文章基本信息

标题：Towards optimizing hierarchical data revisions
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作者：Burkhard Schaffrin ; Jackson Cothren
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：1998
卷号：XXXII Part 4
出版社：Copernicus Publications
摘要：The revision of existing data must always be considered when new data are collected which have known relations with theold data, thereby taking into account that the two datasheets in question may belong to one and the same, or to two differenthierarchical levels. In the first case, optimal data fusion would amount to a joint adjustment and, as a result, to modificationsof the existing data which may then be checked for their significance. In the second case, the situation turns out to besomewhat trickier since, after the integration, the old dataset with a higher position in the hierarchy should still be unaffected,including the corresponding dispersion matrix. Here we shall explore the optimal procedure for the second case and present aunifying algorithm which would allow us to go ahead with the revisions until (only in the last step) we have to decide aboutthe hierarchical behaviour.Although some of the more theoretical questions must be left unanswered at this point, we do include an example in whichtwo photogrammetric networks of substantially different scales are to be integrated.