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  • Table of Content
       , Volume 6 Issue 4 Previous Issue    Next Issue
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    Review
    REMOTE SENSING AND URBAN GEOGRAPHIC INFORMATION SYSTEMS
    Shi Songlian
    REMOTE SENSING FOR LAND & RESOURCES. 1994, 6 (4): 8-12.   DOI: 10.6046/gtzyyg.1994.04.02
    Abstract   HTML   PDF (353KB) ( 821 )

    In this paper the work in urban remote sensing completed by Ministry of Geology and Mineral Resources (MGMR) is introduced briefly. The paper proposed that we must adopt advanced geographic information systems (GIS)technology for urban modernized managerment and MGMR is with superiority to carry out this job.

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    Applied Research
    USING TM DATA TO IDENTIFY SURFACIAL GEOLOGICAL FEATURE OF THE GOLD DEPOSIT ──A Case Study in Er daogou Gold Mine
    Ma Jianwen, Zhang Qidao, Xu Ruisong, Ma Yaoliang
    REMOTE SENSING FOR LAND & RESOURCES. 1994, 6 (4): 20-22.   DOI: 10.6046/gtzyyg.1994.04.04
    Abstract   HTML   PDF (800KB) ( 836 )

    TM data because of its multispectral bands and continous spacial coverage as well as good price, is widely used in small and middle scale geological mapping. This project is a case study for using TM data to map surfacial characteristics of ore deposit modle for large scale gold mining district prospecting.The result image is overlayed by 1:10000 geology map, gold bearing vein map, and 1:2000 Cu secondary dispersion halo map. It is conclued that 70% of geological unit is matched, 100% of gold bearing vein and halo are well overlayed.

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    APPLICATION OF REMOTE SENSING IMAGERY MODEL FOR GOLD DEPOSIT AND "EVIDENCE-RIGHT-WEIGHT"METHOD IN GOLD DEPOSIT PREDICTION
    Luo Fusheng, Cui Zhenkui, Xu Shuang, Wang Guojuan
    REMOTE SENSING FOR LAND & RESOURCES. 1994, 6 (4): 23-29,7.   DOI: 10.6046/gtzyyg.1994.04.05
    Abstract   HTML   PDF (528KB) ( 805 )

    Xiongershan region, Henan province is an important gold-mineralized area in China. Research of gold mineralization and selection of prospective targets in the region have been carried out by using remote sensing technology. First of all, TM image data are processed through various methods to get ideal remote sensing images, then, the image information is interpreted and analyzed in combinaticon with regional geological survey and typical gold deposit study to determin main ore control factors, such as structures,ore-bearing strata, rock bodies, and alteration, etc. The remote Sensing imagery models of different types of gold deposit have been set up on tho basis of extraction of comprehensive image signatures and gold deposit distribution pattern.In the light of the models, prospecting targets have been chosen by using "evidence-right-weight" graphics information integration. The method,which presents favourable geological factors of ore control as binary graphics and calculates their "evidence-right-weight", is based on Bayes rule, By use of geographic information system (GIS), mutual independent geological factors relative to the deposit, mineralization evidence, are integrated statisticaly for calculating posterior probability of gold deposit distribution,which can be used to indicate potential gold-mineralized area, The method,combination of remote sensing, statistics and expert’s experiences, is provided with a rigorous theoretical basis and visual, fast, and flexible characterastics,and is convinent for geological application.After practice, it is concluded that according to remote sensing imagery models of different type of gold mineralization and "evidence-right-weight"graphics information integration method to choose prospecting targets is succeesful. Various extents of gold mineralization have been found in 8 first class and 5 second class potential areas predicted by us after field testing . The result is very obvious.

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    STUDY OF OIL-GAS MODELS OF REMOTE SENSING AND SYNTHETIC PREDICTION OF PROSPECT RANGES
    Xie Qingyun, Guo defang, Bao shaohua, Lan yuqi
    REMOTE SENSING FOR LAND & RESOURCES. 1994, 6 (4): 30-36.   DOI: 10.6046/gtzyyg.1994.04.06
    Abstract   HTML   PDF (902KB) ( 961 )

    It is the synthetical, general, macro and visual Characteristics of remotely sensed image that makes remote sensing technigue a successful way to find oil-gas fields. on the basis of study of the relations between linearment, ring feature, geological structure and the distribution of oil-gas fields, three oilgas prediction models of remote sensing are established in the paper. Using mainly the three models with other geological models, synthetical prediction of oil-gas is made in Jiyang Depression on microcomputer, and some oil-gas prospect ranges are pointed out.The research shows that the method presented here is simple, convient and may lower the cost greatly in oil-gas exploration.

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    REGIONAL MODEL OF ENVIRONMENT CHANGE IN MONSOON ASIA
    Buhe Ausser, Li Huiguo
    REMOTE SENSING FOR LAND & RESOURCES. 1994, 6 (4): 37-45.   DOI: 10.6046/gtzyyg.1994.04.07
    Abstract   HTML   PDF (619KB) ( 923 )

    Entering the 90s, more and more attentions have shifted from study global change caused by single element to study the one caused by regional models of multielement. The primary reason is that remote sensing was introduced as an important means into the global change study field. The paper,in light of the regional features of monsoon Asia, put forward a regonal model of global change as well as the temperal and spatial domain for remote sensing application in the study field.

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    PRESENT CONDITION AND FUTURE ADJUSTMENT OF LAND USE IN HAINAN ISLAND
    Cai Yunlong
    REMOTE SENSING FOR LAND & RESOURCES. 1994, 6 (4): 46-53.   DOI: 10.6046/gtzyyg.1994.04.08
    Abstract   HTML   PDF (605KB) ( 1182 )

    This article analyses some important aspects of present condition of land use in Hainan Island, including land use composition, land productivity,spatial distribution of land use, land use technology, land use rate, and land use planning and management. Then, the guiding principles of future land use are described as following: (1) The land use composition should be adjusted appropriately according to the regional development strategy;(2) Land use should more coordinated with market in economic operation; (3) Tropical crop should take an important place in land use; (4) The land should be developed and used in sustainable way; (5) The macro control of goverment should be strengthened; (6) The area of cropland should be stabilized. Finally, some measures to realize rational and effictive land use are suggested.

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    Discussion and Debate
    ATMOSPHERIC CORRECTION OF LANDSAT TM IMAGERY BY USING METEOROLOGICAL RECORDS
    Zhang Yugui
    REMOTE SENSING FOR LAND & RESOURCES. 1994, 6 (4): 54-62.   DOI: 10.6046/gtzyyg.1994.04.09
    Abstract   HTML   PDF (521KB) ( 837 )

    The complexity of forest canopies and the variability of atmospheric conditions necessitate the normalization or standardization of satellite imagery. Standardized reflectance images were produced by using atmospheric correction in a simplified procedure. The atmospheric parameters at overpass time were evaluated by using interpolation among local meteorological records. The path radiance derived from the visual range is adjusted by the dark pixels in the image data. The normalized reflectance images were enhanced with linear or nonlinear transformation for storage. A set of four date subscenes were used as examples to illustrate the good correspondence of reflectance results from quite different atmospheric conditions.

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    ARTIFICIAL NEURAL NETWORK MODEL FOR RECOGNITION ABOUT LAND COVER TYPE OF REMOTE SENSING
    Cai Yudong, Li Wei, Xu Weijie
    REMOTE SENSING FOR LAND & RESOURCES. 1994, 6 (4): 63-66.   DOI: 10.6046/gtzyyg.1994.04.10
    Abstract   HTML   PDF (199KB) ( 846 )

    The self-organization artificial neural network model for the recognition about land cover type of remote sensing was presented in this paper.A group of samples was selected and studied for the model testing. The recognizing rate is high. The results show that the neural network model is good, and therefore it might be referred as an effective technique for the recognition about land cover type of remote sensing.

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