10 resultados para Above-ground biomass

em Queensland University of Technology - ePrints Archive


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A parametric study was carried out to investigate the effects on reconstructed images from a ground penetrating radar (GPR) due to (a) the centre frequency of the GPR excitation pulse, (b) the height of transmitting and receiving antennas above ground level, and (c) the proximity of the buried objects. An integrated software package was developed to streamline the computer simulation based on synthetic data generated by GPRMax.

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This thesis is a study of naturally occurring radioactive materials (NORM) activity concentration, gamma dose rate and radon (222Rn) exhalation from the waste streams of large-scale onshore petroleum operations. Types of activities covered included; sludge recovery from separation tanks, sludge farming, NORM storage, scaling in oil tubulars, scaling in gas production and sedimentation in produced water evaporation ponds. Field work was conducted in the arid desert terrain of an operational oil exploration and production region in the Sultanate of Oman. The main radionuclides found were 226Ra and 210Pb (238U - series), 228Ra and 228Th (232Th - series), and 227Ac (235U - series), along with 40K. All activity concentrations were higher than the ambient soil level and varied over several orders of magnitude. The range of gamma dose rates at a 1 m height above ground for the farm treated sludge had a range of 0.06 0.43 µSv h 1, and an average close to the ambient soil mean of 0.086 ± 0.014 µSv h 1, whereas the untreated sludge gamma dose rates had a range of 0.07 1.78 µSv h 1, and a mean of 0.456 ± 0.303 µSv h 1. The geometric mean of ambient soil 222Rn exhalation rate for area surrounding the sludge was mBq m 2 s 1. Radon exhalation rates reported in oil waste products were all higher than the ambient soil value and varied over three orders of magnitude. This study resulted in some unique findings including: (i) detection of radiotoxic 227Ac in the oil scales and sludge, (ii) need of a new empirical relation between petroleum sludge activity concentrations and gamma dose rates, and (iii) assessment of exhalation of 222Rn from oil sludge. Additionally the study investigated a method to determine oil scale and sludge age by the use of inherent behaviour of radionuclides as 228Ra:226Ra and 228Th:228Ra activity ratios.

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Road surface macro-texture is an indicator used to determine the skid resistance levels in pavements. Existing methods of quantifying macro-texture include the sand patch test and the laser profilometer. These methods utilise the 3D information of the pavement surface to extract the average texture depth. Recently, interest in image processing techniques as a quantifier of macro-texture has arisen, mainly using the Fast Fourier Transform (FFT). This paper reviews the FFT method, and then proposes two new methods, one using the autocorrelation function and the other using wavelets. The methods are tested on pictures obtained from a pavement surface extending more than 2km's. About 200 images were acquired from the surface at approx. 10m intervals from a height 80cm above ground. The results obtained from image analysis methods using the FFT, the autocorrelation function and wavelets are compared with sensor measured texture depth (SMTD) data obtained from the same paved surface. The results indicate that coefficients of determination (R2) exceeding 0.8 are obtained when up to 10% of outliers are removed.

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Commuting in various transport modes represents an activity likely to incur significant exposure to traffic emissions. This study investigated the determinants and characteristics of exposure to ultrafine (< 100 nm) particles (UFPs) in four transport modes in Sydney, with a specific focus on exposure in automobiles, which remain the transport mode of choice for approximately 70% of Sydney commuters. UFP concentrations were measured using a portable condensation particle counter (CPC) inside five automobiles commuting on above ground and tunnel roadways, and in buses, ferries and trains. Determinant factors investigated included wind speed, cabin ventilation (automobiles only) and traffic volume. The results showed that concentrations varied significantly as a consequence of transport mode, vehicle type and ventilation characteristics. The effects of wind speed were minimal relative to those of traffic volume (especially heavy diesel vehicles) and cabin ventilation, with the latter proving to be a strong determinant of UFP ingress into automobiles. The effect of ~70 minutes of commuting on total daily exposure was estimated using a range of UFP concentrations reported for several microenvironments. A hypothetical Sydney resident commuting by automobile and spending 8.5 minutes of their day in the M5 East tunnel could incur anywhere from a lower limit of 3-11% to an upper limit of 37-69% of daily UFP exposure during a return commute, depending on the concentrations they encountered in other microenvironments, the type of vehicle they used and the ventilation setting selected. However, commute-time exposures at either extreme of the values presented are unlikely to occur in practice. The range of exposures estimated for other transport modes were comparable to those of automobiles, and in the case of buses, higher than automobiles.

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Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

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Particles emitted by vehicles are known to cause detrimental health effects, with their size and oxidative potential among the main factors responsible. Therefore, understanding the relationship between traffic composition and both the physical characteristics and oxidative potential of particles is critical. To contribute to the limited knowledge base in this area, we investigated this relationship in a 4.5 km road tunnel in Brisbane, Australia. On-road concentrations of ultrafine particles (<100 nm, UFPs), fine particles (PM2.5), CO, CO2 and particle associated reactive oxygen species (ROS) were measured using vehicle-based mobile sampling. UFPs were measured using a condensation particle counter and PM2.5 with a DustTrak aerosol photometer. A new profluorescent nitroxide probe, BPEAnit, was used to determine ROS levels. Comparative measurements were also performed on an above-ground road to assess the role of emission dilution on the parameters measured. The profile of UFP and PM2.5 concentration with distance through the tunnel was determined, and demonstrated relationships with both road gradient and tunnel ventilation. ROS levels in the tunnel were found to be high compared to an open road with similar traffic characteristics, which was attributed to the substantial difference in estimated emission dilution ratios on the two roadways. Principal component analysis (PCA) revealed that the levels of pollutants and ROS were generally better correlated with total traffic count, rather than the traffic composition (i.e. diesel and gasoline-powered vehicles). A possible reason for the lack of correlation with HDV, which has previously been shown to be strongly associated with UFPs especially, was the low absolute numbers encountered during the sampling. This may have made their contribution to in-tunnel pollution largely indistinguishable from the total vehicle volume. For ROS, the stronger association observed with HDV and gasoline vehicles when combined (total traffic count) compared to when considered individually may signal a role for the interaction of their emissions as a determinant of on-road ROS in this pilot study. If further validated, this should not be overlooked in studies of on- or near-road particle exposure and its potential health effects.

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Regrowing forests on cleared land is a key strategy to achieve both biodiversity conservation and climate change mitigation globally. Maximizing these co-benefits, however, remains theoretically and technically challenging because of the complex relationship between carbon sequestration and biodiversity in forests, the strong influence of climate variability and landscape position on forest development, the large number of restoration strategies possible, and long time-frames needed to declare success. Through the synthesis of three decades of knowledge on forest dynamics and plant functional traits combined with decision science, we demonstrate that we cannot always maximize carbon sequestration by simply increasing the functional trait diversity of trees planted. The relationships between plant functional diversity, carbon sequestration rates above-ground and in the soil are dependent on climate and landscape positions. We show how to manage ‘identities’ and ‘complementarities’ between plant functional traits in order to achieve systematically maximal co-benefits in various climate and landscape contexts. We provide examples of optimal planting and thinning rules that satisfy this ecological strategy and guide the restoration of forests that are rich in both carbon and plant functional diversity. Our framework provides the first mechanistic approach for generating decision-making rules that can be used to manage forests for multiple objectives, and supports joined carbon credit and biodiversity conservation initiatives, such as Reducing Emissions from Deforestation and forest Degradation REDD+. The decision framework can also be linked to species distribution models and socio-economic models in order to find restoration solutions that maximize simultaneously biodiversity, carbon stocks and other ecosystem services across landscapes. Our study provides the foundation for developing and testing cost-effective and adaptable forest management rules to achieve biodiversity, carbon sequestration and other socio-economic co-benefits under global change.

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This paper describes the results of experiments made in the vicinity of EHV overhead lines to investigate sources of clouds of charged particles using simultaneously-recording arrays of electric field meters to measure direct electric fields produced under ion clouds. E-field measurements, made at one metre above ground level, are correlated with wind speed and direction, and with measurements from ionisation counters and audible corona effects to identify possible positions of sources of corona on adjacent power lines. Measurements made in dry conditions on EHV lines in flat remote locations with no adjacent buildings or large vegetation indicate the presence of discrete ion sources associated with high stress points on some types of line hardware such as connectors and conductor spacers. Faulty line components such as insulators and line fittings are also found to be a possible source of ion clouds.

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Airborne particulate pollutant is considered to be one of the major harmful emissions produced by vehicle engines as it has been directly linked to serious health problems. Passengers spend long times at bus stations and may be exposed to high concentrations of pollution. Particle pollution at two bus stations in Brisbane, Australia were monitored. The two bus stations consisted of markedly different site geography and surroundings with one situated in a street canyon and the other elevated above ground level. The same flow of traffic operated through both stations. Real time measurements of ultrafine particle concentration, size distribution and meteorological conditions were carried out on the platform continuously over several days. The results showed that the particle number concentrations were significantly different at the two stations, suggesting that the layout of site geometry and surroundings was a dominant determining factor through the injection of fresh air into the station platforms and the rates of dilution.

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Increasing threat of terrorism highlights the importance of enhancing the resilience of underground tunnels to all hazards. This paper develops, applies and compares the Arbitrary Lagrangian Eulerian (ALE) and Smooth Particle Hydrodynamics (SPH) techniques to treat the response of buried tunnels to surface explosions. The results and outcomes of the two techniques were compared, along with results from existing test data. The comparison shows that the ALE technique is a better method for describing the tunnel response for above ground explosion with regards to modeling accuracy and computational efficiency. The ALE technique was then applied to treat the blast response of different types of segmented bored tunnels buried in dry sand. Results indicate that the most used modern ring type segmented tunnels were more flexible for in-plane response, however, they suffered permanent drifts between the rings. Hexagonal segmented tunnels responded with negligible drifts in the longitudinal direction, but the magnitudes of in-plane drifts were large and hence hazardous for the tunnel. Interlocking segmented tunnels suffered from permanent drifts in both the longitudinal and transverse directions. Multi-surface radial joints in both the hexagonal and interlocking segments affected the flexibility of the tunnel in the transverse direction. The findings offer significant new information in the behavior of segmented bored tunnels to guide their future implementation in civil engineering applications.