually have become weaker and weaker over time. On the whole, though the spatial level difference of the demonstration area is not significant, the "two mountains and one lake" area remains the core tourism sector and guides the development of regional tourism tend to be closer to it. From the perspective of locality, with Fangte Theme Park as the main sector, the Northeast area has a tendency to become a demonstration zone portal and the attractions around the Huangshan Mountain are closely linked together in space. However, Anqing City has not fully been integrated into the tourism development pattern of the demonstration area with distance as the major possible influencing factor. In summary, the research on South Anhui international cultural tourism demonstration area space structure on the basis of the geostatistics method, on the one hand, may help all scenic spots to get their correct identification in the demonstration area, to make a competitive analysis, and to design a suitable marketing strategy for them, so as to increase mutual association driving effect among them; on the other hand, it may offer a macro guidance on spatial structure adjustment in the demonstration area, to integrate all scenic spots within the region, to provide a reference for tourism development direction and trend in the demonstration area.
以中国展览业为例,立足于展览业和区域经济发展的空间分布特征,使用Moran’s I和Moran’s I散点图阐释展览业与区域经济之间的空间自相关性,分析纳入空间因素的空间计量经济模型相对于经典回归模型的优越程度,进而揭示展览业发展对区域经济的空间溢出效应。研究结果显示：① 中国展览业发展和区域经济水平在地理空间上分布都不均衡;② 展览业及区域经济皆呈现高高聚集（HH）、低低聚集（LL）两种空间聚集格局;③ 现阶段,中国展馆规模与区域经济之间存在正相关关系;④ SLM优于经典回归模型,展览业发展对区域经济存在显著的空间溢出效应,在展览经济预测研究中充分考虑区域经济增长过程中的空间效应十分必要。
This article took the exhibition industry in China as an example to reveal the spatial distribution characteristics of exhibition industry and economic development level. It also measured the spatial correlation of exhibition industry and regional economic development level with Moran’s I index and its scatter plot. After the observation of spatial correlation, this article constructed a spatial econometric model, then, on this basis, explored the model’s merit compared with classical regression model to indicate the spatial spillover effects. The results showed that: 1) regional exhibition industry and economic development level are seriously imbalanced between east and west China; 2) exhibition industry and economic development level show a strong positive spatial autocorrelation and strong spatial correlation between each other, especially, high-high correlation and low-low correlation obtained; 3) at the present stage, the number and the size of exhibition centers do have a positive relationship with economic development level, but the relationship between the factors of exhibition scale and economy are most significant; 4) SLM has higher explanatory ability than classical regression model,and exhibition industry have significant spatial spillover effect in the regional economy. It implied that considering space factors in events’ economic impact assessment model is necessary.
科学界定都市圈范围是研究都市圈的基础,采用2014年沈阳市及周边市县镇乡社会经济统计数据,采用断裂点和经济隶属度模型,界定沈阳都市圈范围。用经济隶属度指标划分城镇体系。用分形理论分析沈阳都市圈城镇的空间分布特征,结果为：集聚维数、容量维数、信息维数和关系维数分别为1.430 1、1.294 1、1.473 5和0.393 8,说明沈阳都市圈城镇空间向心性集聚分布较为显著,城镇空间分布的均衡性较好,城镇空间分布具有较强的相关性,形成了以沈阳市为中心呈凝聚态分布的都市圈城镇空间结构,城镇间联系较为紧密,相互作用较强。进而提出沈阳都市圈城镇空间分布优化的对策。
：Metropolitan area is a developing stage of the urbanization of modern metropolis which is a kind of organization spatial form of metropolitan area. Defining metropolitan area spatial scale scientifically is the fundamental of researching on metropolitan region reasonably. This article is based on the villages and towns’ statistical data of Shenyang Metropolitan Area in 2014, referring to the domestic and foreign urban metropolitan area related definition method, using breaking-point theory and economic membership degree model, taking villages and towns as defining unit, using the economic distance, urban field intensity, the intensity of economic links and membership degree index to calculate and determine the geographic area and spatial structure of Shenyang Metropolitan Area from the perspective of daily life cycle. The results show that: It take Shenyang urban area as the core of Shenyang Metropolitan Area, which is urban compact districts with social economic ties of neighboring villages and towns district area constitute the regional spatially close to each other, the function in collaboration with each other, form the structural, has the integration trend of urban concentration areas. The urban system of Shenyang Metropolitan Area is divided by economic membership index. The urban system of Shenyang Metropolitan Area has non scaling property and has fractal feature. It quantitative analysis the characteristics of centrality, equilibrium and correlation and reflects the distribution of cities and towns of Shenyang Metropolitan Area and its aggregation dimension, capacity dimension, information dimension and correlation dimension are 1.430 1, 1.294 1, 1.473 5 and 0.393 8. It shows that the towns of Shenyang Metropolitan Area have obvious centripetal agglomeration characteristics, cities and towns abounding Shenyang City presenting a cluster state, and performance the law of reducing the density of the central city to the surrounding and the primacy ratio is obvious, Shenyang City effecting on surrounding cities and towns strongly; Towns of Shenyang Metropolitan Area has better spatial distribution and the cities and towns are more concentrated and balanced in the southwest and more concentrated equilibrium distribution in the northwest and southeast; Towns of Shenyang Metropolitan Area has better correlation and urban and transportation networks more developed and have strongly connection and interrelation. The urban spatial structure of Metropolitan Area have formed Shenyang City as the center of the urban circle of urban spatial structure. Shenyang Metropolitan Area is still in the stage of low level polarization and some suggestions on how to optimize urban spatial distribution of Shenyang Metropolitan Area are proposed. The definition of geographic area of Shenyang Metropolitan Area which provides a theoretical method and reference basis of Shenyang City play a leading role in the process of regional economic development in further.
Residential area is important hazard-bearing body of earthquake disasters. Accurate grasp of the spatial distribution of residential area is an important basis for understanding the earthquake disaster and carrying out the earthquake emergency preparedness. Residential area are changing faster and faster in recent years, the development of remote sensing technology provides advanced means for acquisition spatial information of residential area. The spatial distribution of the real residential area extracted by remote sensing can provide a new data for earthquake emergency preparedness. At the same time, when large destructive earthquake happens, we can rapid determine buried areas and rescue mode according to residential area of quantitative classification result, which has a certain guiding significance on the rescue and evacuation plans. In this article, we use gray level co-occurrence matrix and mathematical morphology methods to extract the spatial distribution of residential area from the 2 m resolution GF-1 satellite remote sensing data, and use visual interpretation, image analysis, buffer analysis to carry out residential area quantitative classification, which can provide data support for the earthquake emergency preparedness. Due to the different earthquake intensity, population distribution and the different types of building structures, the number of buried person in different regions is also different. The residential areas are divided into multi-storey residential areas and bungalow residential areas using visual interpretation, the number of houses is interpretated according to the image characteristic as residential areas attribute data, then the residential areas of buried person distribution are graded through analysis. At the same time, in traffic as the research object, different grade of roads has different road accessibility. We do buffer analysis with different effects ranges for state roads, provincial roads, county roads, township roads and special roads in study area, then the residential areas of rescue convenience degree are graded according to different regional values. The residential areas are divided into four grades, such as first level traffic conditions residential areas, second level traffic conditions residential areas, third traffic conditions residential areas and fourth level traffic conditions residential areas. The results revealed that: Using gray level co-occurrence matrix and mathematical morphology methods can better extract the residential area information of the high resolution GF-1 2 m image. The algorithm of this article has high accuracy and good robustness. However, to ensure data accuracy, extraction results and images were compared and analyzed, and residential areas were extracted semi automatically by the artificial intervention. The quantitative analysis of the residential area revealed that in seismic intensity VIII and the following area, buried zone mainly concentrated in the bungalow areas; When the seismic intensity is higher than VIII degrees and caused large area multi-storey buildings collapsed, densely populated areas of the county are the main rescue areas; In the earthquake emergency preparedness, we should increase the reserve point of emergency supplies especially in the third and fourth level traffic conditions residential areas. At the same time, the mountain residential areas should be considered to converse the rescue methods and do a good job in the emergency plan in the case of road damage.
选取黑龙江省鹤山农场面积为0.91 km2的典型黑土区的坡耕地作为研究样地。按横纵100 m间隔共采集101个样点,运用地理信息系统和地统计学相结合的方法研究分析0~15 cm土层有机质空间变异及其与土壤侵蚀的关系。结果表明：位于典型黑土区样地的有机质含量集中在3%~5%范围内,均值为4.13%,高于黑龙江省的有机质平均水平。有机质含量空间变异明显,且主要受土壤侵蚀的影响：高侵蚀区对应低有机质区,中度侵蚀区对应中等有机质区,沉积区对应高有机质区。顺坡种植平均坡度2.2°时,每侵蚀1 000 t/km2土壤,有机质含量降低0.8%。土壤有机质空间变异可采用球状模型表达,自相关明显,进一步表明土壤侵蚀导致的再分布。对比分析确定200 m采样间距能够能准确表达该区表层有机质含量的空间特征,为精准施肥提供了采样依据。
In order to promote the management of soil fertility and precision agriculture effectively, provide some guidance for the soil and water conservation. A sloping cropland (0.91 km2) located in Heshan farm in Heilongjiang Province was selected as the research area,101 samples were collected by vertical and horizontal 100 m interval, for the study of spatial distribution of soil organic matter of the 0-15 cm top layer soil and the relation with soil erosion by the GIS and geostatistics math methods. The results showed that the average content of soil organic matter in typical black soil area was 4.13%, higher than the average level of Heilongjiang Province, and the proportion of organic matter content concentrated in the 3%-5%. Spatial variability of organic matter significantly which was mainly affected by soil erosion. High erosion area corresponds to low organic matter, erosion area in the corresponding medium organic matter content areas and sedimentary areas correspond to areas with high organic matter content. When the slope planted with an average gradient of 2.2°, per 1 000 t/km2 soil erosion increased, accompanied with the content of organic matter will be reduced by 0.8%. The spatial variability of organic matter could be described by the spherical model, showed significantly spatial autocorrelation, further suggested that soil erosion causes the redistribution of soil organic matter. When the sampling interval is 200 m which based on the range, the interpolation of spatial distribution can accurately reflect spatial variability of organic matter content, to provide precision fertilizer sampling basis.
以哈尔滨市为例,基于2001年、2004年、2008年和2015年夏季Landsat TM 5 /OLI 8遥感影像为基础数据源,采用“单窗算法”遥感技术手段定量反演瞬时地表温度格局,并深入分析温度特征,分区差异和重心变化。研究表明：2001~2015年研究区温度增加1.44℃,平均温年增0.10℃,3时段（2001~2004年、2005~2008年、2009~2015年）年均温分别增加0.08℃、0.09℃、0.12℃,具有加速上升趋势;最高温增加2.74℃,始终位于香坊区,最低温基本恒定,始终位于道里区;2001~2015年极高、高、极低温度分区面积增加4.92 km2、104.07 km2、87.71 km2,年均增量均具有持续增加趋势,中、低分区面积减少110.61 km2、84.94 km2,具有波动降低趋势,极高、高、中、低分区格局总体按照城区-城乡结合地区-乡村的水平梯度扩展;地表温度重心向东偏南70.58°方向移动536.90 m,其中6个市辖区迁移方向和距离差异明显,表明地表能量移动方向和温度重新分布的活跃程度不同。总体来看,研究区地表温度上升明显,分区时空变化剧烈,能量的轨迹移动过程具有折返特征。
As a rapid urbanization region in Northeast China, Harbin City has experienced dramatic urban expansion in recent decades, followed by increased urban heat island (UHI) effects. In order to explore the UHI effects under such a rapid urbanization process, the mono-window algorithm and Landsat images was used to retrieve land surface temperature (LST) in Harbin City in summer of 2001, 2004, 2008, and 2015. We then analyzed general characteristics and regional discrepancies of urban heat effects as well as the trajectory of urban heat gravity center in the period. The results showed that: 1) the highest LST occurred in Xiangfang District and increased by 2.74℃ with an accelerated speed from 39.15℃ in 2001 to 41.89℃ in 2015; While the lowest temperature occurred in Daoli District and hardly changed (around 23.18℃). The average increment of LST was 0.10℃, specifically 0.08℃ during 2001-2004, 0.09℃ during 2005-2008, and 0.12℃ during 2009-2015 which showed increased warming rates. 2) The areas in the extremely high temperature, high temperature, and lowest temperature zones increased by 4.92 km2 and 104.07 km2 and 87.71 km2, respectively, with increasing speeds; While the medium temperature and low temperature zones decreased by 110.61 km2 and 84.94 km2 respectively. The extremely high temperature, high temperature, medium temperature and low temperature zones showed ring-structure from inside urban area, to suburb fringe area, to rural area in the outside. 3) Gravity center of LST moved by 536.9 meters to the south by east from 2001 to 2015; The diverse distances and directions in the gravity center trajectories showed different urban heat patterns in the six districts. In sum, the UHI effects in Harbin enhanced from 2001 to 2015, despite different levels of surface energy changes in varied districts.