Qualitative spatial logics for buffered geometries

This paper describes a series of new qualitative spatial logics for checking consistency of sameAs and partOf matches between spatial objects from different geospatial datasets, especially from crowd-sourced datasets. Since geometries in crowd-sourced data are usually not very accurate or precise, we buffer geometries by a margin of error or a level of tolerance a E R≥0, and define spatial relations for buffered geometries. The spatial logics formalize the notions of 'buffered equal' (intuitively corresponding to `possibly sameAs'), 'buffered part of' ('possibly partOf'), 'near' (`possibly connected') and 'far' ('definitely disconnected'). A sound and complete axiomatisation of each logic is provided with respect to models based on metric spaces. For each of the logics, the satisfiability problem is shown to be NP-complete. Finally, we briefly describe how the logics are used in a system for generating and debugging matches between spatial objects, and report positive experimental evaluation results for the system

A logic of directions

We propose a logic of directions for points (LD)over 2D Euclidean space, which formalises primary direction relations east (E), west (W), and indeterminate east/west (Iew), north (N), south (S) and indeterminate north/south (Ins). We provide a sound and complete axiomatisation of it, and prove that its satisfiability problem is NP-complete

Using qualitative spatial logic for validating crowd-sourced geospatial data

We describe a tool, MatchMaps, that generates sameAs and partOf matches between spatial objects (such as shops, shopping centres, etc.) in crowd-sourced and authoritative geospatial datasets. MatchMaps uses reasoning in qualitative spatial logic, description logic and truth maintenance techniques, to produce a consistent set of matches. We report the results of an initial eval- uation of MatchMaps by experts from Ordnance Survey (Great Britain’s National Mapping Authority). In both the case studies considered, MatchMaps was able to correctly match spatial objects (high precision and recall) with minimal human intervention

Using qualitative spatial logic for validating crowd-sourced geospatial data

We describe a tool, MatchMaps, that generates sameAs and partOf matches between spatial objects (such as shops, shopping centres, etc.) in crowd-sourced and authoritative geospatial datasets. MatchMaps uses reasoning in qualitative spatial logic, description logic and truth maintenance techniques, to produce a consistent set of matches. We report the results of an initial eval- uation of MatchMaps by experts from Ordnance Survey (Great Britain’s National Mapping Authority). In both the case studies considered, MatchMaps was able to correctly match spatial objects (high precision and recall) with minimal human intervention

Matching disparate geospatial datasets and validating matches using spatial logic

In recent years, the emergence and development of crowd-sourced geospatial data has provided challenges and opportunities to national mapping agencies as well as commercial mapping organisations. Crowd-sourced data involves non-specialists in data collection, sharing and maintenance. Compared to authoritative geospatial data, which is collected by surveyors or other geodata professionals, crowd-sourced data is less accurate and less structured, but often provides richer user-based information and reflects real world changes more quickly at a much lower cost. In order to maximize the synergistic use of authoritative and crowd-sourced geospatial data, this research investigates the problem of how to establish and validate correspondences (matches) between spatial features from disparate geospatial datasets. To reason about and validate matches between spatial features, a series of new qualitative spatial logics was developed. Their soundness, completeness, decidability and complexity theorems were proved for models based on a metric space. A software tool `MatchMaps' was developed, which generates matches using location and lexical information, and verifies consistency of matches using reasoning in description logic and qualitative spatial logic. MatchMaps was evaluated by the author and experts from Ordnance Survey, the national mapping agency of Great Britain. In experiments, it achieved high precision and recall, as well as reduced human effort. The methodology developed and implemented in MatchMaps has a wider application than matching authoritative and crowd-sourced data and could be applied wherever it is necessary to match two geospatial datasets of vector data

Matching disparate geospatial datasets and validating matches using spatial logic

In recent years, the emergence and development of crowd-sourced geospatial data has provided challenges and opportunities to national mapping agencies as well as commercial mapping organisations. Crowd-sourced data involves non-specialists in data collection, sharing and maintenance. Compared to authoritative geospatial data, which is collected by surveyors or other geodata professionals, crowd-sourced data is less accurate and less structured, but often provides richer user-based information and reflects real world changes more quickly at a much lower cost. In order to maximize the synergistic use of authoritative and crowd-sourced geospatial data, this research investigates the problem of how to establish and validate correspondences (matches) between spatial features from disparate geospatial datasets. To reason about and validate matches between spatial features, a series of new qualitative spatial logics was developed. Their soundness, completeness, decidability and complexity theorems were proved for models based on a metric space. A software tool `MatchMaps' was developed, which generates matches using location and lexical information, and verifies consistency of matches using reasoning in description logic and qualitative spatial logic. MatchMaps was evaluated by the author and experts from Ordnance Survey, the national mapping agency of Great Britain. In experiments, it achieved high precision and recall, as well as reduced human effort. The methodology developed and implemented in MatchMaps has a wider application than matching authoritative and crowd-sourced data and could be applied wherever it is necessary to match two geospatial datasets of vector data

A logic of directions

We propose a logic of directions for points (LD)over 2D Euclidean space, which formalises primary direction relations east (E), west (W), and indeterminate east/west (Iew), north (N), south (S) and indeterminate north/south (Ins). We provide a sound and complete axiomatisation of it, and prove that its satisfiability problem is NP-complete

A logic of directions

We propose a logic of directions for points (LD)over 2D Euclidean space, which formalises primary direction relations east (E), west (W), and indeterminate east/west (Iew), north (N), south (S) and indeterminate north/south (Ins). We provide a sound and complete axiomatisation of it, and prove that its satisfiability problem is NP-complete

A Logic of East and West

We propose a logic of east and west (LEW) for points in 1D Euclidean space. It formalises primitive direction relations: east (E), west (W) and indeterminate east/west (Iew). It has a parameter τ ∈ ℕ&gt;1, which is referred to as the level of indeterminacy in directions. For every τ ∈ ℕ&gt;1, we provide a sound and complete axiomatisation of LEW, and prove that its satisfiability problem is NP-complete. In addition, we show that the finite axiomatisability of LEW depends on τ: if τ = 2 or τ = 3, then there exists a finite sound and complete axiomatisation; if τ &gt; 3, then the logic is not finitely axiomatisable. LEW can be easily extended to higher-dimensional Euclidean spaces. Extending LEW to 2D Euclidean space makes it suitable for reasoning about not perfectly aligned representations of the same spatial objects in different datasets, for example, in crowd-sourced digital maps.</p

Theorising affective habitus in historical geographies of mobilities: unfolding spatio-temporal modalities

This essay applies a case study approach to theorise a research agenda for critical explorations of emotions and mobilities centred on three core concepts and key phenomena: affective habitus, spatio-temporal modalities and historical geographies. The analysis offers novel perspectives on the interplay between the affectivity of geographies of social difference and the multiscalar dynamics shaping social relations through mobility. This is demonstrated in how emotions linked to agency provide a generative lens to explore how social relationships and political subjectivities intersect to inform mobile identities/lifeworlds. The case studies offer critical insights of how migrants/refugees/indigenous people in navigating challenging structural conditions can reflect conceptualisations of the mutually constitutive contexts of emotionality and intersectional inequity with indigeneity and (im)mobility. A temporal-historical lens reveals how emotional mobilities are shaped by structural/social dynamics including, but not limited to, trauma and exclusion, historical divisions, cultural identities, border and racialised regimes, intergenerationality. These exemplifications through a case study empirical lens draw from research focusing on indigenous and Palestinian peoples