Table of Content

    15 November 1998, Volume 53 Issue 6 Previous Issue    Next Issue
    Cheng Liansheng
    1998, 53 (6):  481-491.  doi: 10.11821/xb199806001
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    New cities should be defined as those cities that are newly built, beginning from a low base line and having reached an obvious size. In this paper, they are defined as those that have been built from virgin land or settlements below the level of county capital since the industrialization drive of the early 1950s and that have been formally recognized as cities by the state. In 1994, China had 89 new cities in all. In terms of distribution, the western part of the nation has more new cities than the eastern part, the north more than the south, and the frontier areas more than the coastal regions. With the help of graph theory, the paper presents separate maps on China’s urban networks for three time periods: the early 1950s, the late 1970s, and the early 1990s. An analysis of the network maps suggests that the new cities have performed four functions affecting the urban networks. They have facilitated the maturity of the networks, stimulated the networks’ spatial expansion, accelerated their internal differentiation, and enhanced their linkage potential. By analyzing the new cities’ connection rate, accessibility, centripetal tendency and locational sensibility, the ability of the new cities to dictate the networks is discussed. Using the locational quotients of centripetal tendency and locational sensibility, WH and WM , a dualistic classification of the new towns’ functions with four types of positions are put forward: Type 1: Centripetal dominance, WM>1, WH>1; Type 2: Marginal dominance, WM>1, WH<1; Type 3: Centripetal extremity, WM<1, WH>1; Type 4: Marginal extremity, WM<1, WH<1. The study reveals that the stronger a new city’s location can dominate its urban network, the better is its accessibility, and the more beneficial it is to the city’s economic development. Three types of new city locations——centers, midpoints and extreme points——affect the differences of the new cities’ positions in the networks. When new cities are established before the emergence of their network, they lead to the spatial expansion of the urban network; if an urban network exists earlier than the new cities, the establishment of new cities leads to the network’s internal differentiation.
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    Liu Yuefeng, Han Mukang, Wu Lun, Nobuo Mimura
    1998, 53 (6):  492-500.  doi: 10.11821/xb199806002
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    Zhujiang River empties into the South China Sea through eight outlets in the delta. The evolution of the outlets, the rates of delta reclamation and the changes in the coast line in 1966~1996 are quantitatively studied. The results revealed by remote sensing and GIS techniques are compared with the data taken and digitized from the 1966 topographic map at the scale of 1∶10 000 . The total reclaimed area in the entire delta during the period has been calculated to be 344 km2, or at the average rate of 11 47 km2/a which is much greater than that in the historical period. Of this total, 146 km2 have been reclaimed in the Lindingyang district where four eastern outlets (Humen, Jiaomen, Hongqili and Hengmen, denoted as A, B, C, D in Fig.1) are found. In the Modaomen and Jitimen districts (E and F in Fig. 1) in the western part of the delta, 115 km2 have been reclaimed, and around the Yamen and Hutiaomen (G and H in Fig.4) in the Huangmaohai district 73 km2 have also been reclaimed. Through our analysis of the digital TM images for five years (1986, 1988, 1992, 1994 and 1996), three areas with different levels of sediment concentration——relatively high, medium and relatively low——can be differentiated in the Lingdingyang estuary (Figs. 1 and 2). Here, the presence of three closely located outlets (B, C. and D in Fig. 1), where large amounts of sediments are deposited in the western part of the estuary, has made it the most rapidly expanding reclamation area. In addition, the blocking of sediment movement by the rocky Qi’ao Island has also facilitated rapid reclamation in the peripheral areas of the Hongqili and Henmen outlets to the north of the island. Beside, because of the presence of rich sediment coming from the north, active and strong siltation has occurred in the sea area to the west of the island and between the island and Zhuhai/Macao, including the harbor of Zhuhai City. By contrast, the eastern coast of the Lingdingyang estuary has grown much more slowly, with some sections even experiencing slight retreat due to erosion. Thus the prospect for large scale reclamation does not look bright, but this should not adversely affect the development of landfill projects for industrial use along the rocky coast. In the western part of the delta (Figs. 3 and 4) during the same period, due to rapid reclamation, the coast line has moved seaward by 4.7 km, at the rate of 156 m/a, seriously affecting the hydrological conditions and sediment dynamics in each outlet and its adjoining channel. This has caused the channels to lengthen greatly and resulted in channel splitting, a redistribution of runoff and sediment load, and frequent river flooding. Rapid reclamation during 1966~1996 led the Modaomen outlet to rapidly advance seaward for 4.7 km (Fig. 3). After the completion of a planned reclamation project, shown in the area with dashed line, the present Modaomen outlet will advance further seaward by more than 11 km, while in the Huangmaohai estuary (Fig. 4), the Yamen and Hutiaomen outlets are merging into a new outlet due to rapid reclamation. Should the current trend continues, the prospect for delta reclamation in the future would be adversely affected by the following two factors∶1. The source of sediment generation will become progressively small as increasing amount of sediment is trapped in the reservoirs on the middle and lower reaches of the river and as sand excavation from the river intensifies to satisfy the growing demand for sand by the booming construction in the delta. 2. In the next 50 years, the delta region’s relative sea level will rise by 0 5 m, which will increase the water depth and weaken sedimen tation inside as well as outside of the outlets. These issues should be taken seriously in making land use decisions and in the management of the delta.
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    Zheng Jingyun, Huang Jinhuo
    1998, 53 (6):  501-510.  doi: 10.11821/xb199806003
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    Grain loss caused by natural disasters in China’s eight agricultural regions during the period 1950~1990 is estimated by the equation:Yd=Yt-1 +(y^p-yt-1 )St+yt(St-St-1 )-Ytwhere Yd is the grain loss due to natural disasters, ytis grain production per ha in yeart, St is planting area in year t, Yt is the amount of production in yeart , and y^pis calculated grain production per ha including y^tand ye as listed respectively in Tables 3 and 7. After the situations of agricultural production, irrigation, agricultural input and natural disasters are discussed, the estimated grain loss for the eight agricultural regions in 1950~1990 is presented. The estimation shows that the average yearly grain loss due to natural disasters is 34 billion kg, or 11 6% of the yield. The time series for the percentage change is given in Figure 2, which shows a decreasing trend since the early 1960s. The regional patterns of the percentages of loss vary. Northeast China has had the most grain loss, followed by North China and then South China.
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    Li Kerang, Zhou Chunping, Sha Wanying
    1998, 53 (6):  511-519.  doi: 10.11821/xb199806004
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    Based on the 〈Atlas of physical climate of the ocean〉 that has been compiled and on the indexes of warm pool that has been calculated, this study analyzes the basic features of warm pool in the western Pacific Ocean and its impact on climate and climate change, especially the relationships among the warm pool, subtropical high in the western Pacific and ElNi o. The Atlas provides the basic data of monthly physical climate of the warm pool region of the ocean for 1949~1990, including the atmospheric thermal, kenetic and dynamic features of the ocean surace. The indexes of the warm pool are: areas, north (or south) boundary, east (or west) boundary, intensity and the location of its centre. The results show that there are close relations among the warm pool, subtropical high and ElNi o. The warm pool and the subtropical high are positively correlated, including both seasonal variation of the area and its northern and southern boundaries. Variation of the warm pool usually precedes that of the subtropical high. The area of the warm pool expands (or contracts) and the location of the warm pool center in the western Pacific moves toward the north (or the south) from winter (February or March) to summer (July or August) (or from summer to winter). In general, the seasonal and interannual variation of the area and the location of the subtropical high are similar to those of the warm pool, with the latter preceding the former by a few months. The relationships between western Pacific warm pool and ElNi o, including the SST and area size, are also discussed.
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    Ling Yuquan, L iu Shaozhong, Wu Zheng, Li Changzhi
    1998, 53 (6):  520-527.  doi: 10.11821/xb199806005
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    Aeolian sand ripples are a common landform feature created by the movement of sand grains on sand bed driven by wind. The process of their formation and evolution are complex. Although there are no apparent stages in the evolutionary process, which depend essentially on the changing conditions of the wind, three rough stages are suggested by our wind funnel experiment. The first is the stage of formation, during which sand ripples are formed by sand grains creeping forward on the sand bed. Sand grain creeping requires time and involves the adjustment of position of the grains on the sand bed, i.e., sand grains are sorted out by wind. During this stage, the sand driving wind is a state of nonsaturation in which the air currents fluctuate and the grains creep. Sand ripples do not follow any typical pattern and their distribution is random. The second is the stage of development. Sand ripples develop due of the action of wave grain duality. During two stage, sand driving wind is highly satuated and a state of balance is reached between sand grain creep and the intensity of grain saltation. The wave grain duality of the sand driving wind also reaches maximum, as does the action of grain sorting by wind. Third, during the stage of disappearance, high unsaturated sand driving wind hastens the processes of the sand ripple morphological changes, disintegrate the sand ripples, and reconstitute them. Creeping is rapidly changing into soltation. These processes cause sine wave resonance between air current and sand driving wind until the sand ripples disappear. Fine sand and extremely fine sand of natural sand dunes are the grain sizes for the formation of sand ripples. The major forms of sand ripples include the wave form which is the most basic and recurrent, the abnormal forms and their derivations, all nourecurring; and the crescent form found in the border zone between the coarse and fine sand beds. The velocity of sand ripple movement is slow, raging between 10 -1 ~10 1 cm/min. The experiment formula is VR=1.58×(VL-5.5)0.67(cm/min). The wave length and wave height of the sand ripples in the experiment are identical to those found in the field.
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    Han Maoli, Hu Zhaoliang
    1998, 53 (6):  528-536.  doi: 10.11821/xb199806006
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    Ttraditional China’s civil service examination system was designed to recruit government officials. The top winner of the final examination held at the capital was granted the highly respected title of “zhuangyuan” (meaning “number one scholar”). This paper investigates and explains its geographic distribution in different time periods. The creation of the imperial examination system in the Sui Dynasty (581~618) significantly altered the old way of selecting imperial officials. No longer was a candidate’s family background a criterion for selection, and all candidates were judged by their performance on the examinations. Only the top scorer of the final examination was granted the title of “zhuangyuan” after he had passed all lower level examinations and the final text. A “zhuangyuan” was always seen as the most brilliant person in his community and an instant star in the nation at the time, and he was normally appointed to a very high official post. During the 1300 years of imperial rule when the examination system was implemented, some 700 “zhuangyuan” were selected, of whom 378 can be identified by their native places of origin. Our analysis of their places of origin in different time periods shows that most of them had come from north China prior to the Tang and Song Dynasties (618~1279), but after that the number from the south gradually increased. During the Ming and Qing Dynasties (1278~1911), the south clearly dominated the distribution. Jiangsu Province led the nation in the production of “zhuangyuan”, with a total of 27 produced at different times. The spatial and temporal distribution of “zhuangyuan” was shaped primarily by regional economic conditions. Beginning with the Song Dynasty (960~1279), the nation’s economic, educational and cultural center began to shift from the north to the south. From the Song to the Qing, the number of schools in the south always exceeded that of the north. In addition, the changing locations of the capital city and the changes in the examination system also affected the geographic distribution of “zhuangyuan”. Such a pattern of distribution is a consequence of China’s geographic, historical and cultural characteristics, and the pattern has had profound impact on China’s socioeconomic development, up to today.
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    Wang Guo, Zhang Qingsong, Li Yuanfang
    1998, 53 (6):  537-544.  doi: 10.11821/xb199806007
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    The purpose of this study is to reconstruct the record of recent environmental change at Barrow, Alaska through temporal inverse deduction using a sedimentary core. In this field of study, the traditional approach is qualitative, taking grain size, its statistical feature, geochemical composition and its combination as indexes of sedimentary environment to indicate environmental change. In recent years, the use of Q mode factor analysis and transfer function techniques has facilitated the quantification of paleoenvironment research. Q mode factor analysis has been used to study several undetermined factors, revealing certain results that are widely known. Changes of sea level, sedimentary rate, temperature and precipitation must cause changes in sedimentary grain size and chemical composition in the lagoon sedimentary environment. The causal relationship may not be strictly linear, but before nonlinear technique can be practically used, we will analyze grain size and geochemical composition by Q mode factor analysis to extract sedimentary environment factors. Factor identification is the key to Q mode factor analysis. Here, the identification was done according to: (1) the cause and effect relationship in sedimentary modeling; (2) the qualitative feature of environmental changes that are already known; (3) the degree of correlation between recent meteorological data and the factors identified. In this paper, we will identify temperature, precipitation, sedimentation speed and sea level as the major factors affecting environmental change. Defining transfer function is important in paleoenvironment quantitative research. The temperature and precipitation transfer function is obtained from linear transformation of these factors, and the two unknown constants are obtained by linear regression of 11 years of running mean climatic data from Barrow Meteorological Station. Determining sedimentary rate is very important for establishing sedimentary temporal model. The transfer function of sedimentary rate is from linear transformation of its factors, and the two constants needed are determined by 210 Pb timing and recognition of several environment events. The transfer function of sea level change is obtained from linear transformation of the sea level factor, and the two constants are determined by the time when marine sediment began and by the present ocean depth. Research on sea level change is only exploratory here because, first, there are no recent observed sea level data to compare with, and second, it remains to be further studied what effect sea level change had on shore zone sediment prior to marine transgression. Based on the analysis of the sedimentary environment of AB 67 core at Barrow, some conclusions are reached: 1) From the reconstructed sedimentary rate curve, we have determined the sedimentary period of each layer in the AB 67 core. Sedimentation in the bottom layer began in the latter half of the 16th century. 2) From our study of sea level change, we get the sea level change curve of Elson Lagoon. According to the grain size, geochemical composition and micropoleontology combination, marine deposit begins at the depth of 20 cm, which corresponds to the last half of the 18th century. This is earlier than the date estimated by 210 Pb. The mean uplift speed of sea level is 10 mm穉 1 over the last 200 years. 3) The trends of temperature and precipitation show that the environment in the 16th and the 17th centuries was colder and dryer than that of today, that temperature rose and precipitation fluctuated greatly in the 18th and the 19th centuries, and that both temperature and precipitation fluctuated greatly in the 20th century. The pattern of temperature fluctuation is well confirmed by the realignment of microponotoly in the AB 67 core.
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    Li Guosheng, Shao Yubin
    1998, 53 (6):  545-552.  doi: 10.11821/xb199806008
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    The possibility of using remote sensing of ocean water color to determine oceanic primary productivity has been recognized for many years. After reviewing the relevant literature, this paper presents the mechanism and a methodology to obtain oceanic primary productivity by using remote sensing and GIS technologies. The physical processes of absorption and scattering cause the upwelling radiance just beneath the sea surface to be related to the constituents of the water. Except for waters in close proximity to coastlines and coastal river months, biological constituents play a dominant role in these processes. The most important constituent appears to be phytoplankton, microscopic plant organisms that photosynthesize and constitute the bottom link in the ocean food chain. These plankton contain chlorophyll a, which absorbs strongly in the blue and red regions of the visible spectrum. Hence, increasing concentrations of phytoplankton (chlorophyll a) have the effect of changing the color of water from its pure state of deep blue to green hues. Another major factor that influences the precision of water color sensing is the unknown spectral characteristics of the water. Because of inherently different characters, there is great difference between the spectral measurement and analysis of different types of land and water. The method we use to remove the aerosol effects is based on a correction algorithm devised by Gordon, which isL(λ)=L s(λ)+L d(λ)={L w(λ)+L g(λ)}×T A(λ)+L P A(λ)+L P R(λ) In the investigation of marine primary productivity, it is most important that one formulates suitable algorithm for estimating primary productivity using the chlorophyll concentrations derived from remotely sensed ocean color data. Because of the problems in plant physiological response, there are difficulties in generating a suitable algorithm. Three methods for measuring primary productivity have been suggested by Ryther and Yentsch (1957), Parsons, et al (1984) and Eppley, et al (1985) based on the use of assimilation ratio, the intensity of photosynthesis to chlorophyll concentration, the chlorophyll a concentration, and the irradiance penetrating to ocean depths, etc. Such works show that equations can be written as P= C×Q×R/K , P t,d =P t, max {aI o, max sin 3(π/D)te -kd }/{1+aI o, max sin 3(π/D)te -kd } and ln P t =3.06+0.5ln C -0.24 T A +0.25 D L , respectively. In this paper, with the remote sensing algorithm model of the content of sea surface chlorophyll, three types of algorithm about oceanic primary productivity are introduced. By using GIS rule based on simulation technologies, a theoretical GIS estimation model written as P t=? 苮{phy(x,y,z),a,b,c} and its resolution method for the spatial oceanic primary productivity are proposed.
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    Li Zhen, Bao Jigang, Qin Chaofeng
    1998, 53 (6):  553-561.  doi: 10.11821/xb199806009
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    The impact of tourist development on the environment quality of the vegetation ecology and the quality of scenery management of Mount Danxia in Shaoguan, Guangdong is quantitatively analyzed in terms of the value of landscape, tourist impact coefficient and sensitivity level. The perpendicular profiles of five scenic vegetation plots were selected in the tourist area to demonstrate and analyze the visual aesthetics of the scenery. Twenty two sampling quadrats were selected to reveal the impact of tourist development on the vegetation cover, of which ten are tourist areas. Several conclusions were reached. First, there was a 20% decrease of vegetation in the heavily visited tourist areas. Second, while the vegetation in tourist areas is protected, 30%~70% of the vegetation in non tourist areas has been destroyed. Third, the old trees near tourist spots have suffered from termite destruction and withered as a result of weakened resistance, whereas the trees some distance away from tourist areas were often felled by hotels and temples for fuel. Generally speaking, however, tourist development in Mount Danxia has stabilized the plant groups’ ecological environment.
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    Lu Guonian, Qian Yadong, Chen Zhongming
    1998, 53 (6):  562-569.  doi: 10.11821/xb199806010
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    Automated extraction of the characteristics of topography from digital elevation models (DEM) is an important application technique used for qualitative analysis of remote sensing observations of the earth system, for positional analysis in GIS database construction, and for complex analysis of multi dimensional information and polymorphic information. Based on our study of the extraction techniques using DEM in recent years, we find that the key to their successful application lies in two factors. The first is how to adequately define topographic structure morphologically or hydrologically, and the second is how to design algorithms for the defined topographic structure. The definitions of and the relationships among geomorphic entities must be concerned with the most significant attributes of the landscape. Different definitions of a morphostructure will lead to different algorithm designs and different analytical results. Hydrologically based method employing many composites of thresholds to extract surface features may yield obscure and inaccurate results. On the other hand, morphologically based method using spatial composites and contrast analysis of finite morphologic elements can produce accurate results. In the last 20 years, two approaches to the identification of topographic features from DEM have emerged, one seeking to classify individual pixels or connected pixel regions on the basis of local surface characteristics, and the other attempting to accumulate more global surface information to build a more consistent structure of the surface features. The typical local method of pixel classification includes a hill, depression, cape, ravine, regular slope or saddle. These elements are included by inspecting the eight connected pixels adjacent to a cell and by computing the central pixel. An alternative to such a local method is to base the stream, divide, and basin extraction directly on the synthesized global information through pixel integration into larger structures. In this paper, we develop an algorithm based on global information. For experimentation, we constructed GIS databases and studied the ravine district in the loess hills of the Wangjiagou drainage area in Lishi, Shanxi Province. The primitive drainage catchments are generally characterized as having uniform aspect and elevation, arranged as leaves on the stream channel tree graph. Landform features extracted from the algorithm match the ground truth quite well. Topological operations on the channel network may be extended to other drainage catchments by building attribute files parallel to the topologic stream graph code.
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