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The predictive capability of landslide susceptibility maps is usually estimated using independent information that was not utilized in the LSM process.
It has been applied to characterize the structure of the human genome [ 8– 10] but only a small fraction of the raw optical maps is usually used for mapping.
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Free maps are usually available at the trail head.
Maps are usually seen as objective, factual, informative.
The maps are usually bogus, or they lead you to a desk where a man will try to sell you time shares.
Since maps are usually represented as graphs, topological algorithms tend to preserve continuity in the matching, avoiding frequent errors.
The landuse maps are usually classified into several classes, but in this study, forest (including primary and secondary), bushes, crop land (agriculture), and grass land were considered.
Geomorphological maps are usually produced by interpretation of aerial photographs and various other documents that are concerned with slope materials and chronology.
However, vegetation maps are costly to produce and update and most land-use/land-cover maps are usually made with a general purpose, focused on land management, and not thinking on animal distribution.
In view of the relatively low computational load, look-up tables (or maps) are usually used to approximate nonlinear function or characterize operating-point-dependent system variables in typical embedded applications.
Unlike conventional maps, transit maps are usually not geographically accurate, but emphasize the topological connections among the different stations.
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