A new model combining building block displacement and building block area reduction for resolving spatial conflicts

Abstract

Applying pre‐processing and geometric transformation, for the generalization of building blocks, can lead to spatial conflicts which are mainly resolved by displacement. However, the conflicts may not be resolved, due to the insufficient space for displacement or the existence of other objects that prevent displacement. This article proposes a novel model combining building block displacement and building block area reduction for resolving spatial conflicts. In this model, first the immune genetic algorithm with improved objective function, with the goal of minimizing the total conflicting area, is used for displacement. Second, a building block area reduction model is applied to reduce the area of the unresolved conflicting building blocks. For this, a building segment partitioning model is developed for partitioning the boundaries of conflicting building blocks. Then, the conflicting segments are locally simplified for more adaptation to the initial generalized ones. We generalized two datasets from scale 1:25 to 1:50k and then used the datasets with scale 1:50k to assess the proposed model. The results demonstrate that the proposed model has improved the correctness and completeness by 3.62 and 4.24% for dataset 1 and 5.67 and 7.92% for dataset 2, respectively, compared to one of the recent models for resolving conflicts.

A spatial contextual immune genetic algorithm to building cartographic displacement

“…One is to add the new map states related to other operators into the map state space, and then use an optimization algorithm to search for the best or a feasible map configuration (Ware et al, 2003; Wilson et al, 2003). The other approach is to implement different operators separately, and then integrate them into a system with established processes (Pilehforooshha et al, 2021; Ruas, 1998) or an intelligent control model (e.g. the multi‐agent system) (Barrault et al, 2001;Wang, Guo, Wei, et al, 2017; Wei, He, et al, 2018).…”

“…The other approach is to implement different operators separately, and then integrate them into a system with established processes (Pilehforooshha et al, 2021;Ruas, 1998) or an intelligent control model (e.g. the multi-agent system) (Barrault et al, 2001;Wei, He, et al, 2018).…”

“…Pilehforooshha et al (2021) added the total conflicting area to the objective function of their IGA. With the improved objective function, their algorithm can resolve more conflicts with shorter displacement distance and less remaining conflict area.…”

Generalização Cartográfica: Desafios e Perspectivas

“…A generalização cartográfica é mais do que a aplicação de operadores de generalização (CEBRYKOW, 2017), trata-se de uma tarefa complexa, que exige experiência humana e criatividade (MCMASTER; SHEA, 1992). Apresenta-se como um tópico relevante na exploração de dados geoespaciais na era digital (STOTER et al, 2014;ROCCA et al, 2017;SCHIEWE, 2021;PILEHFOROOSHHA;KARIMI;MANSOURIAN, 2021), entretanto, nos últimos anos, observa-se uma consolidação das atividades de pesquisas científicas relacionadas à essa temática, devido às menores demandas de visualização em ambientes virtuais, quando comparado com produtos impressos (SESTER, 2020). Isso se dá, principalmente, devido ao desenvolvimento do Sistema de Informação Geográfica (SIG) que emprega ferramentas de zoom e camadas monotemáticas simultaneamente (MIÜLLER et al, 1995).…”

Topology Conflict Detection Considering Incremental Updating of Multi-Scale Road Networks

“…For example, owing to the displacement or simplification operation operators, the intersection relationship of two roads becomes a disjointed relationship from large-scale to small-scale, or when two roads before and after updating are both intersection relationships, the relative positions of the two roads have changed greatly after updating, which will affect the practical application of the updated road network (Figure 1b). Most of the previous studies focused on a single scale to detect whether topology conflicts of type I [8][9][10][11][12][13][14] exist. However, there are few studies on detecting type II topology conflicts in different scales caused by incremental update, thus leading to the topology inconsistency and hindering the application of road path query and planning in the updated road data.…”