182 resultados para Hedges


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Flood modelling of urban areas is still at an early stage, partly because until recently topographic data of sufficiently high resolution and accuracy have been lacking in urban areas. However, Digital Surface Models (DSMs) generated from airborne scanning laser altimetry (LiDAR) having sub-metre spatial resolution have now become available, and these are able to represent the complexities of urban topography. The paper describes the development of a LiDAR post-processor for urban flood modelling based on the fusion of LiDAR and digital map data. The map data are used in conjunction with LiDAR data to identify different object types in urban areas, though pattern recognition techniques are also employed. Post-processing produces a Digital Terrain Model (DTM) for use as model bathymetry, and also a friction parameter map for use in estimating spatially-distributed friction coefficients. In vegetated areas, friction is estimated from LiDAR-derived vegetation height, and (unlike most vegetation removal software) the method copes with short vegetation less than ~1m high, which may occupy a substantial fraction of even an urban floodplain. The DTM and friction parameter map may also be used to help to generate an unstructured mesh of a vegetated urban floodplain for use by a 2D finite element model. The mesh is decomposed to reflect floodplain features having different frictional properties to their surroundings, including urban features such as buildings and roads as well as taller vegetation features such as trees and hedges. This allows a more accurate estimation of local friction. The method produces a substantial node density due to the small dimensions of many urban features.

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The density (BSG) of bone increases, at the osteon scale, during lifetime aging within the bone. In addition, post-mortem diagenetic change due to microbial attack produces denser bioapatite. Thus, fractionation of finely powdered bone on the basis of density should not only enable younger and older populations of osteons to be separated but also make it possible to separate out a less diagenetically altered component. We show that the density fractionation method can be used as a tool to investigate the isotopic history within an individual's lifetime, both in recent and archaeological contexts, and we use the bomb C-14 atmospheric pulse for validating the method.

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Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.

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Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.

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Shoot dieback is a problem in frequently trimmed Leyland hedges and is increasingly affecting gardeners’ choice of hedge trees, having a negative effect on a conifer nursery industry. Some damage can be attributed to the feeding by aphids, but it is unclear if there are also underlying physiological causes. In this study, we tested the hypothesis that shoot-clipping of conifer trees during adverse growing conditions (i.e. high air temperature and low soil moisture) could be leading to shoot ‘dieback’. Three-year-old Golden Leyland Cypress (x Cupressocyparis leylandii ‘Excalibur Gold’) plants were subjected to either a well-watered or droughted irrigation regime and placed in either a ‘hot’ (average day temperature = 40°C) or a ‘cool’ (average day temperature = 27°C) glasshouse compartment. Half of the plants from each glasshouse were clipped on Day 14 and again on Day 50. Measurements of soil moisture content (SMC), net CO2 assimilation rate (A), stomatal conductance (gs), branchlet xylem water potential (XWP), plant height and foliage colour were made. Within the clipped and unclipped treatments of both glasshouse compartments, plants from the droughted regime had significantly lower values for A, gs and XWP than those from the well-watered regime. However, there was no difference in these parameters between the hot and cool glasshouse compartments. The trends seen for A, gs and XWP of all treatments generally mirrored changes in SMC indicating a direct effect of water supply on these parameters. By the end of the experiment the overall foliage colour of plants from the hot glasshouse was darker than that of plants from the cool glasshouse and the overall foliage colour was also darker following shoot clipping. In general, shoot clipping led to increases in A, gs XWP and SMC. This may be due to the reduction in total leaf area leading to a greater supply of water for the remaining leaves. No shoot ‘dieback’ was observed in any treatment in response to drought stress or shoot-clipping.

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The River Lugg has particular problems with high sediment loads that have resulted in detrimental impacts on ecology and fisheries. A new dynamic, process-based model of hydrology and sediments (INCA- SED) has been developed and applied to the River Lugg system using an extensive data set from 1995–2008. The model simulates sediment sources and sinks throughout the catchment and gives a good representation of the sediment response at 22 reaches along the River Lugg. A key question considered in using the model is the management of sediment sources so that concentrations and bed loads can be reduced in the river system. Altogether, five sediment management scenarios were selected for testing on the River Lugg, including land use change, contour tillage, hedging and buffer strips. Running the model with parameters altered to simulate these five scenarios produced some interesting results. All scenarios achieved some reduction in sediment levels, with the 40% land use change achieving the best result with a 19% reduction. The other scenarios also achieved significant reductions of between 7% and 9%. Buffer strips produce the best result at close to 9%. The results suggest that if hedge introduction, contour tillage and buffer strips were all applied, sediment reductions would total 24%, considerably improving the current sediment situation. We present a novel cost-effectiveness analysis of our results where we use percentage of land removed from production as our cost function. Given the minimal loss of land associated with contour tillage, hedges and buffer strips, we suggest that these management practices are the most cost-effective combination to reduce sediment loads.

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There is widespread evidence that the volatility of stock returns displays an asymmetric response to good and bad news. This article considers the impact of asymmetry on time-varying hedges for financial futures. An asymmetric model that allows forecasts of cash and futures return volatility to respond differently to positive and negative return innovations gives superior in-sample hedging performance. However, the simpler symmetric model is not inferior in a hold-out sample. A method for evaluating the models in a modern risk-management framework is presented, highlighting the importance of allowing optimal hedge ratios to be both time-varying and asymmetric.

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This study proposes a utility-based framework for the determination of optimal hedge ratios (OHRs) that can allow for the impact of higher moments on hedging decisions. We examine the entire hyperbolic absolute risk aversion family of utilities which include quadratic, logarithmic, power, and exponential utility functions. We find that for both moderate and large spot (commodity) exposures, the performance of out-of-sample hedges constructed allowing for nonzero higher moments is better than the performance of the simpler OLS hedge ratio. The picture is, however, not uniform throughout our seven spot commodities as there is one instance (cotton) for which the modeling of higher moments decreases welfare out-of-sample relative to the simpler OLS. We support our empirical findings by a theoretical analysis of optimal hedging decisions and we uncover a novel link between OHRs and the minimax hedge ratio, that is the ratio which minimizes the largest loss of the hedged position. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark

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Taste perception has been studied frequently in young and older adult groups. This paper systematically reviews these studies to determine the effect of ageing on taste perception and establish the reported extent of sensory decline. Five databases were searched from 1900 to April 2012. Articles relating to healthy ageing in human subjects were included, reviewed and rated (Downs and Black scoring system). Sixty-nine studies investigated the effect of ageing on taste perception; forty examined detection thresholds of which twenty-three provided sufficient data for meta-analysis, eighteen reported identification thresholds and twenty-five considered supra-threshold intensity perception. Researchers investigating detection thresholds considered between one and thirteen taste compounds per paper. Overall, the consensus was that taste detection thresholds increased with age (Hedges' g = 0·91, P < 0·001), across all taste modalities. Identification thresholds were reported to be higher for older adults in seventeen out of eighteen studies. Sixteen out of twenty-five studies reported perception of taste intensity at supra-threshold levels to be significantly lower for older adults. However, six out of nine studies concerning sucrose found perceived intensity of sweet taste not to diminish with age. The findings of this systematic review suggest taste perception declines during the healthy ageing process, although the extent of decline varies between studies. Overall, the studies reviewed had low Downs and Black scores (mean 16 (SD 2)) highlighting the need for more robust large scale and longitudinal studies monitoring the impact of ageing on the sensory system, and how this influences the perception of foods and beverages.

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Hedge-mony was a site-specific visual performance involving the creation of a human maze involving 400+ performers including a large number of Deakin University students and alumni. The Red Cabbage Collective developed the work with the support of Next Wave for Festival 2006, the cultural festival of the Commonwealth Games. The Red Cabbage 'Hedges' were featured internationally in the Games advertising campaign 'See The Games We Play'.