By Shashi Shekhar; Hui Xiong
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Extra info for Encyclopedia of Geographical Information Sciences
Example text
This cost may be significant, e. , in applications with frequent updates, such as those involving moving objects. This extra cost may be reduced if updates are deferred; this would improve performance, but with an accompanying loss of accuracy. Beyond aggregate queries, progressive approximation can also be used in queries producing a set of objects as output. Unlike aggregate queries that admit to a natural definition of accuracy (the length of the confidence interval), there is no clear metric to assess the quality of set-based answers.
Generalization is always subjective and requires the expertise of a human cartographer [2]. In the digital era, attempts to automate generalization have lead to the differentiation between model generalization and cartographic generalization, where the operations of model generalization are considered to be easier to automate than those of cartographic generalization. After model generalization has been applied, the thematic and geometric granularity of the data set corresponds 8 Abstraction of GeoDatabases appropriately to the target scale.
Such aggregate information can improve the aggregation query performance is that if the query region fully contains the MBR of some index entry, the total weight stored along with the index entry contributes to the answer, while the sub-tree itself does not need to be examined. However, even with this optimization the query effort is still affected by the size of the query region. Scientific Fundamentals This section presents a better index for the dominance-sum query (and in turn the spatial aggregation query) called the Box-Aggregation Tree, or BA-tree in short.
