Spatial Data Retrieval Research Articles

A parallel approach for improving Geo-SPARQL query performance

Geospatial Semantic Web promises better retrieval geospatial information for Digital Earth systems by explicitly representing the semantics of data through ontologies. It also promotes sharing and reuse of geospatial data by encoding it in Semantic Web languages, such as RDF, to form geospatial knowledge base. For many applications, rapid retrieval of spatial data from the knowledge base is critical. However, spatial data retrieval using the standard Semantic Web query language – Geo-SPARQL – can be very inefficient because the data in the knowledge base are no longer indexed to support efficient spatial queries. While recent research has been devoted to improving query performance on general knowledge base, it is still challenging to support efficient query of the spatial data with complex topological relationships. This research introduces a query strategy to improve the query performance of geospatial knowledge base by creating spatial indexing on-the-fly to prune the search space for spatial queries and by parallelizing the spatial join computations within the queries. We focus on improving the performance of Geo-SPARQL queries on knowledge bases encoded in RDF. Our initial experiments show that the proposed strategy can greatly reduce the runtime costs of Geo-SPARQL query through on-the-fly spatial indexing and parallel execution.

An Efficient Spatial Data Index Based On Gossip for Overlay Networks

In large and highly dynamic distributed environments, the retrieval of spatial data entails some challenges such as network topology, indexing efficiency, and mapping methods for multidimensional spatial data. Conventional methods may not allow for the complex retrieval of multidimensional spatial data in an efficient manner. This paper proposes an overlay network for indexing spatial data based on gossip. The proposed network, referred to as the 2D-Ring, has a ring-like topology with a spatial data index. First, the paper introduces a protocol for constructing an overlay network for indexing spatial data and then presents a method for mapping the data onto the 2D-Ring by using a distributed quadtree and control points. The results of a comprehensive experiment for an evaluation of the performance of the 2D-Ring with respect to various features indicate that the 2D-Ring converges logarithmically to network size, has desirable small-world properties, and is robust across dynamic scenarios. The proposed solution can be applied not only to overlay networks but also to other types of networks requiring the sharing of distributed data sets.

Space–time measurements of oceanic sea states

Stereo video techniques are effective for estimating the space–time wave dynamics over an area of the ocean. Indeed, a stereo camera view allows retrieval of both spatial and temporal data whose statistical content is richer than that of time series data retrieved from point wave probes. We present an application of the Wave Acquisition Stereo System (WASS) for the analysis of offshore video measurements of gravity waves in the Northern Adriatic Sea and near the southern seashore of the Crimean peninsula, in the Black Sea. We use classical epipolar techniques to reconstruct the sea surface from the stereo pairs sequentially in time, viz. a sequence of spatial snapshots. We also present a variational approach that exploits the entire data image set providing a global space–time imaging of the sea surface, viz. simultaneous reconstruction of several spatial snapshots of the surface in order to guarantee continuity of the sea surface both in space and time. Analysis of the WASS measurements show that the sea surface can be accurately estimated in space and time together, yielding associated directional spectra and wave statistics at a point in time that agrees well with probabilistic models. In particular, WASS stereo imaging is able to capture typical features of the wave surface, especially the crest-to-trough asymmetry due to second order nonlinearities, and the observed shape of large waves are fairly described by theoretical models based on the theory of quasi-determinism (Boccotti, 2000). Further, we investigate space–time extremes of the observed stationary sea states, viz. the largest surface wave heights expected over a given area during the sea state duration. The WASS analysis provides the first experimental proof that a space–time extreme is generally larger than that observed in time via point measurements, in agreement with the predictions based on stochastic theories for global maxima of Gaussian fields.

Local Mapping Based Modeling Sensor Network Data Algorithm for Query Processing

In Wireless Sensor Network (WSN), sensors are devices used to collect data from the environment related to the detection or measurement of physical phenomena. The original sensor network data are commonly large amounts of measurements and high-dimensional. Spatial data mining techniques used to retrieve high-dimensional spatial information from WSN is effectively. Due to the limited energy of the sensors in WSN, energy efficient query evaluation is critical to prolong the system lifetime. In this paper, we propose a local mapping based modeling sensor network data algorithm for query processing to render effective spatial data retrieval services in the resource constrained WSN. The algorithm can be associated with the present features in spatial data and project high-dimensional data to feature space by using local mapping linear embedding for reducing the computation of spatial data retrieval. As the experiment results shown, the algorithm can preserve important spatial feature information and provide effective preprocessing analysis results. Furthermore, the algorithm is the more effectual on feature preserving than local linear embedding (LLE) when the sample space is sparse source data.

Offshore stereo measurements of gravity waves

Stereo video techniques are effective for estimating the space-time wave dynamics over an area of the ocean. Indeed, a stereo camera view allows retrieval of both spatial and temporal data whose statistical content is richer than that of time series data retrieved from point wave probes. To prove this, we consider an application of the Wave Acquisition Stereo System (WASS) for the analysis of offshore video measurements of gravity waves in the Northern Adriatic Sea. In particular, we deployed WASS at the oceanographic platform Acqua Alta, off the Venice coast, Italy. Three experimental studies were performed, and the overlapping field of view of the acquired stereo images covered an area of approximately 1100m2. Analysis of the WASS measurements show that the sea surface can be accurately estimated in space and time together, yielding associated directional spectra and wave statistics that agree well with theoretical models. From the observed wavenumber-frequency spectrum one can also predict the vertical profile of the current flow underneath the wave surface. Finally, future improvements of WASS and applications are discussed.

Gossip-Based Indexing Ring Topology for 2-Dimension Spatial Data in Overlay Networks

Overlay networks are used widely in the Internet, such as retrieval and share of files, multimedia games and so on. However, in distributed system, the retrieval and share of 2-dimension spatial data still have some difficult problems and can not solve the complex retrieval of 2-dimension spatial data efficiently. This article presents a new indexing overlay networks, named 2D-Ring, which is the ring topology based on gossip for 2-dimension spatial data. The peers in our overlay networks exchange the information periodically and update each local view by constructing algorithm. 2-dimension spatial data is divided by quad-tree and mapped into control points, which are hashed into 2D-Ring by SHA-1 hash function. In such way, the problem of 2-dimension spatial data indexing is converted to the problem of searching peers in the 2D-Ring. A large of extensive experiments show that the time complexity of constructing algorithm of 2D-Ring can reach convergence logarithmically as a function of the network size and hold higher hit rate and lower query delay.

Toward semantics-aware annotation and retrieval of spatial data

The retrieval of spatial resources is typically hindered by the lack of exhaustive metadata, linguistic issues, multilingualism, and domain-related terminology mismatches. This paper describes an experimental attempt to set up a knowledge base that will serve as groundwork for harmonising domain knowledge from distinct thematic areas, to enable the semantics-aware annotation of resources, and to support the implementation of novel discovery techniques. Setting this up also required establishing a general work flow for translating ISO-compliant registries into SKOS/RDF data structures and enriching them with structural information. These steps are also presented. The validity of the approach is then evaluated by analysing various applications’ exploitation of the knowledge base in diverse use cases.

An emission time series generator for pollutant release modelling in urban areas

Dynamic priority pollutant (PP) fate models are being developed to assess appropriate strategies for limiting the release of PPs from urban sources and for treating PPs on a variety of spatial scales. Different possible sources of PP releases were mapped and both their release pattern and release factors were quantified as detailed as possible. This paper focuses on the link between the gathered PP sources data and the dynamic models of the urban environment. This link consists of (1) a method for the quantitative and structured storage of temporal emission pattern information, (2) the retrieval of spatial emission source data from a GIS covering the studied urban area, (3) the coupling of the (GIS-based) spatial emission source data with temporal emission pattern information and (4) the generation of PP release time series to feed the dynamic sewer catchment model. Steps 3 and 4 were included as the main features of a dedicated software tool. Finally, this paper also illustrates the method's applicability to generate model input time series for generic pollutants (N, P and COD/BOD) in addition to priority pollutants.

Comparison of Optical Sensor-Based Spatial Data Collection Techniques for Civil Infrastructure Modeling

Infrastructure modeling refers to the process of collecting infrastructure spatial data and transforming them into structured representations. It is useful during all stages of the infrastructure life cycle, and plays an important role in infrastructure's development and rehabilitation applications. In order to facilitate infrastructure modeling, a variety of optical spatial data collection techniques are available. None of them is ideal for all infrastructure applications. Each has its own benefits and limitations. The main purpose of this paper is to select an appropriate technique based on the given infrastructure application requirements. To achieve this goal, the principles of these techniques are first investigated. Their benefits and limitations are identified by comparing them in aspects such as accuracy, automation of spatial data retrieval, instrument cost, and portability. This way, the relationships between techniques and the requirements of civil infrastructure applications are established and compiled in tables. Practitioners can easily select an appropriate technique for their own applications by consulting these tables.

Topological feature vectors for exploring topological relationships

Topological relationships between spatial objects such as overlap, disjoint, and inside have for a long time been a focus of research in a number of disciplines like cognitive science, robotics, linguistics, artificial intelligence, and spatial reasoning. In particular as predicates, they support the design of suitable query languages for spatial data retrieval and analysis in spatial database systems and Geographic Information Systems. While conceptual aspects of topological predicates (like their definition and reasoning with them) as well as strategies for avoiding unnecessary or repetitive predicate evaluations (like predicate migration and spatial index structures) have been emphasized, the development of correct and efficient implementation techniques for them has been rather neglected. Recently, the design of topological predicates for different combinations of complex spatial data types has led to a large increase of their numbers and accentuated the need for their efficient implementation. The goal of this article is to develop efficient implementation techniques of topological predicates for all combinations of the complex spatial data types point2D, line2D, and region2D, as they have been specified by different authors and in different commercial and public domain software packages. Our solution is a two‐phase approach. In the exploration phase, for a given scene of two spatial objects, all topological events like intersection and meeting situations are recorded in two precisely defined topological feature vectors (one for each argument object of a topological predicate) whose specifications are characteristic and unique for each combination of spatial data types. These vectors serve as input for the evaluation phase which analyzes the topological events and determines the Boolean result of a topological predicate or the kind of topological predicate. This paper puts an emphasis on the exploration phase and the definition of the topological feature vectors. In addition, it presents a straightforward evaluation method.

Mapping the Sensitivity to oil spill of the Santos basin coastline, Southeast Brazil

For the last ten years new offshore oil fields were brought into production in the Santos Basin. This has led to an increase in the processing and transportation of crude oil and its derived products, hence posing new threats to the integrity of coastal environments and human resources. The Brazilian Ministry of Environment responded by coordinating an initiative aimed at mapping the sensitivity to oil spill of the Brazilian coastline. The results for the Santos Basin are presented here, for which the appropriate technologies had to be integrated in order to cover over 1300 km of the coastal environment. A partnership between public and private sectors was established in order to achieve high-quality mapping standards by sharing data and expertise. A total of ten ETM+ Landsat images have been mosaicked and processed using spectral image techniques such as restoration and band fusion. Remote sensing and field data have been organized into a digital database following an object-oriented model devised to allow the retrieval and upgrading of spatial and tabular data. These procedures are now standard practices for mapping the sensitivity to oil spill of other marine basins in Brazil. A total of 44 maps have been produced in three different geographic scales for specific contingency planning and spill scenarios. Parana state has 82% of its coastline occupied by mangrove vegetation, the most sensitive ecosystem. In contrast, 52% of the Rio de Janeiro coastline are composed of different types of rocky shores, from vertical impermeable substrates to thalus deposits. Rio de Janeiro also has the largest proportion of sandy substrates, with 41% of its coastline. Many other diagnostic information and quantitative analyses can be carried out by querying the available geographic database, which are necessary for any contingency planning and emergency response actions.

Volunteered geographic information: key questions, concepts and methods to guide emerging research and practice

New web services that support user-generated and user-modified maps and spatial data are continuing to emerge at a rapid pace, as are geo-enabled digital devices that can collect and disseminate data with spatial attributes. Interactive web services such as GoogleMaps or Wikimapia allow users to create their own maps online or contribute to and edit geographic information contributed by others. Users may import or ‘mash up’ shared source codes (application programming interfaces or ‘‘APIs’’) into their own web mapping services, or use markup languages to ‘geotag’ online content such as photographs with information about their geographic location. New forms of digital spatial data are created through a growing proportion of our daily activities, such as using electronic payment cards to board a bus whose location is tracked by the public transit agency, or using GPS-enabled cell phones that trace our location and movements throughout the day. These technologies and practices are dramatically altering the contexts of geospatial data creation and sharing, the individuals and institutions who act as data producers and users, and perhaps most strikingly, geospatial data themselves. This special issue contributes to a growing body of research investigating the technological, social, and political opportunities, limitations, and implications of these phenomena. The authors examine whether existing structures and practices for spatial data collection, retrieval, validation, and dissemination are appropriate in this new context; the purposes for which these new forms of spatial data might be used; how these new technologies and practices affect (and are shaped by) the so-called ‘digital divide’; and what social and political practices may be advanced in connection with these new technologies and data. Research on these new geospatial technologies and forms of data is still nascent enough that a central line of discussion remains how to name these phenomena and the activities they enable. Terms such as neogeography (Turner 2006; Sui 2008), ubiquitous cartography (Gartner et al. 2007), and web mapping (Plewe 2007) emphasize cartographic representation, speaking to ways in which interactive web mapping services might open the practices of cartography and geospatial data creation to new actors. In contrast, others forward terms such as user-generated content (Sieber 2007), collaboratively contributed geographic information (Bishr and Mantelas this issue), and volunteered geographic information (Goodchild 2007). This second group of terms emphasizes the data themselves, highlighting shifts in the forms of spatial information that are available and in the processes through which they are created and used. These naming debates are important in part because they focus our attention on those concepts that are key to understanding this new phenomenon, and help S. Elwood (&) Department of Geography, University of Washington, Box 353550, Seattle, WA 98195, USA e-mail: selwood@u.washington.edu

Efficient Implementation Techniques for Topological Predicates on Complex Spatial Objects

Topological relationships like overlap, inside, meet, and disjoint uniquely characterize the relative position between objects in space. For a long time, they have been a focus of interdisciplinary research as in artificial intelligence, cognitive science, linguistics, robotics, and spatial reasoning. Especially as predicates, they support the design of suitable query languages for spatial data retrieval and analysis in spatial database systems and geographical information systems. While, to a large extent, conceptual aspects of topological predicates (like their definition and reasoning with them) as well as strategies for avoiding unnecessary or repetitive predicate executions (like predicate migration and spatial index structures) have been emphasized, the development of robust and efficient implementation techniques for them has been largely neglected. Especially the recent design of topological predicates for all combinations of complex spatial data types has resulted in a large increase of their numbers and stressed the importance of their efficient implementation. The goal of this article is to develop correct and efficient implementation techniques of topological predicates for all combinations of complex spatial data types including two-dimensional point, line, and region objects, as they have been specified by different authors and in different commercial and public domain software packages. Our solution consists of two phases. In the exploration phase, for a given scene of two spatial objects, all topological events like intersection and meeting situations are summarized in two precisely defined topological feature vectors (one for each argument object of a topological predicate) whose specifications are characteristic and unique for each combination of spatial data types. These vectors serve as input for the evaluation phase which analyzes the topological events and determines the Boolean result of a topological predicate (predicate verification) or the kind of topological predicate (predicate determination) by a formally defined method called nine-intersection matrix characterization. Besides this general evaluation method, the article presents an optimized method for predicate verification, called matrix thinning, and an optimized method for predicate determination, called minimum cost decision tree. The methods presented in this article are applicable to all known complete collections of mutually exclusive topological predicates that are formally based on the well known nine-intersection model.

Topological relationships between complex spatial objects

For a long time topological relationships between spatial objects have been a focus of research in a number of disciplines like artificial intelligence, cognitive science, linguistics, robotics, and spatial reasoning. Especially as predicates they support the design of suitable query languages for spatial data retrieval and analysis in spatial databases and geographical information systems (GIS). Unfortunately, they have so far only been defined for and applicable to simplified abstractions of spatial objects like single points, continuous lines, and simple regions. With the introduction of complex spatial data types an issue arises regarding the design, definition, and number of topological relationships operating on these complex types. This article closes this gap and first introduces definitions of general and versatile spatial data types for complex points , complex lines , and complex regions . Based on the well known 9-intersection model, it then determines the complete sets of mutually exclusive topological relationships for all type combinations. Completeness and mutual exclusion are shown by a proof technique called proof-by-constraint-and-drawing . Due to the resulting large numbers of predicates and the difficulty of handling them, the user is provided with the concepts of topological cluster predicates and topological predicate groups , which permit one to reduce the number of predicates to be dealt with in a user-defined and/or application-specific manner.

Geographical information systems and location science

Since the 1970s the field of Geographical Information Systems (GIS) has evolved into a mature research and application area involving a number of academic fields including Geography, Civil Engineering, Computer Science, Land Use Planning, and Environmental Science. GIS can support a wide range of spatial queries that can be used to support location studies. GIS will play a significant role in future location model development and application. We review existing work that forms the interface between GIS and Location Science and discuss some of the potential research areas involving both GIS and Location Science. Scope and purpose During the past 30 years there have been many developments in spatial data analysis, spatial data storage and retrieval, and mapping. Many of these developments have occurred in the field of Geographical Information Science. Geographical Information Systems software now supports many elementary and advanced spatial analytic approaches including the production of high quality maps. GIS will have a major impact on the field of Location Science in terms of model application and model development. The purpose of this paper is to explore the interface between the field of Location Science and GIS.

Generating spatiotemporal datasets on the WWW

Efficient storage, indexing and retrieval of time-evolving spatial data are some of the tasks that a Spatiotemporal Database Management System (STDBMS) must support. Aiming at designers of indexing methods and access structures, in this article we review the GSTD algorithm for generating spatiotemporal datasets according to several user-defined parameters, and introduce a WWW-based environment for generating and visualizing such datasets. The GSTD interface is available at two main sites: http://www.cti.gr/RD3/GSTD/ and http://www.cs.ualberta.ca/~mn/GSTD/.

Potential meets reality: GIS and public health research in Australia

AbstractGeographical Information Systems-computerised systems for the capture, storage, retrieval, analysis and display of spatial data - have recently been promoted as important tools for the study of public health. Attention must also be given to the issues involved in this relatively new application, especially in Australian conditions. These include the coarse spatial resolution of most health and social data, the propagation of error through the need to use estimates and concordance tables to handle data in mismatched official spatial boundaries, the inflexible analytical capacity of most GIS for the needs of epidemiology, and difficulties in access to data, which are compounded by the absence of a good metadata register. The conflict between the need for spatial precision in GIS and preserving the confidentiality of health data is a salient issue. Medical geographers and public heath researchers using GIS must recognise these issues in order to work together and toward extending the use of GIS technology beyond broad ecological and accessibility studies.

A spatial data retrieval and image processing expert system for the world wide web

The integration of a data warehouse, an image processing engine and an expert system provides a complete solution to researchers from different fields that make use of spatial data in their investigations. Also, by adding image processing capabilities and making the system available to the World Wide Web, it is possible to provide remote access and processing of the data. This paper presents the fundamental concepts on designing the system.

Human Factors in Adoption of Geographic Information Systems: A Local Government Case Study

How do perceptions, experience, attitudes, and communication behavior of local government employees affect the adoption of Geographic Information Systems (GIS) technology as an organizational innovation? Nedovic-Budic and Godschalk examine the largely unexplored of GIS diffusion inside local governments in terms of the impact of human factors, internal organizational context, external organizational environment, and GIS management activities. Using a multiple-case study off our agencies within a North Carolina county government, the authors find that GIS diffusion is a very complex process. They conclude that perceived relative advantage, previous computer experience, exposure to the technology, and networking are the most significant determinants of employee willingness to use new GIS technology, while organizational and GIS management factors strongly influence GIS diffusion. The research findings have important implications for devising strategies for effective incorporation of GIS and other information system technologies in public organizations. Computerized geographic information systems (GIS) are increasingly used by public and private organizations as tools for storage, selective retrieval, and manipulation of spatial and nonspatial data. Local governments find GIS technology attractive for three major reasons: (1) spatially referenced data represent a large proportion (estimated at over 70 percent) of data processing in local government agencies (Somers, 1987), (2) information is considered a fundamental resource of government (Howard, 1985; Repo, 1989), and (3) pressure for improving government performance (Osborne and Gaebler, 1992; Gore, 1993) has prompted governments to look for more efficient ways of doing their work. Availability of more affordable computer technology in the late 1980s coincided with the increased interest of local governments in GIS technology and its intensified diffusion. Difficulties in capturing the exact GIS adoption rate sometimes result in inconsistent approximations, ranging from 2 to 3 percent to over 30 percent.(1) In this article, we focus on the factors that influence GIS diffusion in local government agencies. We look at employee perception, experience, attitudes, and communication behavior as they affect the success of GIS implementation. Organizational and management factors are studied as important contextual elements in the diffusion process. GIS Incorporation as Innovation Diffusion Viewing the spread of GIS technology into local governments as a process of technological innovation, diffusion provides a systematic basis for analyzing adoption. Both scholars and local government decision makers need objective information on constraints and opportunities affecting GIS adoption. Diffusion of GIS technology can be observed at both macro and micro levels (Budic and Godschalk, 1994; Onsrud et al., 1993). Macro-level diffusion concerns local government decisions to acquire the technology (Juhl, 1989; Somers, 1991; Wiggins and French, 1991; Budic, 1993a). Micro-level diffusion happens within local governments when their agencies, organizational units, subunits, or individuals decide to implement the technology acquired by the parent government (Leonard-Barton, 1987). Corresponding to the two diffusion levels are the initiation and implementation phases of GIS diffusion (Zaltman, Duncan, and Holbeck, 1973; Rogers, 1983; Onsrud and Pinto, 1993). During the initiation phase, organizations become aware of an innovation (i.e., GIS technology), evaluate it, and decide about acquisition. Implementation encompasses installing the technology, developing a database, and using and maintaining the system. Acquisition of GIS technology is defined as the successful outcome of GIS initiation, while adoption of GIS technology is defined as the successful outcome of GIS implementation. Both GIS initiation and GIS implementation efforts may result in rejection of the technology. …

On epidemiology and geographic information systems: a review and discussion of future directions.

Geographic information systems are powerful automated systems for the capture, storage, retrieval, analysis, and display of spatial data. While the systems have been in development for more than 20 years, recent software has made them substantially easier to use for those outside the field. The systems offer new and expanding opportunities for epidemiology because they allow an informed user to choose between options when geographic distributions are part of the problem. Even when used minimally, these systems allow a spatial perspective on disease. Used to their optimum level, as tools for analysis and decision making, they are indeed a new information management vehicle with a rich potential for public health and epidemiology.