Possibilities of updating small-scale basic spatial data in Lithuania using generalization methods

Abstract

Small-scale spatial data are widely used at regional and national levels not only for mapping but also for the purposes of planning, forecasting, etc. Therefore, a professional preparation of such data is necessary. The generalization of large or medium scale spatial data is the most efficient process to produce and update smaller-scale data. Certainly, a simple transfer of information is almost never suitable to satisfy requirements for small-scale maps. Additional transformations (generalization) are necessary. Spatial information complexity may be significantly reduced in terms of the number of objects, geometry, etc. However, the main spatial, non-spatial and topological characteristics of the objects have to be preserved. The process of reduction is irreversible, and therefore it is necessary at first to clearly define requirements for spatial data (for example, the density of spatial objects, the minimal allowed area, the width and length of an object, a minimum length of the edge of an object, spatial links between the objects). The above imposed requirements provide a possibility of defining procedures for generalization and a conceptual model between particular data sets.