This article took 31 provinces in China as the objects of study, and made analysis of the current situation of the flux of coal resources flow in every province. It ruled that all provinces which have output coal were classified as source regions, and all provinces which have input coal were classified as sink regions. In analyses, this article led into the concept of gravity centre, and next identified gravity centers of coal source regions and sink regions in 1991-2010, and finally exported space tracking maps of gravity centre points by GIS. The dynamic changes and evolution laws of gravity centers of coal source regions and sink regions were elaborated in the recent 20 years from four aspects, and the study results reflected the spatial development trends and directions of coal resources flow. The first aspect was the whole trends of coal resources flow of source regions and sink regions. The second aspect was the moving trends in longitude and latitude. The third aspect was the space length between gravity center of source regions and gravity center of sink regions in the same year and the fourth aspect was the average flow direction. In addition, statistical maps were used to investigate the characteristics of the spatial structure and dynamic evolution of coal resources flow of source regions and sink regions. And this article used a double of statistical indicators called standard deviation and variation coefficient which respectively reflected absolute and relative differences to investigate the different degrees and development trends of coal flux of source regions and sink regions from temporal series. It also revealed an imbalance of coal resources flow of source regions and sink regions from space perspective. Study results showed that gravity centers of coal source regions were mainly situated in the eastern part of Shanxi Province, and their mobile trajectory were generally rendered "u" type. However, gravity centers of coal sink regions diverted from Jiangsu to Anhui and then to Shandong, and their trajectory were generally rendered northeast-southwest "1" type. Both trajectories in longitude have emerged as a trend of slowly shifting to west. In latitude, gravity centers of coal source regions went through a transfer from north to south and then to north and gravity centers of coal sink regions notably showed a trend of moving to south in fluctuation. There was a clear separation in space between coal production space and demand space. The coal supply bases of China were mainly located in the north of the country, which formed some large output source regions and formed a certain hierarchy. The coal sink regions were mainly in the east of the line of Inner Mongolia, Shanxi, Chongqing and Guizhou, and the space structure showed a trend moving toward southwest. It was obvious that coal source regions were increasingly keeping away from sink regions. The overall of source regions and sink regions was moving toward three directions composed of northwest, southwest, and southeast. The absolute difference of coal source regions was growing and their relative difference was reducing. The absolute and relative differences of coal sink regions all had no big fluctuation.
Regionalization is the important research content in geography. Tourism regionalization is one of the foundations of the development of tourism in a country or region,and has important influence on and significance to the development of regional tourism. The research on scenic spots in the macro tourism regionalization,in essence,is the study of the relationships between tourism destinations and tourists. The A-grade scenic spot is a tourist ranking classifiable system with Chinese characteristics and is a national standard of comprehensive evaluation about scenic spot quality and grade in China. In this article,according to the geographical location and transportation accessibility of scenic spots, the tourism regionalization is studied based on pattern of accessibility. Based on matrix raster data covering the whole space,this article calculates spatial accessibility of all scenic spots in China using cost weighted distance method and ArcGIS as platforms. Service range of A -grade scenic spots is also calculated by using Cost Allocation method. Based on location of scenic spots,transportation accessibility and deep analysis of tourist districts distribution pattern,the service zones are divided by setting the control time,merging up grade by grade,9 first-grade tourist zones,22 second zones and 177 third-grade ones are divided across the country,a hierarchy of tourism division in China is formed. The results showed that the regional average accessibility of scenic spots is about 129.16 minutes,and the area where the accessibility of scenic spots is within 120 minutes reaches 60%,while the area where the accessibility is within 0.5 hour accounts for more than 26% and the longest time needs 75 hours which is located at the core of Tibetan Plateau. The tourism regionalization of the result,which break the administrative boundaries,is more scientific,objective and quantitative. It provided a guideline and basis for further research of the development and utilization of tourism resources.
In recent years, with the continuous development of ports, competition is more and more fierce, and the phenomenon of hinterland overlapping becomes more serious. It is very essential for a port to clearly determine the range of hinterland it can attract. This will also be of great significance for future development of both the port and its hinterlands. However, there are some limitations in the existing port hinterland segmentation methods. These limitations lead that achieving an accurate and detailed segmentation of port hinterland become almost impossible by using these methods. And it is not conducive for the port to determine the direction of its development. Based on summarizing the weak points of existing methods, with the introduction of plume model, this article proposed a new method for partitioning port hinterlands——hinterland plume model. Then this new method was applied to dividing Northeast China into each hinterland scope of the six ports in Liaoning Province. The results show that: The hinterlands of Yingkou Port are Anshan, Liaoyang, Benxi, Tieling, Fushun, Liaoyuan, Siping, Jilin and Changchun. Shenyang and Tongliao are hinterlands of Panjin Port. The hinterlands of Jinzhou Port are Fuxin, Chaoyang and Chifeng. Tonghua and Baishan are hinterlands of Dandong Port. Finally, the remaining cities in Northeast China are hinterlands of Dalian Port.
with the help of key indexes and market analysis methods, such as distribution center, administrative ownership, transport accessibility, spatial fragmentation, time cost matrix and the optimal market selections, the centrality, the center function, the distribution center and the reachable domain of service markets of national historical cities were studied based on its spatial pattern of 119 national historical cities. The results indicated that the different characteristics and central influences of national historic city existed compared with the other cities. Firstly, because of the restriction of the ownership at the county level and the prefecture level, the developing distribution of national historical cities showed discrete characteristics in large scope while gathering landscape form in small range of area. What is more, the distribution center of national historical cities at the prefecture level showed a slight deviation to the eastern China while those at the county level showed a great deviation to the western China. Secondly, though the distribution center of national historical cities showed its deviating characteristics to the eastern and southern China due to different time cost, the deviation fluctuations and influence level was much lower than the influence of the administrative conditions. Thirdly, the developing distribution of national historical cities showed a complicated mesh network and location features were highly related to the regional characteristic, and the distribution centers and the centrality showed great differences in different regions. Last but not least, the influence of the centrality of national historical cities which caused by the administration, transportation and market will change a lot in the future, the administrative function decline, and the traffic function and the marketing function escalate may be the trend of development.
Regional inequality is an important issue in geographical research and regional development studies. China is the largest developing country in the world and its economy has undergone rapid and continuous expansion since the Chinese economic reform in 1978. China has achieved great success in economic development with an annual growth rate at 9.9%. However, behind the economic success in China, the country also faces serious challenges arising from imbalanced growth and intensifying social injustice. Since regional inequality may threaten national unity and social stability, it is a hot issue in research internationally and domestically. Almost all previous studies of the regional inequality have transformed static, qualitative measurement into a dynamic and quantitative evaluation. Most of the research in China has focused on lateral comparisons at a national level, only a few have addressed the provincial level. Added this above, this article analyses the regional inequality in Guangdong Province from 1990 to 2010 and follows a GIS-based multi-scale and multi-mechanism framework. Conventional global inequality indexes, spatial autocorrelation and spatial multi-level regression are utilized in the article to examine the regional inequality in Guangdong Province. Conventional global inequality indexes (including Coefficient variance, Gini coefficient, Theil index) analysis reveal that since the early 1990s, the regional inequalities at county level, municipality level, regional level and urban-rural level are experiencing increasing tends and fluctuated change. Geographical scale and spatial organization play an important effect on regional inequality. Based on GIS, spatial autocorrelation finds that spatial agglomeration-"convergence club" exists in the process of economic growth of Guangdong, which is attributing to intensity the regional inequality. The spatial multi-level regression analysis reveals that globalization, decentralization and investment are the three important mechanisms for understanding the regional inequality in Guangdong Province, and marketization has remitted the regional inequality effectively. What′s more, urban-rural and geomorphology are also the elements of the regional inequality, but the impact is not significant.
This article explored the exploratory spatial data analysis(ESDA) and spatial econometric model to check the spatial distribution of KIBS as well as its spatial dynamics factors across Guangdong Province . There are four main findings. First, it is described that the spatial distribution of KIBS which shows that cities in the Pearl River Delta(PRD) have the highest level across Guangdong Province, though there are discrepancy among different sectors in KIBS.Second, there is a spatial positive correlation relationship and spatial uneven distribution of KIBS among cities of Guangdong Province, which has a location of general dispersion and local concentration across this region. Third, most cities in PRD are KIBS hot spots with a high value agglomeration area, while the rest other cities in the eastern, western and northern of Guangdong are located incold area of KIBS , and the diffusion effect which come from the high level area(the PRD)remains limited to these adjacent cities, this lead to the regional lock-up effect of these cities to be low-low concentration for a couple of years. Fourth, a number of dynamic factors were used to interpret the spatial distribution of KIBS across Guangdong Province, result shows that urbanization, industrialization, ICT, economic openness and transport facilities play a positive role in promoting the development of KIBS, amongst which urbanization factor is the most important factor .While market demand factor has a negative influence on the development of knowledge intensive business service. Therefore, promoting urbanization level, improving the level of new industrial development and popularization of ICT infrastructure construction, increasing foreign investment, and revising the negative effect of market demand, all can effectively promote the development of KIBS in Guangdong Province.
Metropolitan area is a geographical unit which composes of central city and surrounding areas where has highly social and economic integration with the central city. It is generally defined the city center as the core, with the convenient traffic communication as the basis. The economy and diffusion of information in metropolitan area remains highly complex and interconnected. The metropolitan area can integrate more resources, including human resources, material resources and financial resources. So, the metropolitan area is a regional integration entity which is limited by the convenient degree of daily commuting. Defining geographical boundary of metropolitan area is the foundation of metropolitan region research. Defining spatial scale of metropolitan area reasonably is the key to ensure that the resources, infrastructure and land use in central cities and surrounding towns can be integrated in order to achieve the harmonious development between economy and society. Changchun metropolitan area is the central region of Changchun-Jilin-Tumen Forerunner Area, with basic characteristics of the embryonic form of metropolitan area. Construction of Changchun metropolitan area is of great significance for promoting the urbanization level of the central area of Jilin Province and the northeast area of China, coordinating social contradiction, and boosting the overall economic development. This article uses modern defining techniques about city circles, in consideration of daily live circle, to define the city center in Changchun. On this basis, the relationship between surrounding towns and central cities of Changchun metropolitan areas is verified using indexes such as economic distance, gravity model and commuting rate, and at the same time metropolitan area and spatial structure of Changchun metropolitan area are delineated.Changchun metropolitan can be divied into core layer, close circle circle, opportunity circle based on the relation of central city with the surrounding area.Through the construction of metropolitan area, the main expectation is to dilute the administrative divisions, protect green open space and land resources, construct compact city morphology and relatively disperse functional areas, and actively implement the policy of national new-type urbanization.
Population urbanization refers to the process in which rural populations move to urban areas. And this process has attracted more and more attentions of governments, scholars and public in China, as the emergence and rise of the concept of new-type urbanization. In this article, the mechanism of population urbanization in Jilin Province was analyzed by using geographically weighted regression (GWR) and spatial autocorrelation method. Compared with the ordinary least square (OLS), GWR extends the traditional regression framework by allowing the estimation of local rather than global parameters. According to the previous studies and the context of the study area, the article first supposed that there are four kinds of forces supporting the population urbanization in Jilin Province including state-provided force, non-state-provided force, agricultural force and external force. The state-provide force stands for the construction and investment by the state. Converting to the state-provide force, the non-state-provided force emphasized the role of market-oriented economy. The agricultural force refers to the motivational role of rural development, which is proposed due to the status of big agricultural province for Jilin. And the external force aims to analyze how the FDI and foreign trade drive the population urbanization. Then the role of each force was examined and measured by using OLS and GWR method. It is found that, the state-provided force played a most role among the four forces, and the effect intensity declined from central region to northwest and southeast region; the agricultural force stood on the second place, the effect of which increased from southeast to northwest; the non-state-provided force took the third place. The effect intensity of external force is smallest compared with the other forces, and there are no obvious spatial laws. According to these findings, this article suggested that more attentions should be paid to the role of non-state-provided force and the process of rural modernization in future development of population urbanization in Jilin Province. Meanwhile, diversified dynamic urbanization are also encouraged, namely the cities or counties should follow a misplaced and individualized developing mode.
The intensive use of cultivated land resource is not only the key to improve the cultivated land use efficiency and to ensure the national food security, but also been one of the most important components in rural development and social stability. Henan is the largest agricultural province and the most populous province in China, research on the intensive use of cultivated land in Henan is a window for penetrating into phenomena in China, for which occupying more than 6% cultivated land area in China. Considering the actual situation of the 126 counties in Henan Province, the evaluation index system for cultivated land use intensity was established from four aspects, including land investment degree, utilizing intensity, output efficiency and sustainable development status. The weight of each index was calculated by the entropy method, and then the intensity of cultivated land use in 1990, 2000 and 2010 at county level was evaluated and graded. The results demonstrated that: 1) As for temporal characteristic, the average degree of cultivated land intensive use showed an increasing tendency, increased from 0.262 in 1990 to 0.461 in 2010, and the total disparities of intensive use degree in Henan at county level have enlarged. The distribution shapes of intensive use degree were typical “single peak” shapes in the three years, transforming from "spike peak" in 1990 to "broad peak" in 2000 and 2010. 2)As for spatial characteristic, the character of spatial clustering about counties of high value and low value was remarkable, and intensive degree was significantly higher in eastern plain region than in western mountain area, higher in northern region than in southern region. The investment degree and utilizing efficiency of cultivated land were the main reasons that lead to the increment of cultivated land intensive use, while utilizing intensity and sustainable development status improved slower. The level of cultivated land intensive use in most counties from 1990 to 2010 showed a steady increase. 3) The spatial difference of cultivated land intensive use was resulted mainly from location condition, natural features and economic condition, and the main driving forces influencing cultivated land intensive use in different counties were different. The 126 counties in Henan were aggregated into five regions by self-organizing dual zoning method, including the eastern Huang-Huai plain area, the northern plain area, the southeast plain area, the central-south plain area and the western mountain area, and some suggestions on cultivated land intensive use were brought forward.
：To understand response of terrestrial ecosystem to climate changes, it is important to study variations in vegetation greenness (VG) under the changing climate. We firstly extend the Advanced Very High Resolution Radiameter (AVHRR)-based Normalized Difference Vegetation Index (NDVI) from 2006 to 2011 by calibrating the Moderate Resolution Imaging Spectroradiometer-based NDVI. Using hierarchical clustering and empirical orthogonal function (EOF) analysis, this study picked out main models of variations of autumn VG (September to November) which was indicate by NDVI from 1982 to 2011. Then, by using Singular Value Decomposition (SVD), we integrated temporal variations and spatial variations of NDVI and temperature to reveal climate background of variations in VG. We found that the MODIS-NDVI captures the main variations of VG as the AVHRR-NDVI; therefore, it is reliable to extend the AVHRR-NDVI with the MODIS-NDVI. Both of cluster analysis and EOF analysis show the variations in autumn VG had two main models. One (model I) was featured by an increasing trend of VG from 1982 to 2011. This model spreads across the North America land, northern part and (west, east) two ends of Eurasia. The mean rate of increase in NDVI was ~0.014 per decade. The other model (model II) was featured by turn of NDVI variations. This model mostly spread in the center area of Eurasia. The turn point of NDVI variations was about 1994. From 1982 to 1994, the NDVI increased at the rate of 0.027 per decade; while, from 1995 to 2011, the NDVI decreased at the rate of 0.017 per decade. EOF analysis as well as illustrates that above two models could explain 21.1% and 8.1% of total variations of NDVI, respectively. The SVD analysis illustrated that variations in NDVI matched well with variations in temperature. In the Model I area, the temperature changes were featured by an increasing trend. The time coefficients of NDVI and temperature had a strong correlation (R=0.82). In the model II area, the temperature changes were featured by a turn point. Before the turn point, temperature increased; after the turn point, temperature decreased. The time coefficients of NDVI and temperature also had a strong correlation (R=0.92). These results suggest that the persisting greening in the Model I area occurred in the climate warming background and conversion from greening to browning in the Model II area co-occurred with the climate changes from warming to cooling. These findings demonstrate that the main models of variations in VG might result from temperature variations. In the continental scale, the spatial heterogeneity of temperature variations resulted in spatial heterogeneity of VG variations.
Based on the FAO-56 Penman-Monteith formula, reference evapotranspiration (ET0) was calculated using a 50-year meteoro1ogical dataset at 19 meteorological stations over the Liaohe Delta during the period 1961-2010. The change of ET0 was studied by analyzing the sensitivity coefficients of ET0 to air temperature, wind speed, relative humidity and solar radiation together with their relative changes. The results show that variations present among the 3 sub-region (semi-humidity sub-region, semi-arid sub-region and coastal zone). The positive contribution of temperature and the negative contribution of wind speed and relative humidity and solar radiation are observed in 3 sub-regions. Therefore, contribution of wind is biggest and contribution of relative humidity is smallest because of its little relative change. Wind speed and air temperature are the determining factors of ET0 in coastal zone and semi-humidity sub-region, meanwhile air temperature and solar radiation are the determining factors of ET0 in semi-arid sub-region.
Statistics show that there was more precipitation in the first rainy season (April, May, June) , but the second rainy seasonal (July, August, September) precipitation is usually not obvious, and the yearly variation of precipitation is obvious unimodal distribution, base on the monthly precipitation data of 18 stations in Guangdong Beijiang river basin from 1965 to 2007. The precipitation in April and May were mainly downward trend, but mainly upward trend in June from 1965 to 2007 by Mann-Kendall test. Based on the significance of early sea surface temperature (SST) and teleconnection indices to the prediction of precipitation, the paper analyses the correlation between the PC1 of EOF in the first rainy seasonal precipitation and the same period and early one to twelve months globe SST and 10 teleconnection indices. The results showed that SST anomaly key areas are not only distributed in China’s neighboring seas; SST anomaly key areas and teleconnection indices and its key periods are larger differences among months in first rainy season. SST anomaly key area of all months showed that sea areas of negative correlation are bigger than the positive correlation. The positive correlational sea areas of April and May are mainly distributed in the southern hemisphere, while June mainly distributed in the North Pacific Ocean. The negative correlational sea areas of April mainly distributed in northern hemisphere; and the negative correlational sea areas of May mainly distributed in the East Atlantic-the Mediterranean Sea, northwest Pacific Ocean, South America’s southern waters, Australia’s western and southern waters; while June mainly distributed in Australia-centered sea areas. Some sea areas are significantly related to the first rainy seasonal precipitation at the same time and lag one to twelve months. The statistics showed that precipitation in the first rainy season correlated significantly with PNA, AAOI and NAO; and PNA was positive correlation, AAOI was negative correlation. Most of the teleconnection indices that correlated significantly with precipitation in May and June were negative correlation. This study will help to reduce the uncertainty of the first rainy seasonal precipitation forecasts in Guangdong Beijiang River Basin, and to provide a scientific basis for the guidance of industrial and agricultural production and the disaster prevention and mitigation, but also to provide a way for the study of regional climate change and its influencing factors.
The main purpose of this research is to estimate the soil organic carbon density and reserves of top soil in Guangxi, China. With the combined analysis of the soil profile data of the second soil survey, the soil map (1∶500 000) and digital map, the author unveiled the carbon density and reserves’ distribution features of different soil types and areas in Guangxi, and furthermore, made comparison to the data in other provinces in China. The results show that the soil organic carbon density varies significantly at different type of topsoil. The carbon density in soil is comparatively higher in the north of Guangxi than it in the south. And it is also higher in high latitude areas and yellow soil, while it is lower in low latitude areas and latosol. In addition, the whole soil organic carbon reverses of the topsoil in Guangxi is 6.42×1011kg, as much as the 1.5% of the nationwide reverses in China. And the average value of the soil organic carbon density, 3.33 kg/m2, is lower than the national average level, 4.70 kg/m2.
Age sequence in the process of oasification changes soil conditions and affects on soil fauna community. Up to now, few research has explored soil macrofauna community composition and diversity at an age sequence of cultivation in process of oasification. We investigated the composition and diversity of soil macrofauna communities using hand sorting method in both early May, mid July and September in native sandy shrubland, 27-year and 100-year oasis farmland. The results showed age sequence of cultivation had significantly affected on density, group richness, diversity and evenness index of soil macrofauna community. The density and groups of soil macrofauna community were strongly influenced by age sequence of cultivation in contrast to the modest change of diversity and evenness index. 27-year oasis farmland supported nearly 1.95 and 1.54 times higher of density and group richness soil macrofauna community than native sandy shrubland. 100-year farmland supported nearly 3.54 and 3 times higher of density and group richness soil macrofauna community than native sandy shrubland. The density of Geophilidae, Enchytraeidae, Lumbricidae and Muscidae larvae increased with oasis farmland cultivated, but the density of Tenebrionidae and Cicindelidae distinctly decreased with oasis farmland cultivated, and the density of Gnaphosidae, Noctuidae larvae and Formicidae had no obviously changed with oasis farmland cultivated. RDA analyses showed that the distribution of soil macrofauna community between native sandy shrubland and 27-year oasis farmland was clearly affected by soil temperature, pH, soil moisture, soil silt and clay content, total nitrogen and soil organic carbon. However, soil salinity, soil coarse content, soil fine sand content were the most important factors in shaping the spatial distribution pattern of soil macrofauna community between 27-year and 100-year oasis farmland.
Environmental magnetism is a newly rising frontier science among earth science, environmental science and magnetism. It reveals environmental actions, environmental processes and environmental problems of different temporal and spatial scales through the magnetic measurement and analysis of the magnetic mineral assemblage and characteristics. Due to the type, the content and the grain size of magnetic mineral related to the sediment sources, sediment transport capacity and early digenesis, and changes of these factors are heavily influenced by environmental changes, the information of sedimentary environment change can be extracted through the analysis of the magnetic characteristics of sediment. At present, environmental magnetic method has been widely used in loess, lake and shelf deposits as an normal mean for studying sedimentary record, but using this method on sedimentary environment in tidal flat is seldom. Hence, by measuring the magnetic parameters and the grain size parameters of the core YDZ1 in tidal flat of the Yellow River Delta, and combined with data of AMS14C dating, this paper analyzes the sediment magnetic properties and its sedimentary environment after the Last Glacial Maximum in tidal flat of the Yellow River Delta. The results show that the ferromagnetic mineral of pseudo-single domain (PSD) and multi-domain (MD) dominates the sediment magnetic properties of the core YDZ1. Among the magnetic properties of sediment, the parameters of χARM, χARM/SIRM and χARM/χ can be regarded as the substituted indexes for the clay (<4 μm) content or the fine-grained component (<32 μm) content. The sedimentary facies from surface to bottom in tidal flat of the Yellow River Delta has experienced the floodplain facies, the river facies, the delta-front facies, the neritic facies, the tidal flat facies and the river facies, and the sedimentary dynamical environment had a variation process from strong to weak, and then strong again.
Dabie Mountain is one of the most important water conservation in Anhui Province. According to the features of water resources, the water ecosystem services of the five reservoirs in West Anhui were classified into 2 categories (direct and indirect valuation) and 8 subcategories in this article. At the same time, a set of valuation index system was constituted with market value method, cost payout method, substitute engineering approach and so on, the value of the five reservoirs water ecosystem service was assessed by means of value evaluation in 2010. The result demonstrated that the total value of the five reservoirs water ecosystem service was 60.59×108 yuan RMB, and was up to 8.95% of the GDP of Lu′an City in 2010. The direct value was estimated as 19.62×108 yuan RMB, and indirect value was 40.92×108 yuan RMB. Among the different ecological service categories of the five reservoirs, flood control and water resource storage were of great value. The five reservoirs play an important role in flood control and water resource storage.
The tourist attraction is the material carrier of tourism supply. The proper construction of spatial structure of the tourist attraction is of great significance to the development of Chizhou tourism. With the network analysis of geographical mathematics method, the article analyzes the spatial structure of Chizhou tourism. Based on the nearest distance model, connectivity, accessibility and compactness, it analyzes and measures the spatial structure of Chizhou tourism from the perspective of the features of general spatial distribution, and regional spatial distribution structure. The result shows that the spatial distance of class A tourist attraction in Chizhou is small with the aggregation distribution; β index is 1.56 , γ index is 0.53, the average pathway length is 3.26, the connectivity in the tourist attractions is low, and the connection of transportation network is weak, the intense transportation network has not come into being, and the integration of tourism resources is low. C of the compactness index is 0.55, the compactness is in medium level, which lays good foundation for tourism transportation construction and improvement of connectivity and accessibility of tourism resources.
