Abstract: Human interactions with geographical information are contextualized by problem-solving activities which endow meaning to geospatial data and processing. However, existing spatial data models have not taken this aspect of semantics into account. This paper extends spatial data semantics to include not only the contents and schemas, but also the contexts of their use. We specify such a semantic model in terms of three related components: activity-centric context representation, contextualized ontology space, and context mediated semantic exchange. Contextualization of spatial data semantics allows the same underlying data to take multiple semantic forms, and disambiguate spatial concepts based on localized contexts. We demonstrate how such a semantic model supports contextualized interpretation of vague spatial concepts during human---GIS interactions. We employ conversational dialogue as the mechanism to perform collaborative diagnosis of context and to coordinate sharing of meaning across agents and data sources.

Abstract: This paper presents a study of Geography Markup Language (GML), the issues that arise from using GML for spatial applications, including storage, parsing, querying and visualization, as well as the use of GML for mobile devices and web services. GML is a modeling language developed by the Open Geospatial Consortium (OGC) as a medium of uniform geographic data storage and exchange among diverse applications. Many new XML-based languages are being developed as open standards in various areas of application. It would be beneficial to integrate such languages with GML during the developmental stages, taking full advantage of a non-proprietary universal standard. As GML is a relatively new language still in development, data processing techniques need to be refined further in order for GML to become a more efficient medium for geospatial applications.

Abstract: Topological relations have played important roles in spatial query, analysis and reasoning. In a two-dimensional space (IR2), most existing topological models can distinguish the eight basic topological relations between two spatial regions. Due to the arbitrariness and complexity of topological relations between spatial regions, it is difficult for these models to describe the order property of transformations among the topological relations, which is important for detailed analysis of spatial relations. In order to overcome the insufficiency in existing models, a multi-level modeling approach is employed to describe all the necessary details of region---region relations based upon topological invariants. In this approach, a set of hierarchically topological invariants is defined based upon the boundary---boundary intersection set (BBIS) of two involved regions. These topological invariants are classified into three levels based upon spatial set concept proposed, which include content, dimension and separation number at the set level, the element type at the element level, and the sequence at the integrated level. Corresponding to these hierarchical invariants, multi-level formal models of topological relations between spatial regions are built. A practical example is provided to illustrate the use of the approach presented in this paper.

Abstract: Traditional application of Voronoi diagrams for space partitioning results in Voronoi regions, each with a specific area determined by the generators' relative locations and weights. Particularly in the area of information space (re)construction, however, there is a need for inverse solutions; i.e., finding weights that result in regions with predefined area ratios. In this paper, we formulate an adaptive Voronoi solution and propose a raster-based optimization method for finding the associated weight set. The solution consists of a combination of simple, fixed-point iteration with an optional spatial resolution refinement along the regions' boundaries using quadtree decomposition. We present the corresponding algorithm and its complexity analysis. The method is successfully tested on a series of ideal---typical cases and the interactions between the adaptive technique and boundary resolution refinement are explored and assessed.

Abstract: With the continuing advances in wireless communications, geo-positioning, and portable electronics, an infrastructure is emerging that enables the delivery of on-line, location-enabled services to very large numbers of mobile users. A typical usage situation for mobile services is one characterized by a small screen and no keyboard, and by the service being only a secondary focus of the user. Under such circumstances, it is particularly important to deliver the "right" information and service at the right time, with as little user interaction as possible. This may be achieved by making services context aware. Mobile users frequently follow the same route to a destination as they did during previous trips to the destination, and the route and destination constitute important aspects of the context for a range of services. This paper presents key concepts underlying a software component that identifies and accumulates the routes of a user along with their usage patterns and that makes the routes available to services. The problems associated with of route recording are analyzed, and algorithms that solve the problems are presented. Experiences from using the component on logs of GPS positions acquired from vehicles traveling within a real road network are reported.

Abstract: Schematic networks are linear abstractions of functional networks, such as route networks Lines in the original network are modified in order to produce a schematic network which satisfies a set of constraints chosen to design the network A method is described which accomplishes this line transformation using an iterative improvement technique driven by design constraints The method maintains topological characteristics of the network by the use of simple geometric operations and tests The iterative process can be repeated until the line displacements become small enough or until it meets user defined stopping criteria Experimental results are provided to examine the acceptability of outcomes and the convergence of the applied iterative technique Criteria for measuring the quality of results, as well as for stopping the iterative approach are presented

Abstract: Hybrid digital terrain models represent an effective framework to combine and integrate terrain data with different topology and resolution. Cartographic digital terrain models typically are constituted by regular grid data and can be refined by adding locally TINs that represent morphologically complex terrain parts. Direct rendering of both data sets to visualize the digital terrain model would generate geometric discontinuities as the meshes are disconnected. In this paper we present a new meshing scheme for hybrid terrain representations. High quality models without discontinuities are generated as the different representations are softly joined through an adaptive tessellation procedure. Due to the complexity of the algorithms involved in the tessellation procedure, we propose a mixed strategy where part of the information is pre-computed and efficiently encoded. This way, for rendering the model, the tessellation information has to be decoded and only additional simple operations have to be performed.

Abstract: In the world of geospatial data infrastructures, geoportals are developed to facilitate access and use of geospatial resources, including data. The design and implementation of effective and efficient geoportals are becoming crucial. Providing possibilities for users to organize and integrate available resources can arguably enhance the process of data discovery and spatial analysis required, and hence, is the focus of this paper. We argue that the synthesis of summaries of distributed datasets, map and feature services through the geoportal can present a coherent view to support data discovery. For this purpose, the atlas metaphor is used as an indexing server and integration interface of summaries. Thematic maps and a storyteller view are accessible through the atlas metaphor. They can be used to provide a supporting context for data discovery and access purposes.

Abstract: The study of convective clouds is an important issue in weather analysis. Previous methods are based on shape matching and level set. In this paper, a method based on snake model is used for cloud tracking. Snakes are known to be more efficient than level set for contour detection however they do not handle topological changes. Therefore, geometrical criteria are introduced to characterize topological transformations. Geometrical techniques are then combined and inserted in the tracking algorithm to perform morphological operations. By applying this method, a history of the positions of the clouds is obtained. In a second stage, a data model is presented for cloud interrogation. Physical information is introduced and data are organized so that spatiotemporal queries can be performed. Results obtained with the tracking method on a real data set are presented and some query examples are given.

Abstract: Geostatistical methods make it possible to estimate the random errors in digital terrain models (DTMs) from one single set of measurements. After average interpolating trend removal, the error is derived from the variogram of the residual data set. This method is compared with a procedure that uses triangulation and resampling of two overlapping DTMs for extracting the error component. Eighteen small areas measured with a multibeam echo sounder are selected for the comparison. In the experiment the two methods come out with similar values for the random error. A by-product of the experiment is the development of a model for the average noise reduction caused by resampling of triangle models (TINs). The method we apply for the trend computation has time complexity O(n). Since the noise computation only requires the part of the variogram close to the origin, it is possible to formulate the computation of the random error in DTMs in O(n) time.

Abstract: Tropospheric delay inherent to GPS signals negatively impacts positioning precision. However, it can also provide information about the state of the troposphere, which may be useful for several met...

Abstract: The RTCM 3.0 data transmission format is introduced and described as it applies to multiple reference station real-time kinematic differential GPS positioning, or network RTK. The new format provides a more modern and flexible message structure that accommodates network RTK data transmission, while requiring up to 80% less bandwidth for the transmission of RTK correction messages. Based on this reduced bandwidth, we investigated moving the correction interpolation step of the network RTK procedure from the network to the rover user. The RTCM 3.0 format is implemented and tested in both network and user software. Three interpolation methods are implemented and compared with single baseline processing using real data collected using reference stations from the Southern Alberta Network. Under moderate ionospheric conditions, the network RTK solution outperforms the single baseline approach in both the observation and position domains. The three interpolation methods are found to be comparable. Under severe ionospheric conditions, network ambiguity resolution becomes difficult, making the network corrections unreliable. It is recommended that a network ambiguity resolution status flag be added to the RTCM 3.0 network correction message format to alert users when network corrections are unreliable.

Abstract: Addresses are the most common georeferencing resource people use to communicate to others a location within a city. Urban GIS applications that receive data directly from citizens, or from legacy information systems, need to be able to quickly and efficiently obtain a spatial location from addresses. In this paper we understand addresses in a broader perspective, in which not only the conventional elements of postal addresses are considered, but other kinds of direct or indirect references to places, such as building names, postal codes, or telephone area codes, which are also valuable as locators to urban places. This broader view on addresses allows us to work with two perspectives. First, in the ontological definition, modeling, and implementation of an addressing database that is flexible enough to accommodate the variety of concepts and address formats used worldwide, along with direct and indirect references to places. Second, in the definition of an indicator that is able to quantify the degree of certainty that could be reached when a user-given, semi-structured address is geocoded into a spatial position, as a function of the type and completeness of the available addressing data and of the geocoding method that has been employed. This indicator, which we call Geocoding Certainty Indicator (GCI), can be used as a threshold, beyond which the geocoded event should be left out of any statistical analysis, or as a weight that allows spatial analysis methods to reduce the influence of events that have been less reliably located. In order to support geocoding activities and the determination of the GCI, we propose a conceptual schema for addressing databases. The schema is flexible enough to accommodate a variety of addressing systems, at various levels of detail, and in different countries. Our intention is to depart from the usual geocoding strategy employed in commercial GIS products, which is usually limited to the average American or British address format. The schema also extends the notion of postal address to something broader, including popular names for places, building names, reference places, and other concepts. This approach extends Simpson's and Yu's Comput. Environ. Urban Syst., 27: 283---307, 2003 work on postal codes to records of any kind, including place names and loosely formatted addresses.

Abstract: The MultiDimER model is a conceptual model used for representing a multidimensional view of data for Data Warehouse (DW) and On-Line Analytical Processing (OLAP) applications. This model includes a spatial extension allowing spatiality in levels, hierarchies, fact relationships, and measures. In this way decision-making users can represent in an abstract manner their analysis needs without considering complex implementation issues and spatial OLAP tools developers can have a common vision for representing spatial data in a multidimensional model. In this paper we propose the transformation of a conceptual schema based on the MultiDimER constructs to an object-relational schema. We based our mapping on the SQL:2003 and SQL/MM standards giving examples of commercial implementation using Oracle 10g with its spatial extension. Further we use spatial integrity constraints to ensure the semantic equivalence of the conceptual and logical schemas. We also show some examples of Oracle spatial functions, including aggregation functions required for the manipulation of spatial data. The described mappings to the object-relational model along with the examples using a commercial system show the feasibility of implementing spatial DWs in current commercial DBMSs. Further, using integrated architectures, where spatial and thematic data is defined within the same DBMS, facilitates the system management simplifying data definition and manipulation.

Abstract: The ability to process geospatial data will be a great benefit for spatial data infrastructures. This requires the ability to compose data providing services with geoprocessing services. Discovering suitable geoprocessing services is a major challenge in this endeavour. Current (keyword-based) approaches to service discovery are inherently restricted by the ambiguities of natural language, which can lead to low precision and/or recall. To alleviate these problems, we propose to use an ontology-based approach to GI service discovery, which rests on two ideas. Ontologies describing geospatial operations are used to create descriptions of requirements and service capabilities; matches between these descriptions are identified based on function subtyping. We use a running example from the geospatial domain to analyse which problems can occur in existing keyword- and ontology-based approaches and how the discovery of geoprocessing services differs from other service discovery tasks. The example is also used for illustrating the prototypical implementation of the proposed approach.

Abstract: Internet, a client/server system, is a perfect means of GIS data accessing, analyzing and transmission. The World Wide Web, FTP (file transfer protocol) and HTTP programs make it convenient to access and transfer data files across the Internet. Using Internet for GIS makes it easy access to acquire GIS data from diverse data sources in the distributed environment. The geospatial multicriteria decision analysis in a client/server environment is an important and challenging task for the GIS community because of narrow Internet bandwidth for large geospatial data sets. In the present paper, we are developing a multicriteria decision analysis tool for spatial decision making in the web GIS environment. The developed system has been demonstrated for biodiversity conservation and priorities. An attempt has been made to generate the alternative decisions based on priority vectors. The multicriteria technique of Analytic Hierarchy Process (AHP) is used to derive the eigen vectors with the given multiple constraints of conflicting criteria and aims at selecting optimal alternative from the available sets. However, the evaluation recognizes the importance of expert knowledge when assigning the weights for the best spatial priorities. Comparing within classes and alternatives using judgment and decision matrix is based on Saaty's Pairwise Comparison. The Multicriteria Spatial Decision Support System (MC-SDSS) software development uses ASP, ArcIMS 9.0, ArcSDE9.0 and Oracle 9i data server in the web GIS environment. The database organization of spatial and non-spatial data is done in the RDBMS environment using ArcSDE and Oracle 9i data server.

Abstract: Nearest Neighbor (NN) search has been in the core of spatial and spatiotemporal database research during the last decade. The literature on NN query processing algorithms so far deals with either stationary or moving query points over static datasets or future (predicted) locations over a set of continuously moving points. With the increasing number of Mobile Location Services (MLS), the need for effective k-NN query processing over historical trajectory data has become the vehicle for data analysis, thus improving existing or even proposing new services. In this paper, we investigate mechanisms to perform NN search on R-tree-like structures storing historical information about moving object trajectories. The proposed (depth-first and best-first) algorithms vary with respect to the type of the query object (stationary or moving point) as well as the type of the query result (historical continuous or not), thus resulting in four types of NN queries. We also propose novel metrics to support our search ordering and pruning strategies. Using the implementation of the proposed algorithms on two members of the R-tree family for trajectory data (namely, the TB-tree and the 3D-R-tree), we demonstrate their scalability and efficiency through an extensive experimental study using large synthetic and real datasets.

Abstract: The research presented in this paper introduces a relative representation of trajectories in space and time. The objective is to represent space the way it is perceived by a moving observer acting in the environment, and to provide a complementary view to the usual absolute vision of space. Trajectories are characterized from the perception of a moving observer where relative positions and relative velocities are the basic primitives. This allows for a formal identification of elementary trajectory configurations, and their relationships with the regions that compose the environment. The properties of the model are studied, including transitions and composition tables. These properties characterize trajectory transitions by the underlying processes that semantically qualify them. The approach provides a representation that might help the understanding of trajectory patterns in space and time.

Abstract: Orthophotos (or orthoimages if in digital form) have long been recognised as a supplement or alternative to standard maps. The increasing applications of orthoimages require efforts to ensure the accuracy of produced orthoimages. As digital photogrammetry technology has reached a stage of relative maturity and stability, the availability of high quality ground control points (GCPs) and digital elevation models (DEMs) becomes the central issue for successfully implementing an image orthorectification project. Concerns with the impacts of the quality of GCPs and DEMs on the quality of orthoimages inspire researchers to look for more reliable approaches to acquire high quality GCPs and DEMs for orthorectification. Light Detection and Ranging (LiDAR), an emerging technology, offers capability of capturing high density three dimensional points and generating high accuracy DEMs in a fast and cost-effective way. Nowadays, highly developed computer technologies enable rapid processing of huge volumes of LiDAR data. This leads to a great potential to use LiDAR data to get high quality GCPs and DEMs to improve the accuracy of orthoimages. This paper presents methods for utilizing LiDAR intensity images to collect high accuracy ground coordinates of GCPs and for utilizing LiDAR data to generate a high quality DEM for digital photogrammetry and orthorectification processes. A comparative analysis is also presented to assess the performance of proposed methods. The results demonstrated the feasibility of using LiDAR intensity image-based GCPs and the LiDAR-derived DEM to produce high quality orthoimages.

Abstract: Fuzzy set theory has been suggested as a means for representing vague spatial phenomena, and is widely known for directly addressing some of the issues of vagueness such as the sorites paradox. Higher order vagueness is widely considered a necessary component of any theory of vagueness, but it is not so well known that it too is competently modelled by Type n Fuzzy sets. In this paper we explore the fuzzy representation of higher order vagueness with respect to spatial phenomena. Initially we relate the arguments on philosophical vagueness to Type n Fuzzy sets. As an example, we move on to an empirical generation of spatial Type 2 Fuzzy sets examining the spatial extent of mountain peaks in Scotland. We show that the Type 2 Fuzzy sets can be populated by using alternative parameterisations of a peak detection algorithm. Further ambiguities could also be explored using other parameters of this and other algorithms. We show some novel answers to interrogations of the mountain peaks of Scotland. The conclusion of this work is that higher order vagueness can be populated for Type 2 and higher fuzzy sets. It does not follow that it is always necessary to examine these higher order uncertainties, but a possible advantage in terms of the results of spatial inquiry is demonstrated.

Abstract: The lack of effective and efficient schedule-based pathfinding algorithms for transit networks has limited the application of GIS in transit trip planning services. This paper introduces a schedule-based path finding algorithm for transit networks. Based on a pattern-centered spatiotemporal transit network model, the algorithm searches the network by following route patterns. A pattern is a spatial layout of a route in transit terminology. A route usually has many patterns to serve various locations at different times. This path search algorithm is significantly different from traditional shortest path algorithms that are based on adjacent node search. By establishing a set of lemmas and theorems the paper proves that paths generated by the PFS algorithm are schedule-coordinated fastest paths for trips with given constraints. After analyzing computation and database query complexities of the algorithm the paper indicates that the PFS is efficient in computation and database query. Finally, effectiveness and efficiency of the algorithm are demonstrated by implementations in GIS-based online transit trip planners in Wisconsin, US.