Neural factoid geospatial question answering

Existing question answering systems struggle to answer factoid questions when geospatial information is involved. This is because most systems cannot accurately detect the geospatial semantic elements from the natural language questions, or capture the semantic relationships between those elements. In this paper, we propose a geospatial semantic encoding schema and a semantic graph representation which captures the semantic relations and dependencies in geospatial questions. We demonstrate that our proposed graph representation approach aids in the translation from natural language to a formal, executable expression in a query language. To decrease the need for people to provide explanatory information as part of their question and make the translation fully automatic, we treat the semantic encoding of the question as a sequential tagging task, and the graph generation of the query as a semantic dependency parsing task. We apply neural network approaches to automatically encode the geospatial questions into spatial semantic graph representations. Compared with current template-based approaches, our method generalises to a broader range of questions, including those with complex syntax and semantics. Our proposed approach achieves better results on GeoData201 than existing methods.

Interdisciplinary perspectives on place

Editorial for the Special Feature on Interdisciplinary Perspectives on Place.

Identifying regional variation in place visit behavior during a global pandemic

The emergence of the SARS-CoV-2 virus in 2019 lead to a global pandemic that altered the activity behavior of most people on our planet. While government regulations and public concern modified visitation patterns to places of interest, little research has examined the nuanced changes in the length of time someone spends at a place, nor the regional variability of these changes. In this work, we examine place visit duration in four major U.S. cities, identify which place types saw the largest and smallest changes, and quantify variation between cities. Furthermore, we identify socio-economic and demographic factors that contribute to changes in visit duration and demonstrate the varying influence of these factors by region. The results of our analysis indicate that the pandemic's impact on visiting behavior varies between cities, though there are commonalities found in certain types of places. Our findings suggest that places of interest within lower income communities experienced less change in visit duration than others. An increase in the percentage of younger, Black or Hispanic populations within a community also resulted in a smaller decrease in visit duration than in other communities. These findings offer insight into the factors that contribute to changes in visiting behavior and the resilience of communities to a global pandemic.

Sense of place and the city: the case of non-native residents in Lisbon

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 semantics of place-related questions

The trend to equip information systems with question-answering capabilities raises the design problem of deciding which questions a system should be able to answer. Typical solutions build on mining human conversations or logs from similar systems for question patterns. For the case of questions about geographic places, we present a complementary approach, showing how to derive possible questions from an ontology of spatial information and a classification of place facets. We argue that such an approach reduces the inherent and substantial data bias of current solutions. At a more general level, we provide a novel understanding of spatial questions and their role in designing and using spatial information systems.

Using textual volunteered geographic information to model nature-based activities: A case study from Aotearoa New Zealand

A boom in volunteered geographic information has led to extensive data-driven exploration and modeling of places. While many studies have used such data to explore human-environment interaction in urban settings, few have investigated natural, non-urban settings. To address this gap, this study systematically explores the content of online reviews of nature-based recreation activities, and develops a fine-grained hierarchical model that includes 28 aspects grouped into three main domains: activity, settings, and emotions/cognition. It further demonstrates how the model can be used to explore the variation in recreation experiences across activities, setting the stage for the analysis of the spatio-temporal variations in recreation experiences in the future. Importantly, the study provides an annotated corpus that can be used as a training dataset for developing methods to automatically capture aspects of recreation experiences in texts.

Deriving topological relations from topologically augmented direction relation matrices

Topological relations and direction relations represent two pieces of the qualitative spatial reasoning triumvirate. Researchers have previously attempted to use the direction relation matrix to derive a topological relation, finding that no single direction relation matrix can isolate a particular topological relation. In this paper, the technique of topological augmentation is applied to the same problem, identifying a unique topological relation in 28.6% of all topologically augmented direction relation matrices, and furthermore achieving a reduction in a further 40.4% of topologically augmented direction relation matrices when compared to their vanilla direction relation matrix counterpart.