Incorporating uncertainty in environmental models informed by imagery

In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.

NSW rural land performance : 1990-2008

The annual income return for rural property is based on two major factors being commodity prices and production yields. Commodity prices paid to rural producers can vary depending on the agricultural policies of their respective countries. Free trade countries, such as Australia and New Zealand are subject to the volatility of the world commodity markets to a greater extent than those farmers in protected or subsidised markets. In countries where rural production is protected or subsidised the annual income received by rural producers has been relatively stable. However, the high cost of agricultural protection is now being questioned, particularly in relation to the increasing economic costs of government services such as health, education and housing. When combined with the agricultural production limitations of climate, topography, chemical residues and disease issues, the impact of commodity prices on rural property income is crucial in the ability of rural producers to enter into or expand their holdings in agricultural land. These problems are then reflected in the volatility of the rural land capital returns and the investment performance of this property class. This paper will address the total and capital return performance of a major agricultural area and compare these returns on the basis of both location of land and land use. The comparison will be used to determine if location or actual land use has a greater influence on rural property capital returns. This performance analysis is based on over 35,000 rural sales transactions. These transactions cover all market based rural property transactions in New South Wales, Australia for the period January 1990 to December 2008. Correlation analysis and investment performance analysis has also been carried out to determine the possible relationships between location and land use and subsequent changes in rural land capital values.

Large margin vector quantization

In this paper we describe the Large Margin Vector Quantization algorithm (LMVQ), which uses gradient ascent to maximise the margin of a radial basis function classifier. We present a derivation of the algorithm, which proceeds from an estimate of the class-conditional probability densities. We show that the key behaviour of Kohonen's well-known LVQ2 and LVQ3 algorithms emerge as natural consequences of our formulation. We compare the performance of LMVQ with that of Kohonen's LVQ algorithms on an artificial classification problem and several well known benchmark classification tasks. We find that the classifiers produced by LMVQ attain a level of accuracy that compares well with those obtained via LVQ1, LVQ2 and LVQ3, with reduced storage complexity. We indicate future directions of enquiry based on the large margin approach to Learning Vector Quantization.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

A versatile and reliable two-component system for tissue-specific gene induction in Arabidopsis

Developmental progression and differentiation of distinct cell types depend on the regulation of gene expression in space and time. Tools that allow spatial and temporal control of gene expression are crucial for the accurate elucidation of gene function. Most systems to manipulate gene expression allow control of only one factor, space or time, and currently available systems that control both temporal and spatial expression of genes have their limitations. We have developed a versatile two-component system that overcomes these limitations, providing reliable, conditional gene activation in restricted tissues or cell types. This system allows conditional tissue-specific ectopic gene expression and provides a tool for conditional cell type- or tissue-specific complementation of mutants. The chimeric transcription factor XVE, in conjunction with Gateway recombination cloning technology, was used to generate a tractable system that can efficiently and faithfully activate target genes in a variety of cell types. Six promoters/enhancers, each with different tissue specificities (including vascular tissue, trichomes, root, and reproductive cell types), were used in activation constructs to generate different expression patterns of XVE. Conditional transactivation of reporter genes was achieved in a predictable, tissue-specific pattern of expression, following the insertion of the activator or the responder T-DNA in a wide variety of positions in the genome. Expression patterns were faithfully replicated in independent transgenic plant lines. Results demonstrate that we can also induce mutant phenotypes using conditional ectopic gene expression. One of these mutant phenotypes could not have been identified using noninducible ectopic gene expression approaches.

Key competitiveness indicators for new real estate developers

Purpose – The paper aims to explore the key competitiveness indicators (KCIs) that provide the guidelines for helping new real estate developers (REDs) achieve competitiveness during their inception stage in which the organisations start their business. Design/methodology/approach – The research was conducted using a combination of various methods. A literature review was undertaken to provide a proper theoretical understanding of organisational competitiveness within RED's activities and developed a framework of competitiveness indicators (CIs) for REDs. The Delphi forecasting method is employed to investigate a group of 20 experts' perception on the relative importance between CIs. Findings – The results show that the KCIs of new REDs are capital operation capability, entrepreneurship, land reserve capability, high sales revenue from the first real estate development project, and innovation capability. Originality/value – The five KCIs of new REDs are new. In practical terms, the examination of these KCIs would help the business managers of new REDs to effectively plan their business by focusing their efforts on these key indicators. The KCIs can also help REDs provide theoretical constructs of the knowledge base on organisational competitiveness from a dynamic perspective, and assist in providing valuable experiences and in formulating feasible strategies for survival and growth.

Effects of transportation accessibility on residential property values: Application of spatial hedonic price model in Seoul, South Korea, metropolitan area

A number of studies have focused on estimating the effects of accessibility on housing values by using the hedonic price model. In the majority of studies, estimation results have revealed that housing values increase as accessibility improves, although the magnitude of estimates has varied across studies. Adequately estimating the relationship between transportation accessibility and housing values is challenging for at least two reasons. First, the monocentric city assumption applied in location theory is no longer valid for many large or growing cities. Second, rather than being randomly distributed in space, housing values are clustered in space—often exhibiting spatial dependence. Recognizing these challenges, a study was undertaken to develop a spatial lag hedonic price model in the Seoul, South Korea, metropolitan region, which includes a measure of local accessibility as well as systemwide accessibility, in addition to other model covariates. Although the accessibility measures can be improved, the modeling results suggest that the spatial interactions of apartment sales prices occur across and within traffic analysis zones, and the sales prices for apartment communities are devalued as accessibility deteriorates. Consistent with findings in other cities, this study revealed that the distance to the central business district is still a significant determinant of sales price.

The role of the internet on international market growth of Australian firms : an exploratory study

The Internet has been shown to positively influence the internationalisation activities of firms through enhanced information, knowledge and network development. Although there has been evidence of a positive impact of the Internet on internationalisation process components, it is vague as to whether the Internet has an impact on firm international market growth. This paper examines the role of the Internet in the outward internationalisation of a cross-national sample of 224 firms from Australia. The results show evidence that a there is a link between Internet usage, Internet intensity and the international market growth of the firm. The findings indicate that firms are using Internet technologies beyond simple e-mail and websites in their international marketing. For example, Internet directories and Internet market spaces are assisting international market expansion of the firm. Firms are integrating the Internet into international marketing processes such as advertising, marketing, market research and international market management as well as in data transference between company and supplier and company and customer. Further, there is evidence in this study of the statistical relationships between the use of website, e-mail and online sales with the international market growth of the firm.

Internet usage, internet marketing intensity and international marketing growth

This paper examines the role of the Internet in international marketing growth. Evidence of a positive relationship between e-mail, website usage, online marketing and advertising with international market growth was found, in terms of increased sales from new customers in new countries, new customers in existing countries, and existing customers.

New media services : ratings and recommendations websites in the travel and tourism industry

The travel and hospitality industry is one which relies especially crucially on word of mouth, both at the level of overall destinations (Australia, Queensland, Brisbane) and at the level of travellers’ individual choices of hotels, restaurants, sights during their trips. The provision of such word-of-mouth information has been revolutionised over the past decade by the rise of community-based Websites which allow their users to share information about their past and future trips and advise one another on what to do or what to avoid during their travels. Indeed, the impact of such user-generated reviews, ratings, and recommendations sites has been such that established commercial travel advisory publishers such as Lonely Planet have experienced a pronounced downturn in sales ¬– unless they have managed to develop their own ways of incorporating user feedback and contributions into their publications. This report examines the overall significance of ratings and recommendation sites to the travel industry, and explores the community, structural, and business models of a selection of relevant ratings and recommendations sites. We identify a range of approaches which are appropriate to the respective target markets and business aims of these organisations, and conclude that there remain significant opportunities for further operators especially if they aim to cater for communities which are not yet appropriately served by specific existing sites. Additionally, we also point to the increasing importance of connecting stand-alone ratings and recommendations sites with general social media spaces like Facebook, Twitter, and LinkedIn, and of providing mobile interfaces which enable users to provide updates and ratings directly from the locations they happen to be visiting. In this report, we profile the following sites: * TripAdvisor, the international market leader for travel ratings and recommendations sites, with a membership of some 11 million users; * IgoUgo, the other leading site in this field, which aims to distinguish itself from the market leader by emphasising the quality of its content; * Zagat, a long-established publisher of restaurant guides which has translated its crowdsourcing model from the offline to the online world; * Lonely Planet’s Thorn Tree site, which attempts to respond to the rise of these travel communities by similarly harnessing user-generated content; * Stayz, which attempts to enhance its accommodation search and booking services by incorporating ratings and reviews functionality; and * BigVillage, an Australian-based site attempting to cater for a particularly discerning niche of travellers; * Dopplr, which connects travel and social networking in a bid to pursue the lucrative market of frequent and business travellers; * Foursquare, which builds on its mobile application to generate a steady stream of ‘check-ins’ and recommendations for hospitality and other services around the world; * Suite 101, which uses a revenue-sharing model to encourage freelance writers to contribute travel writing (amongst other genres of writing); * Yelp, the global leader in general user-generated product review and recommendation services. In combination, these profiles provide an overview of current developments in the travel ratings and recommendations space (and beyond), and offer an outlook for further possibilities. While no doubt affected by the global financial downturn and the reduction in travel that it has caused, travel ratings and recommendations remain important – perhaps even more so if a reduction in disposable income has resulted in consumers becoming more critical and discerning. The aggregated word of mouth from many tens of thousands of travellers which these sites provide certainly has a substantial influence on their users. Using these sites to research travel options has now become an activity which has spread well beyond the digirati. The same is true also for many other consumer industries, especially where there is a significant variety of different products available – and so, this report may also be read as a case study whose findings are able to be translated, mutatis mutandis, to purchasing decisions from household goods through consumer electronics to automobiles.

An analysis of the Brisbane residential property market and the global financial crisis

The period from 2007 to 2009 covered the residential property boom from early 2000, to the property recession following the Global Financial Crisis. Since late 2008, a number of residential property markets have suffered significant falls in house prices, buth this has not been consistent across all market sectors. This paper will analyze the housing market in Brisbane Australia to determine the impact, similarities and differences that the4 GFC had on range of residential sectors across a divesified property market. Data analysis will provide an overview of residential property prices, sales and listing volumes over the study period and will provide a comparison of median house price performance across the geographic and socio-economic areas of Brisbane.