Knowledge-based approach for planning healthy cities : the case of Logan-Beaudesert, Australia

Introduction - The planning for healthy cities faces significant challenges due to lack of effective information, systems and a framework to organise that information. Such a framework is critical in order to make accessible and informed decisions for planning healthy cities. The challenges for planning healthy cities have been magnified by the rise of the healthy cities movement, as a result of which, there have been more frequent calls for localised, collaborative and knowledge-based decisions. Some studies have suggested that the use of a ‘knowledge-based’ approach to planning will enhance the accuracy and quality decision-making by improving the availability of data and information for health service planners and may also lead to increased collaboration between stakeholders and the community. A knowledge-based or evidence-based approach to decision-making can provide an ‘out-of-the-box’ thinking through the use of technology during decision-making processes. Minimal research has been conducted in this area to date, especially in terms of evaluating the impact of adopting knowledge-based approach on stakeholders, policy-makers and decision-makers within health planning initiatives. Purpose – The purpose of the paper is to present an integrated method that has been developed to facilitate a knowledge-based decision-making process to assist health planning Methodology – Specifically, the paper describes the participatory process that has been adopted to develop an online Geographic Information System (GIS)-based Decision Support System (DSS) for health planners. Value – Conceptually, it is an application of Healthy Cities and Knowledge Cities approaches which are linked together. Specifically, it is a unique settings-based initiative designed to plan for and improve the health capacity of Logan-Beaudesert area, Australia. This setting-based initiative is named as the Logan-Beaudesert Health Coalition (LBHC). Practical implications - The paper outlines the application of a knowledge-based approach to the development of a healthy city. Also, it focuses on the need for widespread use of this approach as a tool for enhancing community-based health coalition decision making processes.

Integration of a road traffic noise model (ASJ) and traffic simulation (AVENUE) for a built-up area

A road traffic noise prediction model (ASJ MODEL-1998) has been integrated with a road traffic simulator (AVENUE) to produce the Dynamic areawide Road traffic NoisE simulator-DRONE. This traffic-noise-GIS based integrated tool is upgraded to predict noise levels in built-up areas. The integration of traffic simulation with a noise model provides dynamic access to traffic flow characteristics and hence automated and detailed predictions of traffic noise. The prediction is not only on the spatial scale but also on temporal scale. The linkage with GIS gives a visual representation to noise pollution in the form of dynamic areawide traffic noise contour maps. The application of DRONE on a real world built-up area is also presented.

Urban growth monitoring techniques for sustainable development

This paper discusses the role of advance techniques for monitoring urban growth and change for sustainable development of urban environment. It also presents results of a case study involving satellite data for land use/land cover classification of Lucknow city using IRS-1C multi-spectral features. Two classification algorithms have been used in the study. Experiments were conducted to see the level of improvement in digital classification of urban environment using Artificial Neural Network (ANN) technique.

Harnessing ICT-based tool for improving the collaborative health planning debate : the case of Logan-Beaudesert, Australia

The field of collaborative health planning faces significant challenges posed by the lack of effective information, systems and a framework to organise that information. Such a framework is critical in order to make accessible and informed decisions for planning healthy cities. The challenges have been exaggerated by the rise of the healthy cities movement, as a result of which, there have been more frequent calls for localised, collaborative and evidence-based decision-making. Some studies suggest that the use of ICT-based tools in health planning may lead to: increased collaboration between stakeholder sand the community; improve the accuracy and quality of the decision making process; and, improve the availability of data and information for health decision-makers as well as health service planners. Research has justified the use of decision support systems (DSS) in planning for healthy cities as these systems have been found to improve the planning process. DSS are information communication technology (ICT) tools including geographic information systems (GIS) that provide the mechanisms to help decision-makers and related stake holders assess complex problems and solve these in a meaningful way. Consequently, it is now more possible than ever before to make use of ICT-based tools in health planning. However, knowledge about the nature and use of DSS within collaborative health planning is relatively limited. In particular, little research has been conducted in terms of evaluating the impact of adopting these tools upon stakeholders, policy-makers and decision-makers within the health planning field. This paper presents an integrated method that has been developed to facilitate an informed decision-making process to assist in the health planning process. Specifically, the paper describes the participatory process that has been adopted to develop an online GIS-based DSS for health planners. The literature states that the overall aim of DSS is to improve the efficiency of the decisions made by stakeholders, optimising their overall performance and minimizing judgmental biases. For this reason, the paper examines the effectiveness and impact of an innovative online GIS-based DSS on health planners. The case study of the online DSS is set within a unique settings-based initiative designed to plan for and improve the health capacity of Logan-Beaudesert area, Australia. This unique setting-based initiative is named the Logan-Beaudesert Health Coalition (LBHC).The paper outlines the impact occurred by implementing the ICT-based DSS. In conclusion, the paper emphasizes upon the need for the proposed tool for enhancing health planning.

Spatial analysis of melioidosis distribution in a suburban area

Burkholderia pseudomallei, the causative agent of melioidosis is associated with soil. This study used a geographic information system (GIS) to determine the spatial distribution of clinical cases of melioidosis in the endemic suburban region of Townsville in Australia. A total of 65 cases over the period 1996–2008 were plotted using residential address. Two distinct groupings were found. One was around the base of a hill in the city centre and the other followed the old course of a major waterway in the region. Both groups (accounting for 43 of the 65 cases examined) are in areas expected to have particularly wet topsoils following intense rainfall, due to soil type or landscape position.

Geographical information systems : an effective planning and decision-making platform for community health coalitions in Australia

The development of locally-based healthcare initiatives, such as community health coalitions that focus on capacity building programs and multi-faceted responses to long-term health problems, have become an increasingly important part of the public health landscape. As a result of their complexity and the level of investment, it has become necessary to develop innovative ways to help manage these new healthcare approaches. Geographical Information Systems (GIS) have been suggested as one of the innovative approaches that will allow community health coalitions to better manage and plan their activities. The focus of this paper is to provide a commentary on the use of GIS as a tool for community coalitions and discuss some of the potential benefits and issues surrounding the development of these tools.

Application of chemometrics to analysis of soil pollutants

This overview focuses on the application of chemometrics techniques for the investigation of soils contaminated by polycyclic aromatic hydrocarbons (PAHs) and metals because these two important and very diverse groups of pollutants are ubiquitous in soils. The salient features of various studies carried out in the micro- and recreational environments of humans, are highlighted in the context of the various multivariate statistical techniques available across discipline boundaries that have been effectively used in soil studies. Particular attention is paid to techniques employed in the geosciences that may be effectively utilized for environmental soil studies; classical multivariate approaches that may be used in isolation or as complementary methods to these are also discussed. Chemometrics techniques widely applied in atmospheric studies for identifying sources of pollutants or for determining the importance of contaminant source contributions to a particular site, have seen little use in soil studies, but may be effectively employed in such investigations. Suitable programs are also available for suggesting mitigating measures in cases of soil contamination, and these are also considered. Specific techniques reviewed include pattern recognition techniques such as Principal Components Analysis (PCA), Fuzzy Clustering (FC) and Cluster Analysis (CA); geostatistical tools include variograms, Geographical Information Systems (GIS), contour mapping and kriging; source identification and contribution estimation methods reviewed include Positive Matrix Factorisation (PMF), and Principal Component Analysis on Absolute Principal Component Scores (PCA/APCS). Mitigating measures to limit or eliminate pollutant sources may be suggested through the use of ranking analysis and multi criteria decision making methods (MCDM). These methods are mainly represented in this review by studies employing the Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and its associated graphic output, Geometrical Analysis for Interactive Aid (GAIA).

Community-based public health: an Online Decision Support Systems : for Logan city, Australia

Introduction Among the many requirements of establishing community health, a healthy urban environment stands out as significant one. A healthy urban environment constantly changes and improves community well-being and expands community resources. The promotion efforts for such an environment, therefore, must include the creation of structures and processes that actively work to dismantle existing community inequalities. In general, these processes are hard to manage; therefore, they require reliable planning and decision support systems. Current and previous practices justify that the use of decision support systems in planning for healthy communities have significant impacts on the communities. These impacts include but are not limited to: increasing collaboration between stakeholders and the general public; improving the accuracy and quality of the decision making process; enhancing healthcare services; and improving data and information availability for health decision makers and service planners. Considering the above stated reasons, this study investigates the challenges and opportunities of planning for healthy communities with the specific aim of examining the effectiveness of participatory planning and decision systems in supporting the planning for such communities. Methods This study introduces a recently developed methodology, which is based on an online participatory decision support system. This new decision support system contributes to solve environmental and community health problems, and to plan for healthy communities. The system also provides a powerful and effective platform for stakeholders and interested members of the community to establish an empowered society and a transparent and participatory decision making environment. Results The paper discusses the preliminary findings from the literature review of this decision support system in a case study of Logan City, Queensland. Conclusion The paper concludes with future research directions and applicability of this decision support system in health service planning elsewhere.

Spatial distribution of suicide in Queensland, Australia

Background: There has been a lack of investigation into the spatial distribution and clustering of suicide in Australia, where the population density is lower than many countries and varies dramatically among urban, rural and remote areas. This study aims to examine the spatial distribution of suicide at a Local Governmental Area (LGA) level and identify the LGAs with a high relative risk of suicide in Queensland, Australia, using geographical information system (GIS) techniques.---------- Methods: Data on suicide and demographic variables in each LGA between 1999 and 2003 were acquired from the Australian Bureau of Statistics. An age standardised mortality (ASM) rate for suicide was calculated at the LGA level. GIS techniques were used to examine the geographical difference of suicide across different areas.---------- Results: Far north and north-eastern Queensland (i.e., Cook and Mornington Shires) had the highest suicide incidence in both genders, while the south-western areas (i.e., Barcoo and Bauhinia Shires) had the lowest incidence in both genders. In different age groups (≤24 years, 25 to 44 years, 45 to 64 years, and ≥65 years), ASM rates of suicide varied with gender at the LGA level. Mornington and six other LGAs with low socioeconomic status in the upper Southeast had significant spatial clusters of high suicide risk.---------- Conclusions: There was a notable difference in ASM rates of suicide at the LGA level in Queensland. Some LGAs had significant spatial clusters of high suicide risk. The determinants of the geographical difference of suicide should be addressed in future research.

Planning online : a community-based interactive decision-making model

The first use of computing technologies and the development of land use models in order to support decision-making processes in urban planning date back to as early as mid 20th century. The main thrust of computing applications in urban planning is their contribution to sound decision-making and planning practices. During the last couple of decades many new computing tools and technologies, including geospatial technologies, are designed to enhance planners' capability in dealing with complex urban environments and planning for prosperous and healthy communities. This chapter, therefore, examines the role of information technologies, particularly internet-based geographic information systems, as decision support systems to aid public participatory planning. The chapter discusses challenges and opportunities for the use of internet-based mapping application and tools in collaborative decision-making, and introduces a prototype internet-based geographic information system that is developed to integrate public-oriented interactive decision mechanisms into urban planning practice. This system, referred as the 'Community-based Internet GIS' model, incorporates advanced information technologies, distance learning, sustainable urban development principles and community involvement techniques in decision-making processes, and piloted in Shibuya, Tokyo, Japan.

Identifying rural disadvantage using a multiday travel diary

This paper identifies transport disadvantage using a 7 day activity-travel diary data from two rural case study areas. A composite participation index (PI) measure was developed for this study based on six indices measuring elements of travel and activity participation. Using the index the paper then goes on to compare these results, with the results obtained from other more traditional indicators used to identify transport disadvantage. These indicators are related to the size of activity space such as unique network distance travelled, number of unique locations visited, activity space area, activity duration, and fullness (shape) of activity spaces. The weaknesses of these indicator based measures are that: firstly, they do not take into account the relativity of the measure between different areas i.e. travel distance in terms of the wider context of available activities within an area; and secondly, these indicators are multi-dimensional and each represents a different qualitative aspect of travel and activity participation. As a result, six individual indices were developed to overcome these problems. These include: participation count index, participation length index, participation area index, participation duration index, participation type index, and participation frequency index. These are then aggregated to assess the relative performance in terms of these different indices and identify the nature of transport disadvantage. GIS was used to visualise individual travel patterns and to derive scores for both the indicator based measures and the index based measures. Factor analysis was conducted to derive weights of the individual indices to form the composite index measure. From this analysis, two intermediate indices were also derived using the underlying factors of the data related to these indices. Using the scores of all these measures, multiple regression analyses were conducted to identify patterns of transport disadvantage.

Participation index : improved measure of transport related social exclusion?

Although transport related social exclusion has been identified through zonal accessibility measures in the recent past, the debate has shifted from zonal to individual level measures. One way to identify disadvantaged individuals is to measure their size of participation in society (activity spaces). After reviewing existing literature, this paper has found two approaches to measure the activity spaces. One approach is based on the time-geographic potential path area (PPA) concept. The size of the PPA has largely been used as an indicator to the size of potential activity spaces and consequently individual accessibility. The limitations of the PPA concept have been identified in this paper and it is argued cannot be applied as a measure of social exclusion. The other approach is based on individuals’ actual travel activity participation called actual activity spaces. The size of actual activity spaces possesses a good potential measure of social exclusion. However, the indicators to measure the size of actual activity spaces are multidimensional representing the different aspects of social exclusion. The development of a unified approach has therefore been found to be important. This paper has developed a participation index (PI) using the different dimensions of actual activity spaces encountered. A framework has also been developed to operationalise the concept in GIS. The framework, on the one hand, will visualize individuals’ actual travel behaviour in real geographic space; on the other hand, it will calculate the size of their participation in society.

Mobility, accessibility and activity participation : a comparative assessment of methods to identify rural transport disadvantage

Traditionally, transport disadvantage has been identified using accessibility analysis although the effectiveness of the accessibility planning approach to improving access to goods and services is not known. This paper undertakes a comparative assessment of measures of mobility, accessibility, and participation used to identify transport disadvantage using the concept of activity spaces. A 7 day activity-travel diary data for 89 individuals was collected from two case study areas located in rural Northern Ireland. A spatial analysis was conducted to select the case study areas using criteria derived from the literature. The criteria are related to the levels of area accessibility and area mobility which are known to influence the nature of transport disadvantage. Using the activity-travel diary data individuals weekly as well as day to day variations in activity-travel patterns were visualised. A model was developed using the ArcGIS ModelBuilder tool and was run to derive scores related to individual levels of mobility, accessibility, and participation in activities from the geovisualisation. Using these scores a multiple regression analysis was conducted to identify patterns of transport disadvantage. This study found a positive association between mobility and accessibility, between mobility and participation, and between accessibility and participation in activities. However, area accessibility and area mobility were found to have little impact on individual mobility, accessibility, and participation in activities. Income vis-àvis ´ car-ownership was found to have a significant impact on individual levels of mobility, and accessibility; whereas participation in activities were found to be a function of individual levels of income and their occupational status.

Rural activity spaces and transport disadvantage : qualitative analysis of quantitative models integrating time and space

Current knowledge about the relationship between transport disadvantage and activity space size is limited to urban areas, and as a result, very little is known to date about this link in a rural context. In addition, although research has identified transport disadvantaged groups based on their size of activity spaces, these studies have, however, not empirically explained such differences and the result is often a poor identification of the problems facing disadvantaged groups. Research has shown that transport disadvantage varies over time. The static nature of analysis using the activity space concept in previous research studies has lacked the ability to identify transport disadvantage in time. Activity space is a dynamic concept; and therefore possesses a great potential in capturing temporal variations in behaviour and access opportunities. This research derives measures of the size and fullness of activity spaces for 157 individuals for weekdays, weekends, and for a week using weekly activity-travel diary data from three case study areas located in rural Northern Ireland. Four focus groups were also conducted in order to triangulate the quantitative findings and to explain the differences between different socio-spatial groups. The findings of this research show that despite having a smaller sized activity space, individuals were not disadvantaged because they were able to access their required activities locally. Car-ownership was found to be an important life line in rural areas. Temporal disaggregation of the data reveals that this is true only on weekends due to a lack of public transport services. In addition, despite activity spaces being at a similar size, the fullness of activity spaces of low-income individuals was found to be significantly lower compared to their high-income counterparts. Focus group data shows that financial constraint, poor connections both between public transport services and between transport routes and opportunities forced individuals to participate in activities located along the main transport corridors.