Urban information is a kind of multi-sources data, and the variety of these data demands that we should set up an
information system. One of the major tasks is to store massive spatial data and non-spatial data and manage these data
effectively. One of the other major tasks of urbanization integration is how to search for spatial data and non-spatial data
what we need into massive information, so we need to establish indexes for spatial data and non-spatial data and construct
the relation between the two kinds of data in order to convenient query. The paper is focused on data indexes
construction, classified indexes for non-spatial data, R-trees index for spatial data and puts forward an area hiberarchy
index tree to build up direct relationship between spatial data and non-spatial data for seamless queries, and the
experiment shows that the hiberarchy index tree is much validated and something useful is obtained.
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