The space–place dichotomy has long been discussed in geography, psychology, philosophy, and more recently in geographic information science. The attempts to integrate vague notions of place into geographic information systems (GIS) constitute the foundations of the place‐based GIS stream of research, but the rationale and methods for operationalizing place differ considerably in the literature. We present a literature review in an attempt to identify and discuss the distinct yet overlapping frameworks that aim to bridge the gap between space, place, and GIS. The review shows that most studies designed knowledge‐based models in the urban context based on concepts drawn from human geography. Using mixed methods, we synthesize the findings, thus encouraging future research in building new conceptual and methodological models that are able to expand and solidify the scope of place‐based GIS.

When immigrants move to a new city, they tend to develop distinct relationships with the urban landscape, which in turn becomes the new setting of their routine-based activities that evolve over time. Previous works in environmental psychology have quantitatively examined non-native residents' development of sense of place towards their new environment. In this paper, we introduce the spatial perspective into studying the sense of place experienced by non-natives in an urban context. We study the person-place bonds, relationships, and feelings cultivated by non-native residents living in the city of Lisbon (Portugal) through an online map-based survey. Then, we carried out spatial analysis aimed at distinguishing and visualizing the different facets of sense of place developed by two participant groups: short-term residents and long-term residents. Results showed that while short-term residents reported bonds with places, long-term residents' senses of place were more intense and broader throughout the city. The correlations, associations, and relationships between participant groups and the dimensions of sense of place allowed us to observe features and patterns that were previously described in the literature, although adding the spatial lenses can potentially provide better insights for urban planning, community development, and inclusive policies.

The neighborhood is a core unit of analysis in urban research, planning, and policy‐making. However, perceptual and historical processes oftentimes result in neighborhoods that are not tied to sub‐urban jurisdictions. For instance, historic neighborhoods might lack official spatial definitions, hampering neighborhood‐based tasks in local offices. In this case, urban practitioners can benefit from readily available spatial proxies, such as the local street network. In this study, we conducted an exploratory analysis that combines neighborhood mapping and street network modeling. By retrieving participants' sketched boundaries and quantifying spatial orientations of sketched polygons and local network patterns, we were able to measure and compare the relationships between the urban fabric and the perceived extents of two historic neighborhoods in Lisbon, Portugal. The results provided insights for enhancing existing definitions of non‐official neighborhoods, outlining new urban districts as well as for discussions about the role of the urban form in shaping people's perceptions.

Abstract. Participant-based methods aimed at extracting neighbourhood definitions are labour and time intensive. On the other hand, user-generated content (UGC) can provide locations to assess the extent of neighbourhoods. We investigated the definitions of Alfama - a historic neighbourhood in Lisbon (Portugal) - using six sources of UGC and applied a modification of the DBSCAN algorithm developed in the literature. By generating shapes from each source, we were able to visually and quantitatively evaluate their agreement as well as their differences.We demonstrate how different profiles of user activity from each source yielded varied geographies of Alfama. Although discrete representations are not the optimal choice, practical applications such as urban planning usually demand sharp definitions. Lastly, our approach can be extended and improved by adding more sources of UGC data and by picking other case studies.

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