A Progressive and Combined Building Simplification Approach with Local Structure Classification and Backtracking Strategy

Abstract

Several algorithms have been developed to simplify buildings based on their local structure in past decades. However, different local structures are defined for certain purposes, and no algorithm can appropriately simplify all buildings. We propose a combined building simplification approach based on local structure classification and backtracking strategy. In this approach, local structures are classified and their based operations are defined by considering the buildings’ orthogonal and non-orthogonal features. Each building is simplified to target scale with a selected local-structure-based operation progressively scale-by-scale. Rules are built to support the selection of local-structure-based operations with a binary decision tree, and a backtracking strategy is used when an invalid operation is applied. When the building is too small or the evaluation shows that it cannot be simplified based on local structures, template matching or enlargement algorithms are applied to simplify the building. A dataset (1:10k) collected from the Ordnance Survey was used for the experiment and simplified scale of 1:25k. Results satisfied legibility constraints and the change in area, orientation and position of simplified buildings are controlled within certain range by comparing with the results generated based on other four simplification algorithms. Possible use of our approach for continuous scale transformation of buildings is also discussed.

A Progressive Simplification Method for Buildings Based on Structural Subdivision

“…The method proposed herein was compared to the adjacent four-point simplification method [15], local-structure-classification simplification method [8], ArcGIS 10.2 building simplification tool (Simplify Building), and recursive method [25] by simplifying 1594 1 Test of directional dependence. Rotate the buildings with rotation angles ω of 90 • in Figure 15b.…”

“…The method proposed herein was compared to the adjacent four-point simplification method [15], local-structure-classification simplification method [8], ArcGIS 10.2 building simplification tool (Simplify Building), and recursive method [25] by simplifying 1594 buildings at scales of 1:25,000 (ε = 7.5 m), 1:50,000 (ε = 15 m), and 1:75,000 (ε = 22.5 m). The original scale of those buildings is 1:1000.…”

“…To evaluate the feasibility and adaptability of our method, the change in the number of vertices (NumC), the change in the area (AreaC), the change in ratio of orthogonal vertices (OrtC), the change in position of the center point (CtrPC), the change in shape in global (SGC), and the change in shape in details (SDC) [8,41] are selected as the evaluation indicators, which are defined as the following:…”

“…Building simplification is usually conducted on a single building, largely independent of contextual information. Additionally, it sometimes can be conducted separately in the process of building map generalization [8]. This paper just focuses on individual building simplification of outlines.…”

“…Considering numerous algorithms to simplify buildings, Yang et al (2021) [42] presented a hybrid approach that identifies the best simplified representation of a building among four existing algorithms to generate simplification candidates with a backpropagation neural network. Wei et al (2021) [8] proposed a combined building simplification approach based on local structure classification. The local structures are classified and operated by considering the buildings' orthogonal and non-orthogonal characteristics.…”