The Ground-truth problem is to find the bias between the remotely sensed data and the true values. As the rainfall observation using satellite is becoming plausible, it is necessary to know how to capture the bias between the remotely sensed data and the true one. In this paper a method to capture the bias based on the second order statistics of rainfall field data is introduced and the application study based on several multi-dimensional precipitation models are tried. The results showed that all three models gave similar dimensionless root-mean-square(RMS) errors and that about 60 visits (about one month) are necessary to achieve about 10% RMS deviation in a special situaltion of continous raining. In reality the raining time during observation is less than 10 % (8% for the GATE), thus much longer observation time is necessary (more than one year).


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    Title :

    Multi-dimensional precipitation models and their application to the ground-truth problem


    Additional title:

    KSCE J Civ Eng


    Contributors:
    Yoo, Chulsang (author) / Ha, Eunho (author)

    Published in:

    Publication date :

    1998-12-01


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






    Ground truth acquisition

    Manderscheid, L. V. | NTRS | 1973


    Ground truth acquisition

    Manderscheid, L. V. | NTRS | 1973


    Ground truth acquisition

    Manderscheid, L. V. | NTRS | 1973