This paper is part of a research on Spatial Data Infrastructure (SDI). In order to prevent duplication of effort and expense in acquiring spatial data, the Brazilian Government started systematic studies aiming at the integration and standardization of spatial data produced by various federal institutions in 2003. The Decree 6.666, which was approved on November 27th 2008, set up the National Spatial Data Infrastructure (INDE). This decree is mandatory for National Government institutions, but not for the other producers of spatial data. The standardization of spatial data and metadata proposed by INDE meets the standard scales covered by the Brazilian Mapping System, and this official mapping system represents the national territory by a series of adjacent and homogenous quadrangle maps at the standard scales 1:25.000, 1:500.00, 1:100.000, 1:25.0000 and 1:1000000, topographic mapping at scales larger than 1:25.000 still demands a normalization. The use of spatial data and metadata rules promoted by INDE for cartographic design on large scales represents a step forward in this direction and is in line with the INDE Action Plan recommendation. Considering the importance of large-scale data for the different segments of Brazilian society that use spatial information, our main research goal is to analyze the applicability of spatial data and metadata standards proposed by the INDE for large-scale topographic maps. In order to perform the intended analyzes, we established some procedures that entails the mapped features analysis, to define their types and representation; the relation of these features with the categories, classes, sub-classes and attributes of objects, according to with the INDE standards; the implementation of a spatial database and the association of metadata. The data used in the development of this paper refer to 123 topographic maps at scale 1:2000. The results confirm the applicability of spatial data and metadata standards proposed by INDE for large-scale data. However, due to the levels of detail inherent to 1:2.000 representations, some adjustments were necessary. Consequently new classes, attributes and attribute domains were created.
Brazilian Spatial Data Infrastructure (INDE); Applicability; Large-Scale Data
