Topological data analysis (TDA) is an emerging field of research, which considers the application of topology to data analysis. Recently, these methods have been successfully applied to research problems in the field of geographical information science (GIS) and there is much potential for future applications. In this article, we provide an introduction to the fundamentals of TDA for GIS researchers and practitioners and highlight specific benefits that TDA methods provide relative to some conventional methods. We focus on the method of persistent homology, which is the most commonly used TDA method. We describe how persistent homology can be applied to data types commonly encountered in the GIScience domain, namely sets of points, networks and sequences of images. We also describe the application of persistent homology to two specific GIS problems, which are the point pattern analysis of UK city pubs and the analysis of UK rainfall radar imagery. In each case we stress the specific benefits of TDA methods that include, for example, generating an output signature in a form that can be subject to subsequent analyses; identification of void regions in point patterns; and providing a relatively simple method to track objects in spatio-temporal images.

Natural language descriptions of geographical locations are used frequently in daily life and there is a motivation to create systems that generate such descriptions automatically, for purposes such as documentation of where events have taken place, where a person is located, where photos were taken and where plants and animals are located. Typically location descriptions combine references to named geographical features with vague spatial relational terms, such as near, north of and at that relate locations to the features. Here we describe a system for generating location descriptions, that combines spatial templates, that model the applicability of different spatial relations relative to a reference location, with toponyms in the vicinity of the described location that are selected according to aspects of salience. The toponyms are retrieved from a gazetteer service based on OpenStreetMap for which we create a hierarchical feature classification scheme to facilitate selection of toponyms according to distinctiveness of their feature types and other aspects of salience. The advantages of the approach are demonstrated in a user study, relative to an existing state of the art system and to other baseline approaches that include manually created captions and the automated methods of two widely used photo captioning systems.

References to geographic locations are common in text data sources including social media and web pages. They take different forms from simple place names to relative expressions that describe location through a spatial relationship to a reference object (e.g. the house beside the Waikato River). Often complex, multi-word phrases are employed (e.g. the road and railway cross at right angles; the road in line with the canal) where spatial relationships are communicated with various parts of speech including prepositions, verbs, adverbs and adjectives. We address the problem of automatically detecting relative geospatial location descriptions, which we define as those that include spatial relation terms referencing geographic objects, and distinguishing them from non-geographical descriptions of location (e.g. the book on the table). We experiment with several methods for automated classification of text expressions, using features for machine learning that include bag of words that detect distinctive words, word embeddings that encode meanings of words and manually identified language patterns that characterise geospatial expressions. Using three data sets created for this study, we find that ensemble and meta-classifier approaches, that variously combine predictions from several other classifiers with data features, provide the best F-measure of 0.90 for detecting geospatial expressions.

In many instances of the object tracking problem the topological properties of objects can change over time. Such changes include the splitting of an object into multiple objects or merging of multiple objects into a single object. We propose a novel tracking model which is robust to such changes. This model is formulated terms of homology theory whereby 0-dimensional homology classes, which correspond to path-connected components, are tracked. A generalisation of this model for tracking spatially close objects lying in an ambient metric space is also proposed. This generalisation is particularly suitable for tracking spatial-temporal phenomena such as weather phenomena. The utility of the proposed model is demonstrated with respect to tracking rain clouds in radar imagery.

We propose a method for modeling the topology of swarm behavior in a manner which facilitates the application of machine learning techniques such as clustering. This is achieved by modeling the persistence of topological features, such as connected components and holes, of the swarm with respect to time using zig-zag persistent homology. The output of this model is subsequently transformed into a representation known as a persistence landscape. This representation forms a vector space and therefore facilitates the application of machine learning techniques. The proposed model is validated using a real data set corresponding to a swarm of 300 fish. We demonstrate that it may be used to perform clustering of swarm behavior with respect to topological features.

Gazetteers play an essential role in GIS in translating between place name and coordinate-based descriptions of location. The proliferation of location-aware social media applications has led to new sources of gazetteer data, many of which are crowd-sourced. They complement the conventional authoritative resources that are typically linked to published map products. We illustrate the variation in performance of several, mostly social media based, gazetteer resources for a reverse-geocoding photo captioning task and demonstrate the advantage of a meta-gazetteer service that integrates multiple individual gazetteer resources and employs several toponym ranking methods.

Social media sources such as Flickr and Twitter continuously generate large amounts of textual information (tags on Flickr and short messages on Twitter). This textual information is increasingly linked to geographical coordinates, which makes it possible to learn how people refer to places by identifying correlations between the occurrence of terms and the locations of the corresponding social media objects. Recent work has focused on how this potentially rich source of geographic information can be used to estimate geographic coordinates for previously unseen Flickr photos or Twitter messages. In this article, we extend this work by analysing to what extent probabilistic language models trained on Flickr and Twitter can be used to assign coordinates to Wikipedia articles. Our results show that exploiting these language models substantially outperforms both (i) classical gazetteer-based methods (in particular, using Yahoo! Placemaker and Geonames) and (ii) language modelling approaches trained on Wikipedia alone. This supports the hypothesis that social media are important sources of geographic information, which are valuable beyond the scope of individual applications.

The current web is rich in geographically referenced data. Mining, retrieving and sharing these data raises the need for rich geographical place name resources that record spatial and thematic elements of geographical places. Here, possible services offered at a place and human activities that can be practised there are considered useful concepts to discover and encode in place name resources. Recognising this dimension of place description can enhance information retrieval tasks by extending the range of possible queries and search criteria that relate to different place instances. This work proposes an automatic approach for the identification and extraction of service and activity-related concepts from multiple resources of textual descriptions of geographical place types. Frequent affordance patterns are identified and then applied to a corpus of resources to extract service and activity types associated with specific geographical place types. The evaluation experiments undertaken demonstrate the potential value of the approach.

Many aspects of spatial language concerned with relationships between spatial entities are essentially vague. Current GIS technology provides very little support for dealing with this vagueness, partially because there is a lack of quantitative data and models for vague spatial relations. This paper presents an experiment that looks at quantifying spatial prepositions. In the context of image captions, the cardinal directions are analysed in an existing set of image captions, with respect to the spatial distribution of the locations of the target object (figure) and the reference object (ground). Future work will focus on using these results to improve current GIS solutions in a wide variety of scenarios.

The World Wide Web has become the world's largest networked information resource, but references to geographical locations remain unstructured and typically implicit in nature. This lack of explicit spatial knowledge within the Web makes it difficult to service user needs for location-specific information. At present, spatial knowledge is hidden in many small information fragments such as addresses on Web pages, annotated photos with GPS co-ordinates, geographic mapping applications, and geotags in user-generated content. Several emerging formats that primarily or secondarily include location metadata, like GeoRSS, KML, and microformats, aim to improve this state of affairs. However, the question remains how to extract, index, mine, find, view, mashup, and exploit Web content using its location semantics. This work-shop brings together researchers from academia and industry labs to discuss and present the latest results and trends in all facets of the relationships between location concepts and Web information.

Geographical information is recorded in a wide variety of media and document types. There are innumerable paper‐based books, reports, images and maps, and there are computer databases and digital m...

Place names are often used to describe and to enquire about geographical information. It is common for users to employ vernacular names that have vague spatial extent and which do not correspond to the official and administrative place name terminology recorded within typical gazetteers. There is a need therefore to enrich gazetteers with knowledge of such vague places and hence improve the quality of place name‐based information retrieval. Here we describe a method for modelling vague places using knowledge harvested from Web pages. It is found that vague place names are frequently accompanied in text by the names of more precise co‐located places that lie within the extent of the target vague place. Density surface modelling of the frequency of co‐occurrence of such names provides an effective method of representing the inherent uncertainty of the extent of the vague place while also enabling approximate crisp boundaries to be derived from contours if required. The method is evaluated using both precise and vague places. The use of the resulting approximate boundaries is demonstrated using an experimental geographical search engine.

Much of the information stored on the web contains geographical context, but current search engines treat such context in the same way as all other content. In this paper we describe the design, implementation and evaluation of a spatially aware search engine which is capable of handling queries in the form of the triplet of ⟨theme⟩⟨spatial relationship⟩⟨location⟩. The process of identifying geographic references in documents and assigning appropriate footprints to documents, to be stored together with document terms in an appropriate indexing structure allowing real‐time search, is described. Methods allowing users to query and explore results which have been relevance‐ranked in terms of both thematic and spatial relevance have been implanted and a usability study indicates that users are happy with the range of spatial relationships available and intuitively understand how to use such a search engine. Normalised precision for 38 queries, containing four types of spatial relationships, is significantly higher (p<0.001) for searches exploiting spatial information than pure text search.

Geographic information represents our understanding of the association of phenomena with their location on and near the Earth's surface. When presented in map form, an essential aspect of that info...

This paper explores the use of the stochastic optimization technique of simulated annealing for map generalization. An algorithm is presented that performs operations of displacement, size exaggeration, deletion and size reduction of multiple map objects in order to resolve graphic conflict resulting from map scale reduction. It adopts a trial position approach in which each of n discrete polygonal objects is assigned k candidate trial positions that represent the original, displaced, size exaggerated, deleted and size reduced states of the object. This gives rise to a possible kn distinct map configurations; the expectation is that some of these configurations will contain reduced levels of graphic conflict. Finding the configuration with least conflict by means of an exhaustive search is, however, not practical for realistic values of n and k. We show that evaluation of a subset of the configurations, using simulated annealing, can result in effective resolution of graphic conflict.

No abstract available.

A method is presented for generalising cartographic lines using an approach based on determination of their structure. Constrained Delaunay triangulation is used to construct a skeleton of the space surrounding the lines and hence represent line features in terms of skeleton branches. Several statistical measures are used to characterise the triangulation branches. The measures enable selective generalisation of different types of line feature, leading to the possibility of user-specification of the style of generalisation. In our implementation of the approach, the triangulation is updated dynamically to allow both sides of multiple lines to be processed, while guaranteeing topological consistency between the resulting generalised lines.

Gazeteers and geographical thesauri can be regarded as parsimonious spatial models that associate geographical location with place names and encode some semantic relations between the names. They are of particular value in processing information retrieval requests in which the user employs place names to specify geographical context. Typically the geometric locational data in a gazetteer are confined to a simple footprint in the form of a centroid or a minimum bounding rectangle, both of which can be used to link to a map but are of limited value in determining spatial relationships. Here we describe a Voronoi diagram method for generating approximate regional extents from sets of centroids that are respectively inside and external to a region. The resulting approximations provide measures of areal extent and can be used to assist in answering geographical queries by evaluating spatial relationships such as distance, direction and common boundary length. Preliminary experimental evaluations of the method have been performed in the context of a semantic modelling system that combines the centroid data with hierarchical and adjacency relations between the associated place names.

This paper focuses on the consistency issues related to integrating multiple sets of spatial data in spatial information systems such as Geographic Information Systems (GISs). Data sets to be integrated are assumed to hold information about the same geographic features which can be drawn from different sources at different times, which may vary in reliability and accuracy, and which may vary in the scale of presentation resulting in possible multiple spatial representations for these features. A systematic approach is proposed which relies first on breaking down the consistency issue by identifying a range of consistency classes which can be checked in isolation. These classes are a representative set of properties and relationships which can completely identify the geographic objects in the data sets. Different levels of consistency are then proposed, namely, total, partial and conditional, which can be checked for every consistency class. This provides the flexibility for two data sets to be integrated without necessarily being totally consistent in every aspect. The second step of the proposed approach is to explicitly represent the different classes and levels of consistency in the system. As an example, a simple structure which stores adjacency relationships is given which can be used for the explicit representation of topological consistency. The paper also proposes that the set of consistent knowledge in the data sets (which is mostly qualitative) be explicitly represented in the database and that uncertainty or ambiguity inherent in the knowledge be represented as well.

Growth in the available quantities of digital geographical data has led to major problems in maintaining and integrating data from multiple sources, required by users at differing levels of generalization. Existing GIS and associated database management systems provide few facilities specifically intended for handling spatial data at multiple scales and require time consuming manual intervention to control update and retain consistency between representations. In this paper the GEODYSSEY conceptual design for a multi-scale, multiple representation spatial database is presented and the results of experimental implementation of several aspects of the design are described. Object-oriented, deductive and procedural programming techniques have been applied in several contexts: automated update software, using probabilistic reasoning; deductive query processing using explicit stored semantic and spatial relations combined with geometric data; multiresolution spatial data access methods combining poini, line, area and surface geometry; and triangulation-based generalization software that detects and resolves topological inconsistency.

Multiresolution data structures provide a means of retrieving geographical features from a database at levels of detail which are adaptable to different scales of representation. A database design is presented which integrates multi-scale storage of point, linear and polygonal features, based on the line generalization tree, with a multi-scale surface model based on the Delaunay pyramid. The constituent vertices of topologically-structured geographical features are thus distributed between the triangulated levels of a Delaunay pyramid in which triangle edges are constrained to follow those features at differing degrees of generalization. Efficient locational access is achieved by imposing a spatial index on each level of the pyramid.

The accumulation of geological information in digital form, due to modern exploration methods, has introduced the possibility of applying geographical information system technology to the field of geology. To achieve the benefits in information management and in data analysis and interpretation, however, it will be necessary to develop spatial models and associated data structures which are specifically designed for working in three dimensions. Some progress in this direction has already been demonstrated, with the application of octree spatial subdivision techniques to the storage of uniform volume elements representing mineral properties. By imposing octree tessellations on more precisely-defined geometric data, such as triangulated surfaces and polygon line segments, it may now be possible to combine efficient spatial addressing with topologically-coded boundary representations of geological strata. The development of storage schemes capable of representing such geological boundary models at different scales poses a particular problem, a possible solution to which may be by means of hierarchical classification of the vertices of triangulated surfaces according to shape contribution.