An Automatic Approach for Generalization of Land-Cover Data from Topographic Data

摘要

The paper presents an approach for the automatic generalization of large land-cover datasets from topographic data using fast generalization algorithms. The generalization approach is composed of several steps consisting of topologic cleaning, aggregation, feature partitioning, identification of mixed feature classes to form heterogeneous classes and simplification of feature outlines. The workflow will be presented with examples for generating CORINE Land Cover (CLC) features from the high resolution German authoritative land-cover dataset of the whole area of Germany (DLM-DE). The results will be discussed in detail.