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Keynote Paper

Agriculture / Soil

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Poster Sessions
  • Poster Paper 1
  • Poster Paper 2



  • ACRS 1990


    Poster Session


    Digital analysis of salinity of soil using multisource data


    Results and Conclusion
    The analysis of soil using multisource data combined remote sensing and non remote sensing more scientific and more accurate according to the theory of genesis of soil table 3 shows the areas of classes with different methods the approximately reference data are from a soil salinity map in YANGGAO area mapped from the interpretations of the TM image comparing the classification result of preprocessed TM image and modification after synthetic classification of multi source data . The confidence of the classification of multi source for salinity is increased and this kind of algorithm can improve the implementation of classification in speed and in simplicity also can use for updating GIS database.

    Table-3 The result of classification
    proportion in total area saline soil
    (%)
    highly salinized soil
    (%)
    mid-salinized soil
    (%)
    weakly salinized soil
    (%)
    non-salinized soil
    (%)
    water
    (%)
    map of
    salinity
    only TM
    data modification
    of multisource
    data


    2.5

    2.8

    0



    7.5

    11.2

    -0.7


    30.7

    30.4

    0.5


    52.1

    48.0

    0.3


    4.5

    4.0

    0


    2.7

    3.2

    0


    The dynamic inspecting of soil salinity could be accomplished using the data of different times the true changes can not be recognized completely in this experiment because the MSS image in March of 1977 has a low resolution when it is not strong salification period Nevtheless some tackled field is a still shown in the images for example a big salinized field at the TM image BAIDENG river is decreased and some highly salinized fields are obvious in the TM image salinized indicates the seriousness Stalinization after the comparison it is known a lot of work still remains to do for improving the large area salinized soil.


    In brief the analysis of salinity using multi source data not only can improve the quantitative result the data of the same time but also can analyze the dynamic change with the data of different time this method is effective for the quantitative inspecting managing and improving of the salinized soil Note that fig 1,2 white error color is for saline soil red highly salinized soil light red for mid salinized green for weekly light blue for non salinized and blue for water.

    Reference
    1. P.H Swain J.A Richards and T.Lee, Machine processing of remotely senses data symposium 1985 pp 211 218

    2. Wanghu Peng Tianjie Li preprint on 40th congress of the international astronautical federation (1989)

    3. R.J Kauth G.S Thmos IEEE Symposium proceedings of machine processing of remotely sensed data (9176 ) pp 4 B 41 4 B 5
    Page 3 of 3
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