Mining topological relations from the web

Topological relations between geographic regions are of interest in many applications. When the exact boundaries of regions are not available, such relations can be established by analysing natural language information from web documents. In particular we demonstrate how redundancy-based techniques can be used to acquire containment and adjacency relations, and how fuzzy spatial reasoning can be employed to maintain the consistency of the resulting knowledge base

Automated Enrichment of Routing Instructions

Commonly used navigation instructions are based on metric turn descriptions (e.g. “turn left onto Nienburger Straße in 100 m”). For the user it is easy to follow the route, but later it is typically hard to remember how s/he got there. Orientation is based on remarkable objects or locations called landmarks. They are then linked and combined to so-called survey knowledge in the psychological model of a cognitive map. Some of today’s navigation systems also contain landmarks – they are, however, only used at decision points of the route. The goal of this research is to enhance the user's own sense of orientation by enriching common routing instructions with relational hints to landmarks. First, potential landmark objects are defined, extracted from OpenStreetMap and assigned an importance weight. The landmarks are then used to enrich the given routes: In the enrichment process, the influence of the landmarks is modeled as a decline of the weight by distance. Afterwards the most influential landmark is selected for each route segment. The 9-Intersection-Model and an adapted Direction-RelationMatrix are the core methods that are used to analyse and determine the relations between the route and the chosen landmarks. The automatic description of relevant landmarks along a route is implemented as an interactive web-map. The main goal of this paper is the development of the system. Still, a first evaluation was conducted, in order to test the users’ ability of orientation after using enriched instructions compared to users using the classic ones

Geographic information retrieval in a mobile environment: evaluating the needs of mobile individuals

This paper describes research that aims to define the information needs of mobile individuals, to implement a mobile information system that can satisfy those needs, and finally to evaluate the performance of that system with end-users. First a review of the emerging discipline of geographic information retrieval (GIR) is presented as background to the more specific issue of mobile information retrieval. Following this, a user needs study is described evaluating the requirements of potential users of a mobile information system; the study finds that there is a strong geographic component to users' information needs. Next, four geographic post-query filters are described which attempt to represent the region of space associated with an individual's query made at some specific spatial location. These filters are spatial proximity (distance in space), temporal proximity (travel time), speed-heading prediction surfaces (likelihood of visiting locations) and visibility (locations that can be seen). Two of these filters — spatial proximity and speed-heading prediction surfaces — are implemented in a mobile information system and subsequently evaluated with users in an outdoor setting. The results of evaluation suggest that retrieved information to which post-query geographic filters have been applied is considered more relevant than unfiltered information, and that users find information sorted by spatial proximity to be more relevant than that sorted by a prediction surface of likely future locations. The paper closes with a discussion of the wider implications of these results for developers of mobile information systems and location-based services

Investigating behavioural and computational approaches for defining imprecise regions

People often communicate with reference to informally agreedplaces, such as “the city centre”. However, views of the spatial extent of such areas may vary, resulting in imprecise regions. We compare perceptions of Sheffield’s City Centre from a street survey to extents derived from various web-based sources. Such automated approaches have advantages of speed, cost and repeatability. We show that footprints from web sources are often in concordance with models derived from more labour-intensive methods. Notable exceptions however were found with sources advertising or selling residential property. Agreement between sources was measured by aggregating them to identify locations of consensus

Viewpoints on emergent semantics

Authors include:Philippe Cudr´e-Mauroux, and Karl Aberer (editors), Alia I. Abdelmoty, Tiziana Catarci, Ernesto Damiani, Arantxa Illaramendi, Robert Meersman, Erich J. Neuhold, Christine Parent, Kai-Uwe Sattler, Monica Scannapieco, Stefano Spaccapietra, Peter Spyns, and Guy De Tr´eWe introduce a novel view on how to deal with the problems of semantic interoperability in distributed systems. This view is based on the concept of emergent semantics, which sees both the representation of semantics and the discovery of the proper interpretation of symbols as the result of a self-organizing process performed by distributed agents exchanging symbols and having utilities dependent on the proper interpretation of the symbols. This is a complex systems perspective on the problem of dealing with semantics. We highlight some of the distinctive features of our vision and point out preliminary examples of its applicatio

Reflecting Human Knowledge of Place and Route-Choice Behavior Using Big Data

Exploring human knowledge of geographical space and related behavior not only helps in understanding human-environment interactions and dynamic geographic processes, but also advances Geographic Information Systems (GIS) toward a human-centric paradigm to make daily life more efficient. Today’s relatively easy acquisition of various big data provides an unprecedented opportunity for geographers to answer research questions that previously could not be adequately addressed. However, new challenges also arise regarding data quality and bias as well as change in methodology for dealing with big data that are different from traditional data types. Representing people’s perception of place and studying driver’s route-choice behavior are two of the many applications of big data in answering research questions about human knowledge and behavior in the fields of GIS and transportation. Incorporating three papers, this dissertation focuses on these two different applications to achieve the following objectives: 1) examine the degree to which a geographic place’s spatial extent can be estimated from human-generated geotagged photos; 2) address the challenge of geotagged photos’ uneven spatial distribution in place estimation and explore an approach that can better derive a place’s spatial extent; 3) develop a method that can properly estimate the spatial extent of a place that has multiple disjoint regions while considering geotagged photos’ uneven distribution; 4) explore useful spatiotemporal patterns of taxi drivers’ route-choice behavior in a dynamic urban environment. This dissertation makes three major contributions to big data applications’ systematic theory: 1) proposes an effective approach to handling the uneven spatial distribution problem of geotagged photos as a type of volunteered geographic data by modeling their representativeness; 2) develops methods that can properly derive the vague spatial extent of a place with or without disjoint regions; and 3) explores taxi drivers’ route-choice patterns in different situations that can inform future transportation decisions and policy-making processes

Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010

This volume holds the papers from the 18th annual GIS Research UK (GISRUK). This year the conference, hosted at University College London (UCL), from Wednesday 14 to Friday 16 April 2010. The conference covered the areas of core geographic information science research as well as applications domains such as crime and health and technological developments in LBS and the geoweb. UCL’s research mission as a global university is based around a series of Grand Challenges that affect us all, and these were accommodated in GISRUK 2010. The overarching theme this year was “Global Challenges”, with specific focus on the following themes: * Crime and Place * Environmental Change * Intelligent Transport * Public Health and Epidemiology * Simulation and Modelling * London as a global city * The geoweb and neo-geography * Open GIS and Volunteered Geographic Information * Human-Computer Interaction and GIS Traditionally, GISRUK has provided a platform for early career researchers as well as those with a significant track record of achievement in the area. As such, the conference provides a welcome blend of innovative thinking and mature reflection. GISRUK is the premier academic GIS conference in the UK and we are keen to maintain its outstanding record of achievement in developing GIS in the UK and beyond