It is difficult to carry out the automatic cartographic generalization of urban buildings, because of their complex shape.
An algorithm and some constraints for generalization using Least Squares Adjustment theory are presented, with
analyzing the procedure of generalization for urban buildings under multi-scale environment. Automatic generalization
for building polygons can be carried out in the algebra way, with building the automatic generalization adjustment model
including simplification, aggregation, displacement and symbolization. The practice shows that the object shape is
represented perfectly by the algorithm, with providing a basis for evaluation on results of generalization, which improves
the procedure of automatic generalization in scientific and feasibility.
Least squares method is one of the effective and widely used data process tool in statistical based data analysis.
Automated map generalization is an intelligent process in nature, which involves mining the knowledge from the original
data sets to form the generalized features that are the abstracted representation of the original features in multiple and
different scale levels. In this paper, we present an integrated methodology for the automated generalization of settlement
areas based on least squares adjustment. Taking the original data sets of the features as observational values, the
parameters representing the generalized features are computed according to the least squares adjustment model. The
four-level hierarchical model for settlement area generalization is first proposed. The rules and constraints conditions in
settlement area generalization are then described, and the least squares adjustment model is derived in settlement areas
generalization. The results of practical tests demonstrate that the validity and feasibility of the proposed model for the
simplification of settlement areas in geographic information system.