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  • 1985 Volume 5 Issue 1
    Published: 20 January 1985
      

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  • Yu Qingyu, Jiang Zhuzhong, Ai Nanshan
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    Stress is physically a tensorial quantity which varies from point to point within the earth. Therefore, the stresses form a field in the earth. The present-day stress field manifests itself in a variety of phenomena, in turn, from a study and interpretation of these phenomena the stress field can be inferred and deduced. Many geomorphic features, such as orientation structure of a river network are first found by Prof. Scheidegger to be due to the action of a tectonic stress field, If the valley are supposed to be Mohr-type fractures, one obtains as predicted stress direction the bisectries of the prefferred valley trends. For calculation of the preferred directions a computational method has been developed by Kohlbeck and Scheidegger. But the program is too large for ordinary computer. The distribution pattern of valley trends is caused by the antagonistic interaction between the endogenetic and exogenetic effects. The exogentic effects give the distribution pattern randomness, meanwhile the endogenetic ones result its non randomness. According to the law of large numbers, the exogenetic effects will offset each other,the distribution will have non-random pattern. Therefore, we can research this pattern without the random statistical method, but with the method of the deterministic mathematics. In this paper we will give a new compStress is physically a tensorial quantity which varies from point to point within the earth. Therefore, the stresses form a field in the earth. The present-day stress field manifests itself in a variety of phenomena, in turn, from a study and interpretation of these phenomena the stress field can be inferred and deduced. Many geomorphic features, such as orientation structure of a river network are first found by Prof. Scheidegger to be due to the action of a tectonic stress field, If the valley are supposed to be Mohr-type fractures, one obtains as predicted stress direction the bisectries of the prefferred valley trends. For calculation of the preferred directions a computational method has been developed by Kohlbeck and Scheidegger. But the program is too large for ordinary computer. The distribution pattern of valley trends is caused by the antagonistic interaction between the endogenetic and exogenetic effects. The exogentic effects give the distribution pattern randomness, meanwhile the endogenetic ones result its non randomness. According to the law of large numbers, the exogenetic effects will offset each other,the distribution will have non-random pattern. Therefore, we can research this pattern without the random statistical method, but with the method of the deterministic mathematics. In this paper we will give a new computational method. Let θi be the direction of a river section and Li correspounding langth. A concept of concentrated degree is introduced as following: where {λ-k,......,λ0,......,λk} are a group of powers, λi-i>0, λ0 is maximum of {λi}, and if j>i, then λji. Obviously, reflects the concentrated degree of the directions of a river network at θm. The prefferred directions can be calculated by the following steps:1) compute 2) Suppose Max/n = a1, look for the maximum of , where n varies in (0°, 180°), (α1-45°, α1+45°) 3) Denote A=(α12)/2, B=A+90, then compute new concentrated degree . in and 4) Suppose β1=max , then β1 is the first preffered direction. Similarly, if β2=max, then β2 is the second preffered direction. By computing it is found that the choice of power {λi} is important. We call η=λ0k by propertion of amplitude. η can be taken near 1 when the variance of data is rather small, on the contrary, it should be taken rather more. utational method. Let θi be the direction of a river section and Li correspounding langth. A concept of concentrated degree is introduced as following: where {λ-k,......,λ0,......,λk} are a group of powers, λi-i>0, λ0 is maximum of {λi}, and if j>i, then λji. Obviously, m reflects the concentrated degree of the directions of a river network at θm. The prefferred directions can be calculated by the following steps:1) compute m 2) Suppose Max/n =al, look for the maximum of , where n varies in (0°, 180°), (α1-45°, α1+45°) 3) Denote A=(α12)/2, B=A+90, then compute new concentrated degree z. in and 4) Suppose β1=max , then β1 is the first preffered direction. Similarly, if β2=max, then β2 is the second preffered direction. By computing it is found that the choice of power {λi} is important. We call η=λ0k by propertion of amplitude. η can be taken near 1 when the variance of data is rather small, on the contrary, it should be taken rather more.
  • Liu Jiyuan, Teng Xuyan, Xiao Jinkai
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    A SIR-A image in the south of Tianjin acquired by the Shuttle Imaging Radar in November 1981 was interpreted directly and processed by computer system. The methods of processing were density slicing with statistical training; producing the normalized false color composite image through coregistration of the SIR-A and Landsat MSS data sets; unsupervised cluster classifications of some different image results of combining the Landsat MSS data and the SIR-A data. The interpretation keys using the SIR-A original image, the SIR-A density clicing image and the SIR-A/Landsat MSS normalized composite image to investigate land use situation were established after investigation in situ and analysis of the dielectric characteristics of different ground cover types and using large scale color IR aerial photo and land use maps aquired recently as the references, According to the keys an experiment on the aformentioned images interpretation and the interpretation accuracy analysis was undertaken. The results of the research indicate that the SIR-A data have higher resolution than Landsat MSS and remedy some defects of Landsat MSS data because of showing residential areas and linear features clearly, The SIRA/Landsat MSS normalized composite images incorporate the strong points of SIR-A and Landsat MSS data, have the resolution of the SIR-A image,reflect the ground surface spectral reflectance characteristics in the bands of visible and near infrared and the ground surface backscatter characteristics in the band of microwave and increase the classification accuracy that use remotely sensed data acquired by spacecrafts to land use maping.
  • Li Hen, Wu Sukung
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    Qinghai-Xizang plateau flora belongs to a floristic subkingdom of Holarctic Kingdom. This subkingdom in Xizang can be divided into 4 regions:(1)Yaluzangbu Valley region:the species of seed plant in this region amount to 1003, making up 19.38% of the total number in Xizang. The sum of endemic species in the region is 159, making up 15.8% of the total number. The flora of Yaluzangbu Valley region mainly originates from East Ximalaya Mountains and Hengduan Mountains. The monotypie genus, Ajaniopsis peniciliformis, is the endemic of the Yaluzangbu Valley. (2)Tangut region:there are 349 species in the region, being 6.74% of the total number in Xizang, of which the endemic species in the region is 10 in number. Two monotyPie genera, both are respectively endemic genera of the Qinghai-Xizang plateau and Hengduan Mountains, are found here, Metaritrichium microuloides and Przewalskia tangutica. In fact, Tangut flora represents an intermediate one between Qinghai-Xizang plateau and Hengduan Mountains. (3)Qiang-Tang region:it is the most poor in flora of Xizang. The spaties of seed plant amount to 255, being only 4.93% of total number in Xizang. The regional endemic species are 18, belonging to 13 genera of 7 families. It is considered that the present flora in Qiang-Tang derived from Himalayan flora and mixed with a great number of Tethysian elements. (4)All region:there are 547 species of seed plant,making up 10.57% of total number in Xizang, containing 41 regional endemic species. The Ali flora seems to be closely related with TethySian one. The Biebersteinia odora and Capparis spinosa oceuring in Ali, may be the few relicts of tropical elements of the Tethys.
  • The Group of Environment and Endemic Disease
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    This paper elucidated the characteristics of geographical epidemiology from the angle of disease ecology. Among them the apparent endemic distribution is the most important charaeteristics. It shows that the disease is closely related to natural environment. Obviously, there exists a KaschinBeck’s disease belt and two non-disease belts in China. According to the natural features of disease-areas, eight envromental groups of diseae-areas can be divided and respectively were merged into three types. The main feature of chemical geography in Kaschin-Beck’s disease area is just like that in Keshan disease area, selenium content in environment in the affected areas is always lower. Hence, the two diseases often emege simultaneously in many cases, but Sometimes in some areas, such as in the area with lower selenium content, one of ths two occurs alone. In this paper, the authors made an approach to disese-cause of Kaschin-Beck’s disease. The low selenium content in environment is a basic factor in appearence of Kaschin-Beck’s disease, but some other factors must be taken into account. All of factors was called compound factors. The other factors include (1) Vitamins, for example Ve, (2) Some life elements related with selenium, such as Cd, Hg, Ag, Mo. Fe, Sr, Zn, etc.,(3)Some organic matter or some toxins in affected areas,(4) Some habits.
  • Zu Wenehen, Ma Xuehui, Wang Rongfen
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    China has rich peat reserves distributed widely. The peat properties vary greatly with regions and types. Based on the correlation analysis, organic matter, humic acid, decomposition degree and acidity are considered asthe basic natures and main properties of peat. According to statistics andquantitative grade, China’s peat is characterized by weak acidness, mediumdecomposition degree, middle organic content and high humic acid content, which result from the conditions of peat formation and development peculiar to China. The main properties of peat in various regions are obviously different. The peats both on the northeast mountains and the Qingzang Plateau have similar properties, but on the northeast mountains the peat with relatively high organic content is weakly acid to acid, herb, wood and moss peats all can be found; while on the Qingzang plateau peat is neutral to alkaline, mainly herbaceous. The peat in the North China Plain is high ash content, low humic acid content, high decomposition degree, nearly neutral, mainly herbaceous. The peat in the middle and lower Changjiang region is weak acidness and middle organic content. There are not only wood and herb peats with high decomposition degree and high contents of organic matter and humic acid, but also some moss peat.
  • Wang Rujlin, Sun Yamei, Hu Yuuyuan
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    This set of maps are represented by means of flow line. Circular symbols represent the volumes of flow of cars in the crossroads, and lineal symbols with two colours represent the volumes of flow in the roads, of which one colour represents the cars coming and another going. This set of maps are compiled automatically by digitizer, electronic computer, digital plotter. This paper is illustrated from follwing five parts:type of data and format of observation and record, graphic repressentation and design of symbols, mathematical model, coding and data organizing, data processing and simple introduction of computer mapping technology.
  • Qian Junlong
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    The close relationship between the content of chemical element in living things and their environment could be found.The rings of trees in different content of chemical elements which showed the character of their environment at that time.The annual change of content in tree ring spontaneously reflects features of its environment.The late,of course,is influencedby human activity. This paper shows that the content of chemical elements in tree ring is gradually change as well as reflects the corresponding changes with its environment. Using model ln Ctree ring=K ln Csoil, we estimated the coefficient K by experements,The result from calculation shows that tha same kind of trees nearly has the same constant K, although they grow in different places We also use this model to discuss the problem of background value of element in different places.
  • Fu Bojie
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    In the paper,taking Yan An nearby regions as a example, the land types of loess hills and gully areas of northern Shanxi province are discussed. Loess hills and gully areas are an important region for developing agriculture.The loss of water and erosion of Soil are severe, in the region. Based upon specific natural condition of Yah An nearby region, some Principles for classifying land types are given.According to these principles,taking landform, vegetation and soil as chief criteria for classifying land types, 5 land types of first category and 23 land types of second category are identified in Yah An nearby regions.A hierarchical scheme for land classification in the region is introduced. Horizontal and vertical structure,and developing diagram of land types as well as the physical features of main land types are discussed.In addition,an approach to the direction of production-construction in the hills and gully areas of northern Shanxi province is also made in the paper.
  • Zhao Rui, Liu zhengdong
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    In this paper a method of classification cvalution of different land units in the light of land quality is introduced on the basis of fuzzy clustering analysis. It is put forward here that according to the regional features of geography and research subject, suitable evalution elements and indexes for the method should be selected, and then marks are given on the basis of synthetic analysis to form a group of fuzzy Subsets, After fuzzy clustering analysis, a comparison is made between its results and those forms—ordinary methods of classification evalution.
  • Xu Mengying
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    In this paper, the author analyses the spatial variation of precipitation over the Yangtze River Basin, using the method of correlation coefficient based on data during April-Sept. from 1953 to 1980. The results are summerized as follows:(1) There is well correlation near Hanko, but the coefficient decresaes rapidly with increase of distance from it. The decrease is faster in southwest direction than one in east-west direction. (2) The maximum correlation coefficient emerges in the east of Yichang along both sides of the Yangtze River. (3) The maximum correlation directions are NW-NWW in the east of Hanko, and SW SWW in the west of Hanko.
  • Sun Zhongming
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    The Gezhouba reach ran out of the Sanxia Gorge and developed on an alluvial fan which was restricted by the rock hills of both banks,representing some complex features of fluvial geomorphology, such as channel widening or branching, main current abruptly turning and unconsequently running. The channel widenin5 seems to relate to the unequal rising of neotectonics and the differential erosion on various lithological characters for long time.The trend that the channel moves to right bank during the river evolution process and the fact that the main current near the convex bank now obviously indicated the relation ship between the evolution and unequal tilting of neotectonics, the extension of Hwangbai River alluvial fan and the flow deflecting caused by Hengliangzi. Since A.D.500 the situation that ErJiang and Sanjiang branches have had no water in dry seasons has been formed. At present, the two branches are still in declining stage.
  • Guo Daben
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    According to measure and data, the author shows main features of rivers in the Sanjiang Plain and change of water balance on time and space, and then estimates water resources of five types, i.e.runoff, underground water, soil water, supplied water from the three rivers and lake (or reservior) water. Sum of the five water resources can be up to 32.3 billion m3. But they are rather unwell-distributed, the annual range is rather considerable too. Up to now, only 7.7% of water resources have been utilized, according to programme, 17.8 billion m3 will be utilized in furture in the area. Rationally exploiting water resources in the area should combine with protection and management, and the criterion judging rationality of utilization only is beneficial results on economic, ecologic and social aspects. During exploitation and utilization, it is important to provent water resources from pollution.