Design a zero energy house in Brisbane, Australia

Due to the increasing energy demand and global warming effects, energy efficient buildings have become increasingly important in the modern construction industry. This research is conducted to evaluate the energy performance, financial feasibility and potential energy savings of zero energy houses. Through the use of building computer simulation technique, a 5 stars energy rated house was modelled and validated by comparing the energy performance of a base case scenario to a typical house in Brisbane. By integrating energy reduction strategies and utilizing onsite renewable energy such as solar energy, zero energy performance is achieved. It is found that approximately 66 % energy savings can be achieved in the household annual energy usage by focusing on maximizing the thermal performance of building envelope, minimizing the energy requirements and incorporating solar energy technologies.

Mapping the experiential in contemporary dance

The research questions how a ‘lived experience’ of contemporary dance could be deepened for the audience. It presents a series of choreographic ‘tools’ to create alternative frameworks of presentation that challenge the dominant modes of creation, presentation and meaning making in contemporary dance. The five tools established and applied in this research are: variations of site, liminality, audience agency, audience-performer proximity and performer qualities. These tools are framed as a series of calibrated scales that allow choreographers to map decisions made in the studio in relation to potential audience engagement. The research houses multiple presentation formats from the traditional to the avant-garde and opens up possibilities for analysis of a wide range of artistic dance works. This research presents options for choreographers to map how audiences experience their work and offers opportunities to engage audiences in new and exciting ways.

The right fit: Christian Street House

Embracing the pleasures of constraint, this new house by James Russell Architect was designed to contextually inspired principles, creating a social and relaxed environment that suits the location’s subtropical way of life.

Children’s personal exposure to air pollution in rural villages in Bhutan

Exposure assessment studies conducted in developing countries have been based on fixed-site monitoring to date. This is a major deficiency, leading to errors in estimating the actual exposures, which are a function of time spent and pollutant concentrations in different microenvironments. This study quantified school children’s daily personal exposure to ultrafine particles (UFP) using real-time monitoring, as well as volatile organic compounds (VOCs) and NO2 using passive sampling in rural Bhutan in order to determine the factors driving the exposures. An activity diary was used to track children’s time activity patterns, and difference in mean exposure levels across sex and indoor/outdoor were investigated with ANOVA. 82 children, attending three primary schools participated in this study; S1 and S2 during the wet season and S3 during the dry season. Mean daily UFP exposure (cm-3) was 1.08 × 104 for children attending S1, 9.81 × 103 for S2, and 4.19 × 104 for S3. The mean daily NO2 exposure (µg m-3) was 4.27 for S1, 3.33 for S2 and 5.38 for S3 children. Likewise, children attending S3 also experienced higher daily exposure to a majority of the VOCs than those attending S1 and S2. Time-series of UFP personal exposures provided detailed information on identifying sources of these particles and quantifying their contributions to the total daily exposures for each microenvironment. The highest UFP exposure resulted from cooking/eating, contributing to 64% of the daily exposure, due to firewood combustion in houses using traditional mud cookstoves. The lowest UFP exposures were during the hours that children spent outdoors at school. The outcomes of this study highlight the significant contributions of lifestyle and socio-economic factors in personal exposures and have applications in environmental risk assessment and household air pollution mitigation in Bhutan.

The effect of ground leases on house prices in Helsinki

One imperfection in housing markets is imperfect knowledge about legal interests such as ground leases. Both actual reduced legal interest as well as uncertainty surrounding rights and future lease payments for houses constructed on leased land may affect prices relative to houses built on freehold land. We use regression analysis of sales prices of condominium transactions in Helsinki to examine the effect ground leases have on house prices. We find that prices on condominiums constructed on leased lots are discounted at least 5 %, on average. In addition, we see that the announcement of potentially large increases in base rents upon renewal contributes to the discount.

Senior House Operations in Finland

This article analyzes the operations of a sample of rental independent living senior apartments in Tampere, Finland. We compare 10 properties containing 421 units owned by one nonprofit and two for-profit housing providers. We examine costs and revenues across properties using data collected through interviews and a survey of company representatives and property managers. The results indicate that until the recent economic downturn, these senior houses generally experienced fast initial lease-up and low turnover but relatively long vacancies for some units when re-leasing. Performance varies among properties.

Finnish seniors’ move to a senior house: Examining the push and pull factors

The purpose of this article is to explore the factors influencing residential decisions of Finnish seniors. Analysis draws on qualitative data gathered from in-depth interviews and open-ended survey questions completed by 37 seniors living in three independent living facilities in Finland. Content analysis was used to identify key factors pushing residents out of their former living situations and pulling them into their respective independent living facility. Analysis indicates that different senior houses attract different types of residents. Nevertheless, as a group, they reported similar motivational factors relating to community, physical, and social environments and to their personal circumstances.

Awareness and attitudes toward age-restricted communities in Finland

The average population age has been increasing for decades. In the U.S., the history of retirement communities in some states is relatively long, reaching back to the 1920s. In Finland, with one of the fastest-growing elderly population and highest total dependency ratios, seniors housing is a relatively new market within the residential housing business. Some studies have reported that only a small percentage of seniors are willing to move into age-restricted communities in Finland. This study analyzes awareness and attitudes of Finnish people toward age-restricted housing for seniors and toward seniors living in these communities. The results show that the majority of Finns were undecided if “senior houses” were the same as assisted living facilities. The respondents associated age-restricted communities with institutional housing for lonely elderly people with illnesses. The results of this study will help investors and developers understand how potential customers see age-restricted housing for seniors. Also, managers of senior houses can use the results for clarifying the idea of senior houses.

What does built environment research have to do with risk mitigation, resilience and disaster recovery?

One could argue that the nature of our housing stock is a key determining factor in the ability of our citizens to manage risk, be resilient to various natural and human events, and to recover from these events. Recent research has been examining current challenges posed by our housing stock and exploring potential solutions from a range of perspectives. The aim of this paper is to discuss key findings from recent built environment research in Australia to initiate cross-sectorial discussion and debate about the implications and opportunities for other sectors such as emergency management and insurance. Three recent building research projects are discussed: - Heat waves The impact of heat waves on houses and occupants, and proposed changes to building regulations, air conditioning standards and building design, to reduce risks associated with heat waves. - Net zero energy homes Exploration of the potential benefits of a strategic optimization of building quality, energy and water efficiency, and household or community level distributed energy and water services for disaster management and recovery. - Building information Mapping of the flow of information about residential buildings, and the potential for national or regional building files (in a similar manner to personal medical records) to assist all parties to make more informed decisions that impact on housing sustainability and community resilience. The paper discusses how sustainability, environmental performance and resilience are inter-related, and can be supported by building files. It concludes with a call for increased cross-sectorial collaboration to explore opportunities for a whole-of-systems approach to our built environment that addresses a range of economic and environmental challenges as well as disaster and emergency management.

Impact of wildfires and floods on property values: A before and after analysis

One of the most evident casualties of a natural disaster is the property market. The private and social costs from such events run into millions of dollars. In this paper, we use a unique dataset to examine the impact on residential house prices affected by natural disasters using a hedonic property (HP) values approach. For this purpose, we use data before and after a wildfire and floods from Rockhampton in central Queensland, Australia. The data is unique because one suburb was affected by wildfires and another was affected by floods. For the analysis, three suburbs namely Frenchville, Park Avenue and Norman Gardens are used. Frenchville was significantly affected by wildfires in the latter part of 2009 and to a lesser extent in 2012, while Park Avenue was affected by floods at the end of 2010, January 2011–2013. Norman Gardens, which was relatively unaffected, is used as a control site. This enables us to examine the before and after effects on property values in the three suburbs. The results confirm that soon after a natural disaster property prices in affected areas decrease even though the large majority of individual houses remain unaffected. Furthermore, the results indicate that the largely unaffected suburb may gain immediately after a natural disaster but this gain may disappear if natural disasters continue to occur in the area/region due to the stigma created. The results have several important policy decision and welfare implications which are briefly discussed in the paper.

Decision fusion for reliable flood mapping using remote sensing images

Flood extent mapping is a basic tool for flood damage assessment, which can be done by digital classification techniques using satellite imageries, including the data recorded by radar and optical sensors. However, converting the data into the information we need is not a straightforward task. One of the great challenges involved in the data interpretation is to separate the permanent water bodies and flooding regions, including both the fully inundated areas and the wet areas where trees and houses are partly covered with water. This paper adopts the decision fusion technique to combine the mapping results from radar data and the NDVI data derived from optical data. An improved capacity in terms of identifying the permanent or semi-permanent water bodies from flood inundated areas has been achieved. Computer software tools Multispec and Matlab were used.

Middle-aged and elderly Finnish households considering moving, their preferences, and potential downsizing amidst changing life course and housing careers

We examine the moving and housing preferences of middle-aged and older in Finland, a country where population composition and movement through the life course are changing. A logistic regression reveals that middle-aged, moderate income residents, renters, those who have lived in their houses only a short time, and residents who are generally dissatisfied are most likely to consider moving. Downsizing appeals to residents with lower incomes who live alone, and who have been in their current houses longer. All potential movers agree on the importance of transportation access and a neighborhood grocery store; however, those preferring to downsize are also interested in house and neighborhood design as well as services that will allow aging in place. Income limitations may create affordability problems for some potential movers.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.