Conceptual model for generalisation of Lithuanian spatial reference data

Abstract

Small scale spatial data are widely used at regional and national level – not only for mapping, but also for assessment of environmental conditions for purposes of planning, forecasting, etc. Therefore it is necessary to prepare such data professionally. Generalisation of large or medium scale spatial data is the most efficient process to produce smaller scale data. Of course, simple transfer of information is almost never suitable to satisfy the requirements for small scale maps. Additional transformations (generalisation) are necessary. During the process of generalisation complexity of spatial information may be significantly be reduced in terms of number of objects, geometry, etc. But the main spatial, non-spatial and topological characteristics of the objects have to be preserved. Process of reduction is irreversible, therefore it is necessary at first to clearly define the requirements for small-scale spatial data (for example, density of spatial objects, minimal allowed area, width and length of object, minimum length of the edge of object, spatial links between the objects). Given those requirements it is possible to be develop conceptual model and procedures of generalisation between particular data sets. Such model will also describe the appropriate selection, aggregation, simplification or alignment algorithms.