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Brisbane, Australia

Eslami-Andargoli L.,Griffith University | Dale P.E.R.,Griffith University | Dale P.E.R.,Environmental Futures Center | Sipe N.,Griffith University | And 2 more authors.
Estuarine, Coastal and Shelf Science | Year: 2010

Land use/cover and mangrove spatial changes were assessed for ten sites and their sub-catchments in Southeast Queensland, Australia. Two time periods were involved: 1972-1990, a period of relatively high rainfall, and 1990-2004, which was significantly drier. Aerial photographs and Landsat satellite imagery were used to map the inter-tidal wetlands and classify the land use/cover in the sub-catchments. A Maximum Likelihood Classification was used to map three types of land cover: agriculture, built-up and plantation forest. Mangroves (mainly Avicennia marina) were the focus as they have been recorded over recent decades encroaching into salt marsh. The Mangrove-Salt marsh Interface (MSI) Index was developed to quantify the relative opportunity for mangroves to expand into salt marshes, based on the shared boundary between them. The index showed a consistent relationship with mangrove expansion and change. To address problems of high dimensionality and multi-collinearity of predictor variables, a Partial Least Squares Regression (PLSR) model was used. A key finding of this research was that the contribution of environmental variables to spatial changes in the mangroves was altered following a reduction in rainfall. For example, agriculture had more influence on mangrove expansion and change during the wet period than during the dry period. © 2010 Elsevier Ltd. Source


Eslami-Andargoli L.,Griffith University | Dale P.,Griffith University | Dale P.,Environmental Futures Center | Sipe N.,Griffith University | Sipe N.,Urban Research Program
Austral Ecology | Year: 2013

The aim of this study was to investigate the interactions of natural and anthropogenic variables at different spatial scales related to changes in mangrove distribution during a relatively wet period (1972-1990) and a dry period (1991-2004) in subtropical eastern Australia. Previous research has demonstrated that mangroves are encroaching into salt marsh. Mangrove spatial change in southeast Queensland is related generally to landscape variables especially during the relatively wet period. What has not been explored is the spatial scale of the influence under the two rainfall regimes (wet and dry) and that is the aim of this paper. Ten sites were examined at different levels of resolution including catchment, sub-catchment and two buffer zones (1000 and 500m), under the period of relatively higher and lower rainfall. Land use was ascertained from Landsat satellite imagery using Maximum Likelihood Classification techniques. Partial least squares regression analysis was used to study the relationships between the predictor variables and the rate of change in the mangrove distribution. The research has found that the impact of land use/cover on the encroachment of mangrove into saltmarsh can vary and appears to be related to rainfall patterns, which in turn affect hydrological connectivity. A major finding of this research was that the changing spatial patterns of mangroves during the wet period was more a function of land use/cover pattern and population density at the sub-catchment level, whereas during drier periods it was more affected by the local effects of nearby land use/cover in buffer zones. © 2012 Ecological Society of Australia. Source


Brown A.L.,Urban Research Program | Tomerini D.,Urban Research Program
Road and Transport Research | Year: 2011

The paper reports the distributions of noise level maxima, LAFmax, generated during the pass-by of over 85 000 vehicles in service on urban arterials and motorways. These were measured under normal traffic and vehicle operating conditions on multilane roadways. They are indicative of the instantaneous maximum noise levels that would be experienced in the free field at the set-back distance of the facades of the first row of many dwellings fronting urban roadways in Australia, from vehicles travelling in the nearside lane. Noise levels are reported separately for four classes of vehicle and for roadways with five different posted speed limits. Results have been standardised as free-field levels 15 m from the centreline of vehicle travel. The data were collected in Brisbane but can be assumed to be representative of noise level maxima from vehicles operating throughout Australia. Maximum noise levels increase with vehicle class (from cars through to articulated trucks) and with roadway speed limits. The within-vehicle-class variance is large and the distributions of maxima from different vehicle classes overlap extensively. Sound Power Levels of the observed vehicles agree well with those from the European IMAGINE emission model. This investigation contributes essential information regarding the source and levels of noise events adjacent to urban road networks - the likely determinant of human sleep disturbance. Source

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