Comparison of roving-window and search-window techniques for characterising landscape morphometry

Brazil`s State of Sao Paulo Research Foundation

Avaliação da disponibilidade de espaços verdes públicos no contexto urbano e a sua relação com a perceção dos residentes. Um estudo para a cidade de Bragança

Os espaços verdes públicos urbanos são muito importantes no contexto urbano. Influenciam de diversas formas na qualidade de vida das populações, proporcionando benefícios ambientais, sociais e econômicos. A fim de avaliar a disponibilidade destes espaços na cidade de Bragança, foram realizadas análises utilizando indicadores, com apoio dos software ArcGIS 9.3 e QGis 2.14.0-Essen, que permitiram avaliar a oferta destes espaços nas suas diferentes tipologias e categorias dimensionais. Para o efeito foram aplicados os indicadores: Percentagem de espaços verdes, Espaços verdes per capita, Distância média, Índice de Área Verde por Área de Implantação e Índice de Área Verde por Área Coberta. Posteriormente, procedeu-se à aplicação de inquéritos a fim de avaliar as perceções e atitudes de uma amostra da população de Bragança, realizando análises descritivas e estatísticas, com recurso ao software SPSS17, buscando descrever a atual relação com os espaços verdes e usando testes não paramétricos para identificar diferenças entre subgrupos da amostra, numa análise centrada em dois níveis: a escala urbana e a escala de Bairro. Procurando avaliar possíveis alterações futuras, foram testados cenários realistas, um correspondendo à introdução de espaços verdes em terrenos na posse da Autarquia e outro considerando a ampliação das áreas verdes previstas no Plano de Urbanização de Bragança de 2010. Os Resultados permitiram identificar diferenças relevantes na oferta de espaços verdes da cidade. Aplicando os indicadores foi possível verificar que existe a concentração de espaços verdes de maior dimensão na zona central da cidade, denotando um claro desequilíbrio na introdução de novos espaços em zonas de expansão urbana. Os inquéritos aplicados possibilitaram constatar que os inquiridos que possuem maior disponibilidade de espaços verdes em seu bairro de residência apresentam respostas mais satisfatórias em relação a acessibilidade e a aparência visual e paisagística dos bairros. Da análise de cenários resulta que com a implantação de novos espaços verdes, para as duas análises, ocorreria uma melhoria da oferta e distribuição dos espaços verdes na cidade permitindo um maior reequilíbrio face à concentração na zona central, melhorando a acessibilidade para toda a população.

Measuring neighbourhood sustainability : a comparative analysis of residential types in Malaysia

The expansion of city-regions, the increase in the standard of living and changing lifestyles have collectively led to an increase in housing demand. New residential areas are encroaching onto the city fringes including suburban and green field areas. Large and small developers are actively building houses ranging from a few blocks to master-planned style projects. These residential developments, particularly in major urban areas, represent a large portion of urban land use in Malaysia, and, thus, have become a major contributor to overall urban sustainability. There are three main types that comprise the mainstream, and form integral parts to contemporary urban residential developments, namely, subdivision developments, piecemeal developments, and master-planned developments. Many new master-planned developments market themselves as environmentally friendly, and provide layouts that encompass sustainable design and development. To date, however, there have been limited studies conducted to examine such claims or to ascertain which of these three residential development layouts is more sustainable. To fill this gap, this research was undertaken to develop a framework for assessing the level of sustainability of residential developments, focusing on their layouts at the neighbourhood level. The development of this framework adopted a mixed method research strategy and embedded research design to achieve the study aim and objectives. Data were collected from two main sources, where quantitative data were gathered from a three-round Delphi survey and spatial data from a layout plan. Sample respondents for surveys were selected from among experts in the field of the built environment, both from Malaysia and internationally. As for spatial data, three case studies – master-planned, piecemeal and subdivision developments representing different types of neighbourhood developments in Malaysia have been selected. Prior to application on the case studies, the appropriate framework was subjected to validation to ascertain its robustness for application in Malaysia. Following the application of the framework on the three case studies the results revealed that master-planned development scored a better level of sustainability compared to piecemeal and subdivision developments. The results generated from this framework are expected to provide evidence to the policy makers and development agencies as well as provide an awareness of the level of sustainability and the necessary collective efforts required for developing sustainable neighbourhoods. Continuous assessment can facilitate a comparison of sustainability over time for neighbourhoods as a means to monitor changes in the level of sustainability. In addition, the framework is able to identify any particular indicator (issue) that causes a significant impact on sustainability.

Neighbourhood Diversity and Social Trust: An Empirical Analysis of Interethnic Contact and Group-specific Effects

To date, neighbourhood studies on ethnic diversity and social trust have revealed inconclusive findings. In this paper, three innovations are proposed in order to systemise the knowledge about neighbourhood ethnic diversity and the development of social trust. First, it is proposed to use a valid trust measure that is sensitive to the local neighbourhood context. Second, the paper argues for a conception of organically evolved neighbourhoods, rather than using local administrative units as readily available proxies for neighbourhood divisions. Thirdly, referring to intergroup contact theory and group-specific effects of diversity, the paper challenges the notion that ethnic diversity has overwhelmingly negative effects on social trust.

The European Union’s Rule of Law Promotion in its Neighbourhood: A Structural Foreign Policy Analysis. EU Diplomacy Paper 04/2013

The promotion of the rule of law has become an important dimension of the European Union’s relations towards its neighbourhood. The rule of law is, however, a complex and multifaceted notion and the EU’s rule of law promotion policy has often been criticised for being either inefficient or self-interested. This collection of short papers offers an analysis of various case studies using the analytical framework of structural foreign policy (SFP) developed by Stephan Keukeleire. It aims to promote an original analytical perspective on the EU’s foreign policy but also to critically test and further develop the SFP analytical framework. The contributions of this collection consist of the shortened version of students’ Master’s theses written at the College of Europe during the academic year 2011-2012 in the framework of the course “The EU as a Foreign Policy Actor” taught by Stephan Keukeleire, Chairholder of the TOTAL Chair of EU Foreign Policy in the Department of EU International Relations and Diplomacy Studies.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Measuring neighbourhood sustainability performance: an indexing model for Gold Coast City, Australia

The aim of this research is to develop an indexing model to evaluate sutainability performance of urban settings, in order to assess environmental impacts of urban development and to provide planning agencies an indexing model as a decision support tool to be used in curbing negative impacts of urban development. Indicator-based sustainability assessment is embraced as the method. Neigbourhood-level urban form and transport related indicators are derived from the literature by conducting a content analysis and finalised via a focus group meeting. The model is piloted on three suburbs of Gold Coast City, Australia. Final neighbourhood level sustainability index score was calculated by employing equal weighting schema. The results of the study show that indexing modelling is a reasonably practical method to measure and visualise local sustainability performance, which can be employed as an effective communication and decision making tool.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.

Experiences of neighbourhood walkability among older Australians living in high density inner-city areas

Walking as an out-of-home mobility activity is recognised for its contribution to healthy and active ageing. The environment can have a powerful effect on the amount of walking activity undertaken by older people, thereby influencing their capacity to maintain their wellbeing and independence. This paper reports the findings from research examining the experiences of neighbourhood walking for 12 older people from six different inner-city high density suburbs, through analysis of data derived from travel diaries, individual time/space activity maps (created via GPS tracking over a seven-day period and GIS technology), and in-depth interviews. Reliance on motor vehicles, the competing interests of pedestrians and cyclists on shared pathways and problems associated with transit systems, public transport, and pedestrian infrastructure emerged as key barriers to older people venturing out of home on foot. GPS and GIS technology provide new opportunities for furthering understanding of the out-of-home mobility of older populations.

Kernel analysis on Grassmann manifolds for action recognition

Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

Rating for sustainable subdivision neighbourhood design (RSSND) : case of Bangkok metropolitan region (BMR), Thailand an eco-efficiency modelling approach

Bangkok Metropolitan Region (BMR) is the centre for various major activities in Thailand including political, industry, agriculture, and commerce. Consequently, the BMR is the highest and most densely populated area in Thailand. Thus, the demand for houses in the BMR is also the largest, especially in subdivision developments. For these reasons, the subdivision development in the BMR has increased substantially in the past 20 years and generated large numbers of subdivision developments (AREA, 2009; Kridakorn Na Ayutthaya & Tochaiwat, 2010). However, this dramatic growth of subdivision development has caused several problems including unsustainable development, especially for subdivision neighbourhoods, in the BMR. There have been rating tools that encourage the sustainability of neighbourhood design in subdivision development, but they still have practical problems. Such rating tools do not cover the scale of the development entirely; and they concentrate more on the social and environmental conservation aspects, which have not been totally accepted by the developers (Boonprakub, 2011; Tongcumpou & Harvey, 1994). These factors strongly confirm the need for an appropriate rating tool for sustainable subdivision neighbourhood design in the BMR. To improve level of acceptance from all stakeholders in subdivision developments industry, the new rating tool should be developed based on an approach that unites the social, environmental, and economic approaches, such as eco-efficiency principle. Eco-efficiency is the sustainability indicator introduced by the World Business Council for Sustainable Development (WBCSD) since 1992. The eco-efficiency is defined as the ratio of the product or service value according to its environmental impact (Lehni & Pepper, 2000; Sorvari et al., 2009). Eco-efficiency indicator is concerned to the business, while simultaneously, is concerned with to social and the environment impact. This study aims to develop a new rating tool named "Rating for sustainable subdivision neighbourhood design (RSSND)". The RSSND methodology is developed by a combination of literature reviews, field surveys, the eco-efficiency model development, trial-and-error technique, and the tool validation process. All required data has been collected by the field surveys from July to November 2010. The ecoefficiency model is a combination of three different mathematical models; the neighbourhood property price (NPP) model, the neighbourhood development cost (NDC) model, and the neighbourhood occupancy cost (NOC) model which are attributable to the neighbourhood subdivision design. The NPP model is formulated by hedonic price model approach, while the NDC model and NOC model are formulated by the multiple regression analysis approach. The trial-and-error technique is adopted for simplifying the complex mathematic eco-efficiency model to a user-friendly rating tool format. Credibility of the RSSND has been validated by using both rated and non-rated of eight subdivisions. It is expected to meet the requirements of all stakeholders which support the social activities of the residents, maintain the environmental condition of the development and surrounding areas, and meet the economic requirements of the developers.