Automating the administration boundary design process using Hierarchical Spatial Reasoning theory and Geographical Information Systems

This paper addresses the problems associated with the integration of data between incongruent boundary systems. Currently, the majority of spatial boundaries are designed in an uncoordinated manner with individual organisations generating individual boundaries to meet individual needs. As a result, current technologies for analysing geospatial information, such as geographic information systems (GISs), are not reaching their full potential. In response to the problem of uncoordinated boundaries, the authors present an algorithm for the hierarchical structuring of administrative boundaries. This algorithm applies hierarchical spatial reasoning (HSR) theory to the automated structuring of polygons. In turn, these structured boundary systems facilitate accurate data integration and analysis whilst meeting the spatial requirements of selected agencies. The algorithm is presented in two parts. The first part outlines previous research undertaken by the authors into the delineation of administrative boundaries in metropolitan regions. The second part outlines the distinctly different constraints required for administrative-boundary design in rural areas. The formalisation of the algorithm has taken place in a GIS environment utilising Avenue, an object-orientated programming language that operates under ArcView, the desktop software developed and distributed by ESRI

Automating the administration boundary design process using Hierarchical Spatial Reasoning theory and Geographical Information Systems

This paper addresses the problems associated with the integration of data between incongruent boundary systems. Currently, the majority of spatial boundaries are designed in an uncoordinated manner with individual organisations generating individual boundaries to meet individual needs. As a result, current technologies for analysing geospatial information, such as geographic information systems (GISs), are not reaching their full potential. In response to the problem of uncoordinated boundaries, the authors present an algorithm for the hierarchical structuring of administrative boundaries. This algorithm applies hierarchical spatial reasoning (HSR) theory to the automated structuring of polygons. In turn, these structured boundary systems facilitate accurate data integration and analysis whilst meeting the spatial requirements of selected agencies. The algorithm is presented in two parts. The first part outlines previous research undertaken by the authors into the delineation of administrative boundaries in metropolitan regions. The second part outlines the distinctly different constraints required for administrative-boundary design in rural areas. The formalisation of the algorithm has taken place in a GIS environment utilising Avenue, an object-orientated programming language that operates under ArcView, the desktop software developed and distributed by ESRI

Automating the administration boundary design process using Hierarchical Spatial Reasoning (HSR) theory and Geographic Information Systems (GIS)

Throughout history, humankind has segmented and delineated the geographic 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 Geographic Information System (GIS) 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 present the findings of a research project aimed 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. In the first section, the paper outlines the problem of data exchange and data integration encountered worldwide when utilising current administrative boundaries and the data attached to them. It also reviews the most commonly adopted methods to overcome the problem and the issues inherent to these methods. Secondly, the paper introduces the concept and theory of HSR and reviews common practices in boundary design. The paper summarises constraints and issues arising from the use of GIS jointly with HSR in polygon-base design. Thirdly, an HSR-based prototype developed for delineating boundaries within the GIS environment is detailed. This prototype has been constructed utilising the state of Victoria, Australia as a working laboratory for development and analysis. The prototype has been implemented in ArcView (ESRI) using cadastre (land parcels), road network and major natural barriers as the core information and Avenue as the programming language. In the prototype, the agencies considered were ABS (Australian Bureau of Statistics) and Australia Post due to their widely acceptance and use amongst institutions and individuals dealing with geospatial data and analyses

Automating the administration boundary design process using Hierarchical Spatial Reasoning (HSR) theory and Geographic Information Systems (GIS)

Throughout history, humankind has segmented and delineated the geographic 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 Geographic Information System (GIS) 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 present the findings of a research project aimed 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. In the first section, the paper outlines the problem of data exchange and data integration encountered worldwide when utilising current administrative boundaries and the data attached to them. It also reviews the most commonly adopted methods to overcome the problem and the issues inherent to these methods. Secondly, the paper introduces the concept and theory of HSR and reviews common practices in boundary design. The paper summarises constraints and issues arising from the use of GIS jointly with HSR in polygon-base design. Thirdly, an HSR-based prototype developed for delineating boundaries within the GIS environment is detailed. This prototype has been constructed utilising the state of Victoria, Australia as a working laboratory for development and analysis. The prototype has been implemented in ArcView (ESRI) using cadastre (land parcels), road network and major natural barriers as the core information and Avenue as the programming language. In the prototype, the agencies considered were ABS (Australian Bureau of Statistics) and Australia Post due to their widely acceptance and use amongst institutions and individuals dealing with geospatial data and analyses

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

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

Spatial algorithm for detecting disease outbreaks in Australia

La detección temprana de brotes de enfermedades es esencial de cara a una intervención pronta en problemas de salud pública. Actualmente en Australia, las enfermedades notificables son recogidas y almacenadas, y referenciadas geográfica y temporalmente. Sin embargo, el proceso para la búsqueda de brotes de enfermedad sobre escalas espaciales distintas no está bien definido. Los brotes son de detección difícil. Algunas enfermedades aparecen relativamente rápido, mientras otras requieren más tiempo para su incubación y sólo se hacen evidentes sobre largos intervalos temporales. En la práctica, los epidemiólogos combinan diferentes conjuntos de evidencias para determinar la probabilidad de la existencia de un brote. Gracias al progresivo incremento de disponibilidad de bases de datos electrónicas y de los Sistemas de Información Geográfica (SIG), el potencial para la utilización de técnicas de análisis espacial para la visualización, exploración y modelado de notificaciones de enfermedades para la detección temprana de brotes, es hoy mayor que en el pasado. En este artículo, los autores presentan un algoritmo que emplea bases de datos de la administración, análisis espacial y SIG para la detección de clusters de enfermedades en el Estado de Australia Occidental. El algoritmo revisa los códigos postales de forma rutinaria hasta encontrar un número de casos que supera los valores que serían esperados en la región considerada. El algoritmo está diseñado para su uso por profesionales de la salud pública para asistir en la identificación y seguimiento de clusters en tiempo real.The early detection of disease outbreaks is essential for early intervention in potential public health problems. Currently in Australia, disease notifications are recorded, temporally and geographically referenced; however, the process of searching for outbreaks over different spatial scales is not well defined. Disease outbreaks are difficult to detect. Some diseases appear relatively rapidly, while others take time to gestate and become apparent over long time intervals. In practice, epidemiologists combine different sets of evidence in different ways and apply reasoning to determine the likelihood of an outbreak. With an increase in the availability of electronic health-care data and geographic information systems (GIS), there is great potential to use spatial analysis techniques for the visualisation, exploration and modelling of disease notifications for the early detection of disease outbreaks. In this paper, the authors present an algorithm that uses administrative databases, spatial analysis and GIS for the detection of disease clusters in Western Australia (WA). The algorithm routinely tests administrative areas (postcodes) and highlights the areas in which counts exceed the expected number for the particular region. This algorithm is intended to be used by public health officials to identify and track clusters in localised geographic areas in real-time

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

Measuring area-level disadvantage in Australia : Development of a locally sensitive indicator

Background In Australia, the Socio-Economic Indexes for Areas (SEIFA), which includes the Index of Relative Socioeconomic Disadvantage (IRSD), captures the socioeconomic characteristics of areas. Because SEIFA rankings are relative to the country or state, the decile categorisations may not reflect an area’s socioeconomic standing relative to areas nearby. Aims The aim of the research was to explore whether IRSD rankings could be re-ranked to become locally sensitive. Data and methods Using existing SEIFA data to redistribute the membership of current decile IRSD groups, we tested three methods to re-rank all SA1 areas relative to the nearest areas capped at: (1) the nearest 99 neighbours, (2) a population threshold of 50,000 (3) a distance threshold of 10 km. Results The reclassification of SEIFA IRSD deciles was largest (up to 8 decile points of change) when comparing the nearest neighbour and population threshold local methods to current state-based rankings. Moreover, compared to using current national and state SEIFA IRSD rankings, the use of local rankings resulted in more evenly distributed deciles between cities, regional, and remote areas. Conclusions Because SEIFA IRSD rankings are used to allocate resources and health services, we encourage the combined use of a state and local ranking to refine areas considered the most disadvantaged