The spatial configuration of local climate zones reveals effects on wayfinding in human walking

standardized built types (LCZ1—LCZ10) and seven land cover types (LCZ A—LCZ G) [19]. The LCZ classification provides more details about the urban environment, such as building density and heights, than simply using “urban” or “impervious surface” which is the case in conventional land use classifications. The LCZ classification has been widely used in urban climate studies to represent local microclimates [20]. For example, some studies linked the configuration metrics using LCZ types with air quality [21] and surface temperature [22]. Therefore, our study can be the first attempt to extend the LCZ classification system beyond urban climate studies to the wayfinding field in spatial planning. Quantifying landscape met- rics among different LCZ types allows for demonstrating spatial configurations of both sur- face structures in terms of built-up types and surface covers in terms of land cover types. As a result, incorporating LCZ classification system and landscape metrics-based spatial config- uration analysis provides opportunities for modifying land covers and built-up areas for improving wayfinding. By combining space syntax-based wayfinding and LCZ-based landscape metrics quantifica- tion of urban form, this study tested the hypothesis that spatial configurations (e.g., agglomera- tion or separation) influence wayfinding via LCZ reconfiguration. Our three specific objectives are: 1) quantifying wayfinding using space syntax technique and urban forms using landscape metrics of LCZ types; 2) identifying possible statistical relationships between quanti-

tative wayfinding and LCZ-based urban forms; 3) suggesting reconfiguration strategies of LCZ types for improving wayfinding. This study is structured into five parts. The data, methods, and technical details of measuring wayfinding, mapping LCZ types, and quantifying landscape metrics are described in Section 2. Section 3 delineates the empirical results of heterogeneous wayfinding among cities, quantitative spatial configurations of LCZ types, and their statistical correlations. The implications for wayfinding measurements and urban spatial modifications are discussed in Section 4. Section 5 presents the study conclusions. 2. Data and methods 2.1 Analytical framework The analytical framework for revealing the effects of urban spatial configurations on wayfind- ing is depicted in Fig 1, presented in four parts. Firstly, to extract spatial characteristic informa- tion, the local climate zone (LCZ) classification was used to categorize urban forms and their spatial configurations were quantified by landscape metrics using the FRAGSTATS tool. The values of landscape metrics for each LCZ type were used as proxies for quantitative urban spa- tial configurations. Moreover, to describe the wayfinding in current urban forms, an intelligi- bility indicator derived from the space syntax was used to measure wayfinding objectively using spatial design network analysis. The value of the intelligibility indicator was used to rep- resent people’s ability to navigate through a city. After the quantifications of both urban spatial

configuration and wayfinding, the third step in this analytical framework is to capture their quantitative relationships. Correlation analysis was thus used to identify the positive or nega- tive relationships between landscape metrics of LCZs and wayfinding. Developing spatial reconfigurations strategies based on correlation results was the final step, allowing planners to decide whether dispersed or agglomerated urban forms were better for people’s wayfinding. Positive correlations indicate a potential improvement in wayfinding by increasing the values of landscape metrics. Additionally, using a hot spot analysis, the spatial clusters of landscape metrics were demonstrated to determine the priority locations for implementing those sug- gested strategies. The strategies and the locations for spatial reconfiguration were the major outputs of this study. PLOS ONE The spatial configuration for wayfinding PLOS ONE | https://doi.org/10.1371/journal.pone.0289780 September 8, 2023 3 / 18