Constrained Building Boundary Simplification Based on Partial Total Least Squares Method

Abstract

Maps obtained from various sensors or surveying instruments provide important geographic information for users. Buildings are critical components of various city-area maps. In this paper, we present a constrained building boundary simplification method based on the partial total least squares (PTLS) method. Simplification of building boundaries may cause some data quality problems, such as geometric displacements, right angles changed into non-right angles, and area inconsistency at different scales. Therefore, in this paper, a linear fitting model based on the PTLS method is constructed for building boundaries with the aim of reducing the total positional difference. Furthermore, end-point, right-angle, and area constraints are constructed at the same time to maintain the right angles and areas of the building. The simplification results are obtained by solving the proposed constrained model by using the PTLS method with constraints. The proposed method was applied in a building boundary simplification experiment. The results showed that the proposed method maintains the right angles and areas of buildings and reduces the geometric displacements of buildings after the simplification.

A Progressive Simplification Method for Buildings Based on Structural Subdivision

“…Self-optimizing techniques have already been studied for an agent system performing generalization [30]. Jin et al (2020) [31] provided a constrained building boundary simplification method based on the partial total least squares, which could obtain smaller geometric displacements of buildings than the classic least-squaresbased fitting method. A simplification algorithm is designed by judging edge structure features of four or five adjacent points [15,32,33], which achieves simplification of various types of buildings.…”