Performance comparison of point and spatial access methods

In the past few years a large number of multidimensional point access methods, also called multiattribute index structures, has been suggested, all of them claiming good performance. Since no performance comparison of these structures under arbitrary (strongly correlated nonuniform, short "ugly") data distributions and under various types of queries has been performed, database researchers and designers were hesitant to use any of these new point access methods. As shown in a recent paper, such point access methods are not only important in traditional database applications. In new applications such as CAD/CIM and geographic or environmental information systems, access methods for spatial objects are needed. As recently shown such access methods are based on point access methods in terms of functionality and performance. Our performance comparison naturally consists of two parts. In part I we w i l l compare multidimensional point access methods, whereas in part I I spatial access methods for rectangles will be compared. In part I we present a survey and classification of existing point access methods. Then we carefully select the following four methods for implementation and performance comparison under seven different data files (distributions) and various types of queries: the 2-level grid file, the BANG file, the hB-tree and a new scheme, called the BUDDY hash tree. We were surprised to see one method to be the clear winner which was the BUDDY hash tree. It exhibits an at least 20 % better average performance than its competitors and is robust under ugly data and queries. In part I I we compare spatial access methods for rectangles. After presenting a survey and classification of existing spatial access methods we carefully selected the following four methods for implementation and performance comparison under six different data files (distributions) and various types of queries: the R-tree, the BANG file, PLOP hashing and the BUDDY hash tree. The result presented two winners: the BANG file and the BUDDY hash tree. This comparison is a first step towards a standardized testbed or benchmark. We offer our data and query files to each designer of a new point or spatial access method such that he can run his implementation in our testbed

Dynamic Reconstruction of Complex Planar Objects on Irregular Isothetic Grids

International audienceThe vectorization of discrete regular images has been widely developed in many image processing and synthesis applications, where images are considered as a regular static data. Regardless of final application, we have proposed in [14] a reconstruction algorithm of planar graphical elements on irregular isothetic grids. In this paper, we present a dynamic version of this algorithm to control the reconstruction. Indeed, we handle local refinements to update efficiently our complete shape representation. We also illustrate an application of our contribution for interactive approximation of implicit curves by lines, controlling the topology of the reconstruction

Future directions of administrative boundary design in support of Spatial Data Infrastructures

Spatial Data Infrastructures (SDIs) comprise a set of policies aimed at coordinating the numerous layers of spatial information upon which society functions. To achieve this objective effectively an SDI must encompass policies, standards, and procedures for organisations to cooperatively produce and share geographic data. One of the most fundamental problems restricting the objectives of SDI is the fragmentation of data between different agency boundaries. Essentially this problem stems from the differing criteria and methods adopted by agencies designing individual boundary units. This current lack of coordination and unstructured methodologies for subdividing space has lead to difficulties in integrating, analysing and exchanging information across boundaries and through time. To further the objectives of SDIs in providing mechanisms for data integration, methods by which agencies may derive administrative boundaries using a common framework, which still meet their own individual requirements are being investigated. Through the development algorithms and standards for the design of administrative boundaries within a spatial hierarchy it is envisaged that SDI will incorporate data integration and cross analysis to its range of existing functions

Hierarchical Spatial Reasoning Applied to Automated Design of Administrative Boundaries

Throughout history, humankind has segmented and delineated the geospatial environment in various ways to support administrative, political and economic activities. To date, the majority of spatial boundaries have been constructed in an uncoordinated manner with individual organisations generating individual boundaries to meet individual needs. This practice has resulted in boundary layers that even the most sophisticated GIS (Geographic Information System) technology is unable to cross analyse accurately. Consequently, geospatial information is fragmented over a series of boundary units. The objective of this paper is to investigate new methods for the organisation of spatial data by applying the principles of Hierarchical Spatial Reasoning (HSR), where HSR can be used as the theoretical framework for investigating the hierarchical structuring of space and for providing new methods for accurate data exchange. Also, to present the issues found in the development of a prototype developed for delineating boundaries within the GIS environment. This prototype has been constructed utilising the state of Victoria, Australia as a working laboratory for development and analysis

Hierarchical Spatial Reasoning Applied to Spatial Data Infrastructures

Many countries throughout the world believe they can benefit both economically and environmentally from better management of their spatial data assets, enabling them to access and retrieve complete and consistent datasets in an easy and secure way. This has resulted in the development of the Spatial Data Infrastructure (SDI) concept at various political and/or administrative levels. The SDI concept has been represented by different descriptions of its nature, however, currently these demonstrate an overly-simplistic understanding of the concept. The simplicity in existing definitions has been slow to incorporate the concept of an integrated, multilevelled SDI formed from a hierarchy of inter-connected SDIs at corporate, local, state/provincial, national, regional (multi-national) and global (GSDI) levels. Failure to incorporate this multidimensionality, and the dynamic mechanistic and functional roles of the SDI have rendered many descriptions of SDI inadequate to describe the complexity and the dynamics of SDI as it develops,and thus ultimately constrain SDI achieving developmental potential in the future. As a result, the objective of this paper is to demonstrate the fitness and applicability of Hierarchical Spatial Reasoning (HSR) as a theoretical framework to demonstrate the multi-dimensional nature of SDIs. It is argued that by better understanding and demonstrating the nature of an SDI hierarchy, any SDI development can gain support from a wider community of both government and nongovernment data users and providers. The findings presented in this paper build on the authors experiences in Regional SDI (multi-national) development and HSR

Towards a model for the multidimensional analysis of field data

International audienceIntegration of spatial data into multidimensional models leads to the concept of Spatial OLAP (SOLAP). Usually, SOLAP models exploit discrete spatial data. Few works integrate continuous field data into dimensions and measures. In this paper, we provide a multidimensional model that supports measures and dimension as continuous field data, independently of their implementation

Hierarchical Spatial Reasoning theory and GIS technology applied to the automated delineation of administrative boundaries

Throughout history, humankind has segmented and delineated the geographic environment\ud in various ways to support administrative, political and economic activities. To date, the majority of spatial boundaries have been constructed in an uncoordinated manner with individual organisations generating individual boundaries to meet their own specific needs. As a result of this lack of coordination, there is a fragmentation of information over a series of boundary units, which not only limits the potential uses for data collected, but also the scope of analysis possible between boundary layers. The proposed solution outlined in this research involves the reorganisation of the spatial environment based on Hierarchical Spatial Reasoning (HSR) and the application of a GIS-based algorithm for the automated delineation of boundaries. By using this approach, it is expected that administrative boundaries can be formed through the aggregation of smaller units. This proposed system is focussed towards facilitating rapid and efficient cross analysis of data sets