A way forward for land-use planning to achieve policy goals by using spatial modelling scenarios

This paper investigates how demographic (socioeconomic) and land-use (physical and environmental) data can be integrated within a decision support framework to formulate and evaluate land-use planning scenarios. A case-study approach is undertaken with land-use planning scenarios for a rapidly growing coastal area in Australia, the Shire of Hervey Bay. The town and surrounding area require careful planning of the future urban growth between competing land uses. Three potential urban growth scenarios are put forth to address this issue. Scenario A ('continued growth') is based on existing socioeconomic trends. Scenario B ('maximising rates base') is derived using optimisation modelling of land-valuation data. Scenario C ('sustainable development') is derived using a number of social, economic, and environmental factors and assigning weightings of importance to each factor using a multiple criteria analysis approach. The land-use planning scenarios are presented through the use of maps and tables within a geographical information system, which delineate future possible land-use allocations up until 2021. The planning scenarios are evaluated by using a goal-achievement matrix approach. The matrix is constructed with a number of criteria derived from key policy objectives outlined in the regional growth management framework and town planning schemes. The authors of this paper examine the final efficiency scores calculated for each of the three planning scenarios and discuss the advantages and disadvantages of the three land-use modelling approaches used to formulate the final scenarios.

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

Expansion-based algorithms for finding single pair shortest path on surface

Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.

A real options based method for power system planning

A deregulated electricity market is characterized with uncertainties, with both long and short terms. As one of the major long term planning issues, the transmission expansion planning (TEP) is aiming at implementing reliable and secure network support to the market participants. The TEP covers two major issues: technical assessment and financial evaluations. Traditionally, the net present value (NPV) method is the most accepted for financial evaluations, it is simple to conduct and easy to understand. Nevertheless, TEP in a deregulated market needs a more dynamic approach to incorporate a project's management flexibility, or the managerial ability to adapt in response to unpredictable market developments. The real options approach (ROA) is introduced here, which has clear advantage on counting the future course of actions that investors may take, with understandable results in monetary terms. In the case study, a Nordic test system has been testified and several scenarios are given for network expansion planning. Both the technical assessment and financial evaluation have been conducted in the case study.

Concepts and tools for comprehensive sustainability assessments for tourism destinations: a comparative review

This paper reviews a wide range of tools for comprehensive sustainability assessments at whole tourism destinations, covering socio-cultural, economic and environmental issues. It considers their strengths, weaknesses and site specific applicability. It is intended to facilitate their selection (and combination where necessary). Tools covered include Sustainability Indicators, Environmental Impact Assessment, Life Cycle Assessment, Environmental Audits, Ecological Footprints, Multi-Criteria Analysis and Adaptive Environmental Assessment. Guidelines for evaluating their suitability for specific sites and situations are given as well as examples of their use.

Compiling a GIS database of tree farms on Leyte Island

As part of ACIAR project ASEM/2003/052, Improving Financial Returns to Smallholder Tree Farmers in the Philippines, plantations of timber trees in Leyte Island, the Philippines were located using a systematic survey of the island. The survey was undertaken in order to compile a database of plantations which could be used to guide the planning of project activities. In addition to recording a range of qualitative and quantitative information for each plantation, the survey spatially referenced each site using a Global Positioning System (GPS) to electronic maps of the island which were held in a Geographical Information System (GIS). Microsoft Excel and Mapsource® software were used as the software links between GPS coordinates and the GIS. Mapping of farm positions was complicated by different datums being used for maps of Leyte Island and this caused GPS positions to be displaced from equivalent positions on the map. Photos of the sites were hyperlinked to their map positions in the GIS in order to assist staff to recall site characteristics.

Public policy in knowledge-based economies: Foundations and frameworks

Knowledge is a product of human social systems and, therefore, the foundations of the knowledge-based economy are social and cultural. Communication is central to knowledge creation and diffusion, and Public Policy in Knowledge-Based Economies highlights specific social and cultural conditions that can enhance the communication, use and creation of knowledge in a society.The purpose of this book is to illustrate how these social and cultural conditions are identified and analysed through new conceptual frameworks. Such frameworks are necessary to penetrate the surface features of knowledge-based economies - science and technology - and disclose what drives such economies.This book will provide policymakers, analysts and academics with the fundamental tools needed for the development of policy in this little understood and emerging area.

Accessibility to general practitioners in rural South Australia - A case study using geographic information system technology

Objective: To demonstrate the potential of GIS (geographic information system) technology and ARIA (Accessibility/Remoteness Index for Australia) as tools for medical workforce and health service planning in Australia. Design: ARIA is an index of remoteness derived by measuring road distance between populated localities and service centres. A continuous variable of remoteness from 0 to 12 is generated for any location in Australia. We created a GIS, with data on location of general practitioner services in non-metropolitan South Australia derived from the database of HUMPS (Rural Undergraduate Medical Placement System), and estimated, for the 1170 populated localities in South Australia, the accessibility/inaccessibility of the 109 identified GP services. Main outcome measures: Distance from populated locality to GP services. Results: Distance from populated locality to GP service ranged from 0 to 677 km (mean, 58 km). In all, 513 localities (43%) had a GP service within 20 km (for the majority this meant located within the town). However, for 173 populated localities (15%), the nearest GP service was more than 80 km away. There was a strong correlation between distance to GP service and ARIA value for each locality (0.69; P<0.05). Conclusions: GP services are relatively inaccessible to many rural South Australian communities. There is potential for GIS and for ARIA to contribute to rational medical workforce and health service planning. Adding measures of health need and more detailed data on types and extent of GP services provided will allow more sophisticated planning.

Predicting energy requirements in the clinical setting: Are current methods evidence based?

Estimating energy requirements is necessary in clinical practice when indirect calorimetry is impractical. This paper systematically reviews current methods for estimating energy requirements. Conclusions include: there is discrepancy between the characteristics of populations upon which predictive equations are based and current populations; tools are not well understood, and patient care can be compromised by inappropriate application of the tools. Data comparing tools and methods are presented and issues for practitioners are discussed. (C) 2003 International Life Sciences Institute.