The aim of the present paper is to analyze the main trends of population change and its spatial variations and patterns in Austria within the last 50 years, from the first population census after World War II in 1951 to the most recent census in 2001. The 2001 population census will be the last 'conventionally organized' census in a long series of modern Austrian population censuses, which started in 1869. The next Austrian population census to be held in 2011 will be - corresponding to similar trends in a growing number of countries in Western and Northern Europe - primarily register-based. The overall demographic trends in Austria within the second half of the 20th century correspond more or less to the general changes that have taken place in many other industrial nations. Thus Austria shares with the majority of European countries an ever increasing life expectancy, a continuously declining fertility rate, a dramatically increasing proportion of older people (by 2035, every third resident will be over 60 years old) and an ongoing concentration of population in urban areas. Three aspects of population change in Austria are analyzed in this paper: population change in Austria in general during the last five decades and its underlying factors; the contrasting spatial patterns of population change in the Western and Eastern parts of Austria; and finally a more detailed analysis of growth regions and regions with population decline. The main results of this paper are: The Western parts of Austria, especially the larger urban regions within the Western Austrian Alps, have shown the strongest population growth during the last 50 years. The most important factor of population growth in Western Austria has been the positive balance of birth. Fertility rates in Western Austria, however, have been falling continuously during the study period, but are still higher than in most other areas of Austria. As far as the future demographic developments in Austria are concerned, it can be assumed that the trends of the second half of the 20th century will be continuing. In contrast to other European countries like Germany or Italy, however, Austria's population will still be growing approximately for the next three decades, although very moderately and only by immigration. Thus the population of Austria is expected to grow from 8.03 million inhabitants in 2001 to approximately 8.43 million by the year 2027. In the long run, however, Austria will be no exception from the European demographic trends: According to Statistics and changing factor analysis, an outlook to the year 2075 shows a decline in the number of population to 7.54 million inhabitants in Austria. Thus, in approximately seven decades, Austria will have about half a million fewer inhabitants than in 2001, a figure that was last recorded in 1980.
Based on a thorough review, this paper firstly identifies three stages in the evolutional process of China's regional planning practice, and describes the various planning contents and characteristics in each stage. Following this, the paper further explores the current situation that some governmental sectors compete for the authorization in spatial planning, and analyzes the fundamental reasons behind. By identifying the great opportunities and bright prospects for regional planning in China, the paper puts forward a series of concrete suggestions for its development, with an emphasis on such issues as regulating the planning system, reforming the planning management organizations, constituting the planning regulations and laws, improving planning contents, enhancing spatial control, etc.
Interregional input-output analysis may depict accurately interregional economic linkage and driving forces of regional development. This paper focuses upon the driving forces of regional industrial development since the 1990s based on analysis of China interregional input-output model. The results show that most of the industries in the coastal areas depend upon external market. The industries with degree of dependence on induced output of external demand exceed 50%, accounting for more than 60% of the total in the coastal areas. On the contrary, in inland areas, most of the industries depend upon the internal market as driving forces of industrial development. The differences in driving forces of industrial development lead to differentiation in potential of industrial development and spatial concentration of industries, and thus many industries gather into the coastal areas. This indicates that development of western areas, revival of northeast industrial bases and growing-up of the midland face many challenges in fostering industrial competitiveness. Hence, the policy of regional development must pay more attention to upgrading of industrial competitiveness in these areas. In view of the external trade, the degree of industrial internationalization in the coastal areas has reached a rather high level. Therefore, the fluctuation of international market will directly influence industrial development, or bring more opportunities to the industrial development in the coastal areas.
By selecting the South-North line from urban central district to Baoshan district of Shanghai, and collecting housing price data along the line where both the second-hand houses and newly developed houses are located inside the inner ring, between the inner ring and the middle ring, between the middle ring and the outer ring, outside the outer ring, the authors analyze the price gradients. It has been found that the prices of second-hand houses are generally higher than the prices of newly developed houses, but the former is faster than the latter in the speed of price decrease successively. Then according to the practical circumstances, seven influencing factors are selected such as flourishing degree, ratio between supply and demand, geographical location, traffic conditions, population situation, basic facilities and environmental quality are selected and by means of the multivariate linear regression method, the influencing factors of housing price gradients are discussed. Finally, the affected degree of factors is evaluated by applying partial relation coefficient analysis method and single factor weighted index method. The results show that the second-hand housing market differs obviously from the newly developed housing market. The ratio between supply and demand is the most important influencing factor on the second-hand housing prices while the environmental quality is the most important influencing factor on the prices of newly developed houses. However, the important effects of the flourishing degree and traffic conditions are not verified in the present study.
After a brief review of the studies on the human dimensions of the land use changes within and outside China, this paper, taking the Pearl River Delta as the case study area, makes a thorough and careful study on the human dimensions that affect the land use changes in China's mega-urban region from the angles of qualitative and quantitative analysis by applying GIS spatial analysis techniques and the SPSS statistic analysis techniques (such as the factor analysis and the regression analysis) together upon the data collected from the government materials, the statistical data and the on-the-spot investigation records. The results of this research consist of two parts: first, the qualitative analysis shows that the human dimensions, including population, economic growth, urbanization and industrialization, government policies and so on, have a strong correlation with the land use changes in the Pearl River Delta, and all of these human dimensions have greatly affected and will continue to affect the land use changes in the mega-urban region of the Pearl River Delta. Second, the quantitative analysis, being the further and verified step of the qualitative analysis, reveals by means of the factor analysis and the regression analysis techniques that the major human dimensions that have influenced the land use changes are population factor, economic development level factor, urbanization and industrialization factor, agricultural structure adjustment factor, regional industrial structure factor and foreign investment factor. Clearly, this result, to some extent, is consistence with the conclusion of the qualitative analysis.
Based on land rocky desertification and land use data (scale: 1:50000) in 2004, the distribution law of land use types with different lithologies and occurrence ratios of rocky desertification relating to different land use types in typical fengcong (peak cluster) rocky desertified area located in central-southern part of Panxian county of Guizhou province were researched quantitatively. The results indicate that there is a high ratio of difficult to use land with exposed basement rocks in homogenous limestone, limestone interbedded with clastic rock, mixed dolomite/limestone assemblages. There is relationship among different grades of rocky desertification and land use types and rock types, such as the cultivated land on slopes has a higher occurrence ratio of slight rocky desertification in homogenous limestone, and then the limestone interbedded with clastic rock. Slight rocky desertified land was dominated by shrub land, and sloping cropland accounts for 11.67%, moderate rocky desertification was dominated by moderate coverage grass slopes, intense rocky desertification was dominated by rocky dryland which is difficult to use. From 1995 to 2000, the rate of intense and highly intense rocky desertification in moderate coverage grass slopes and difficult to use land increased. Finally, the further classification of rocky desertified land by land cover was made according to the above-mentioned researches, and the forming processes and taming emphases of karst rocky desertification in the study area was also pointed out in this paper.
Land use and land cover (LULC) change has profound impacts on water resources, and it is particularly important for the inter-basin Middle-Route of the South-to-North Water Diversion (MR-SNWD) Project of China. We developed a LULC classification system for the water supplying area (~95,000 km2) of the MR-SNWD Project and mapped the LULC in the 2000s using Landsat TM and ETM+ imagery. The analytical results of the spatial pattern of LULC indicate that: 1) The area percentages of forests, shrubs, farmland, rock/bare land and water bodies are 50.97%, 25.58%, 15%, 5.66% and 1%, respectively. 2) There are significant differences in LULC pattern among the southern slope of the Qinling Mountains, plains & hills in the Hanjiang-Danjiang river basin, and the northern slope of the Daba Mountains. Intensive land use and degraded land area appear mainly in the Hanjiang-Danjiang river basin. 3) LULC in the watershed is correlated with topography. Not only does the natural land cover show an altitudinal gradient, but the types and intensity of land use are also relevant to elevation. Steepness is a key restrictive factor to land use. Although no prominent effect of slope aspect was detected in terms of LULC pattern at local scale, there is profound difference in LULC structure between the southern slope of the Qinling Mountains and the northern slope of the Daba Mountains. In summary, the current condition of vegetation is fairly good over the water supplying area of the MR-SNWD. The intensive land use types are concentrated in the relatively flat area below an elevation of 1000 m a.s.l., an area where intensive land degradation also occurs, and made it the crucial area in water quality protection and environmental management.
Supported by "3S" technology, this paper analyses land use change in Huangfuchuan Watershed from 1987 to 2000, conducts a synthetic eco-security assessment on the watershed by multiplication algorithm model on the pixel scale, and discusses the relationship between different land use patterns and eco-security of watershed. The results showed: (1) In recent 10 years, the general tendency of land use change in the study area was that the proportion of urban land, woodland, cropland and shrub increased constantly and that of water area, grassland, sandy land and bare rock decreased gradually. During this period, the watershed land use pattern was under the tremendous pressure from the conflict between the rapid urbanization, economic development and the conservation and rehabilitation of eco-environment. The distinct decline of water area is the bottleneck of this contradiction. (2) From 1987 to 2000, the average synthetical eco-security index rose from 6.033 to 6.506. It is sure that the eco-environment of the whole watershed has been improved. However, eco-environment in some areas even went worse despite of large-scale comprehensive harnessment. (3) In Huangfuchuan Watershed, most of the sandy and soft rocky lands are in a moderate-warning or serious-warning state of eco-security, and the rest of the land use types basically in a light-warning state of eco-security. (4) Land use types are closely correlated with eco-security. The order of eco-security index is: shrub > woodland > grassland > cropland > sand > soft rock, which indicates that measures taken based on woodland and shrub are the priority and important means for ecological restoration of the watershed. Furthermore, the sandy land and bare rocky land are the key problems of comprehensive harnessment of the watershed, which could not be overlooked. Generally, this paper emphasized the impacts of different land use types and patterns on eco-security of watershed and put forward suggestions concerning the adjustment or optimization of land use pattern and improvement of the technical system for eco-security assessment based on simulation and prediction of land use change, which would have wide application prospectives in the future.
Supported by RS and GIS technology, combining the achievements in previous researches and numerous field investigations, we used Landsat-TM images of 1984, 1989, 1992, 1996, 1998, 2004 and Landsat-ETM image of 2002 as an information source to investigate thoroughly and monitor dynamically the wetland resource of Beijing, including wetland type, area, distribution, wetland exploitation, etc. The images of 1996 and 2002 were taken in May, and the remaining in September or October after flood season. We processed images selected using PCI 9.0, and then translated the format into Geotiff format. We set up interpretable symbols of different types of wetland, including reservoir wetland, river wetland, lake wetland, division canal, rice paddy and fishpond. Then images vectorizaton was carried out for spatial analysis and data statistics using ArcGIS 9.0. On this basis, taking the five-river system as an example, we can analyze the dynamic changing trend and evaluate water quality covering 1991 to 2000 using Nemerow Index. It turned out that: the areas of wetland in 1996 and 1998 were larger than those of the other years, reaching 677.29 km2 and 505.84 km2 respectively, and after 1998, the wetland resource degenerated sharply, especially rice paddy wetland. From 1998 to 2004, the area of wetland dropped 46.0%. Furthermore, the water quality of five-river system has a declining tendency, mainly due to precipitation decrease and human destruction. Finally, some countermeasures are put forward on how to use and protect the wetland eco-environment of Beijing.
Cellular Automata (CA) has strong spatial modeling capabilities, which can simulate the evolution of complex geographical phenomena. The core of CA models is how to define transition rules that control the conversion of states in simulation. Transition rules of CA models are usually defined using linear methods, such as multicriteria evaluation (MCE). However, the evolution of geographical phenomena often manifests the complexity of nonlinear features. Discrepancy can be produced by just using the linear solution for retrieving transition rules. This paper proposes a new method to acquire nonlinear transition rules of CA by using the techniques of kernel-based learning machines. The method can transform complex nonlinear problems to simple linear problems through an implicit high-dimensional feature space which is produced by kernel functions. This study has demonstrated that the proposed method can effectively solve complex nonlinear problems in simulating geographical phenomena. It has been applied to the simulation of urban expansion in the fast growing city, Guangzhou. Comparison indicates that more reliable simulation results can be generated by this method.
This paper discusses the basic frame of urban geography in Northeast China on the background of rebuilding northeast old industrial base, new-type industrialization and new-type urbanization. It is an overall summarization of the unban geographical system of northern China for the purpose of proving and practising urban geographical theory further. It is also a basic prerequisite for the analysis of the northeast economic development under the new situation of implementing the concrete strategy of "giving a new life to the region" and "the regional innovation" to meet the actual need of the region. Proceeding from the formation and development process of the urban geographical structure of Northeast China, this paper deals with such basic problems as the urban system frame, the key cities, the metropolitan district, the urban compact district and the urban agglomerations of Northeast China. It points out that the formation and development process of the urban geographical frame in Northeast China witnesses three periods, namely, forming period of the ancient cities and towns, forming period of the modern cities, and shaping and developing period of the modern urban system. In terms of the urban system frame, four relavant aspects are identified as: a top to bottom urbanization process that is fast first and slowing down afterwards, the structure of scale and grade of "weak pyramid" type, the "T-shaped" space structure distributed along railway lines, and the urban function structure developing from "single" to "new-type". The "four cities era" taking Harbin, Changchun, Shenyang and Dalian as key cities in Northeast China has come. The three provincial GDPs are highly concentrated on the four cities, taking shape and developing into four metropolitan districts of "Big Harbin", "Big Changchun", "Economic Zone of Shenyang" and "Big Dalian" relying on these four cities. In the process of rebuilding the northeast old industrial base, the four cities will choose different leading directions that rely on the original foundation and new opportunities for development. Harbin will continue to strengthen its position as the key city in the northern part of Northeast China. Changchun should fully take its basic advantage of automobile industry that has broad market and form an automobile industrial base. Shenyang will serve as the centre of Northeast China. Dalian will become an important passageway of Northeast China depending on its advantage while developing outward-oriented industries. As a result of certain degree of urbanization, the urban compact district and urban agglomerations of Northeast China have developed into a relatively complete and intensive frame, and has formed a basic pattern of "three groups" preliminarily, namely, urban agglomeration of "Central-southern Liaoning", "Central Jilin" and "Harbin-Daqing-Qiqihar".
