143 resultados para DIGITAL ELEVATION MODELS
em University of Queensland eSpace - Australia
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The Wet Tropics World Heritage Area in Far North Queens- land, Australia consists predominantly of tropical rainforest and wet sclerophyll forest in areas of variable relief. Previous maps of vegetation communities in the area were produced by a labor-intensive combination of field survey and air-photo interpretation. Thus,. the aim of this work was to develop a new vegetation mapping method based on imaging radar that incorporates topographical corrections, which could be repeated frequently, and which would reduce the need for detailed field assessments and associated costs. The method employed G topographic correction and mapping procedure that was developed to enable vegetation structural classes to be mapped from satellite imaging radar. Eight JERS-1 scenes covering the Wet Tropics area for 1996 were acquired from NASDA under the auspices of the Global Rainforest Mapping Project. JERS scenes were geometrically corrected for topographic distortion using an 80 m DEM and a combination of polynomial warping and radar viewing geometry modeling. An image mosaic was created to cover the Wet Tropics region, and a new technique for image smoothing was applied to the JERS texture bonds and DEM before a Maximum Likelihood classification was applied to identify major land-cover and vegetation communities. Despite these efforts, dominant vegetation community classes could only be classified to low levels of accuracy (57.5 percent) which were partly explained by the significantly larger pixel size of the DEM in comparison to the JERS image (12.5 m). In addition, the spatial and floristic detail contained in the classes of the original validation maps were much finer than the JERS classification product was able to distinguish. In comparison to field and aerial photo-based approaches for mapping the vegetation of the Wet Tropics, appropriately corrected SAR data provides a more regional scale, all-weather mapping technique for broader vegetation classes. Further work is required to establish an appropriate combination of imaging radar with elevation data and other environmental surrogates to accurately map vegetation communities across the entire Wet Tropics.
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A Geographic Information System (GIS) was used to model datasets of Leyte Island, the Philippines, to identify land which was suitable for a forest extension program on the island. The datasets were modelled to provide maps of the distance of land from cities and towns, land which was a suitable elevation and slope for smallholder forestry and land of various soil types. An expert group was used to assign numeric site suitabilities to the soil types and maps of site suitability were used to assist the selection of municipalities for the provision of extension assistance to smallholders. Modelling of the datasets was facilitated by recent developments of the ArcGIS® suite of computer programs and derivation of elevation and slope was assisted by the availability of digital elevation models (DEM) produced by the Shuttle Radar Topography (SRTM) mission. The usefulness of GIS software as a decision support tool for small-scale forestry extension programs is discussed.
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Examples from the Murray-Darling basin in Australia are used to illustrate different methods of disaggregation of reconnaissance-scale maps. One approach for disaggregation revolves around the de-convolution of the soil-landscape paradigm elaborated during a soil survey. The descriptions of soil ma units and block diagrams in a soil survey report detail soil-landscape relationships or soil toposequences that can be used to disaggregate map units into component landscape elements. Toposequences can be visualised on a computer by combining soil maps with digital elevation data. Expert knowledge or statistics can be used to implement the disaggregation. Use of a restructuring element and k-means clustering are illustrated. Another approach to disaggregation uses training areas to develop rules to extrapolate detailed mapping into other, larger areas where detailed mapping is unavailable. A two-level decision tree example is presented. At one level, the decision tree method is used to capture mapping rules from the training area; at another level, it is used to define the domain over which those rules can be extrapolated. (C) 2001 Elsevier Science B.V. All rights reserved.
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We re-mapped the soils of the Murray-Darling Basin (MDB) in 1995-1998 with a minimum of new fieldwork, making the most out of existing data. We collated existing digital soil maps and used inductive spatial modelling to predict soil types from those maps combined with environmental predictor variables. Lithology, Landsat Multi Spectral Scanner (Landsat MSS), the 9-s digital elevation model (DEM) of Australia and derived terrain attributes, all gridded to 250-m pixels, were the predictor variables. Because the basin-wide datasets were very large data mining software was used for modelling. Rule induction by data mining was also used to define the spatial domain of extrapolation for the extension of soil-landscape models from existing soil maps. Procedures to estimate the uncertainty associated with the predictions and quality of information for the new soil-landforms map of the MDB are described. (C) 2002 Elsevier Science B.V. All rights reserved.
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The area of private land suitable and available for growing hoop pine (Araucaria cunninghamii) on the Atherton Tablelands in North Queensland was modelled using a geographic information system (GIS). In Atherton, Eacham and Herberton shires, approximately 64,700 ha of privately owned land were identified as having a mean annual rainfall and soil type similar to Forestry Plantations Queensland (FPQ) hoop pine growth plots with an approximate growth rate of 20 m3 per annum. Land with slope of over 25° and land covered with native vegetation were excluded in the estimation. If land which is currently used for high-value agriculture is also excluded, the net area of land potentially suitable and available for expansion of hoop pine plantations is approximately 22,900 ha. Expert silvicultural advice emphasized the role of site preparation and weed control in affecting the long-term growth rate of hoop pine. Hence, sites with less than optimal fertility and rainfall may be considered as being potentially suitable for growing hoop pine at a lower growth rate. The datasets had been prepared at various scales and differing precision for their description of land attributes. Therefore, the results of this investigation have limited applicability for planning at the individual farm level but are useful at the regional level to target areas for plantation expansion.
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A method for regional assessment of the distribution of saline outbreaks is demonstrated for a large area (68 000 km(2)) in north Queensland, Australia. Soil samples were used in conjunction with a digital elevation model and a map of potentially saline discharge zones to examine the landscape distribution of soluble salts in the region. The hypothesis of atmospheric accession of salt was tested for the topographically defined catchment regions feeding into each potentially saline discharge area. Most catchments showed a salt distribution consistent with this hypothesis, i.e. %TSS was large near the discharge areas and decreased rapidly with distance uphill from the discharge areas. In some catchments, however, local saline outbreaks were apparent at significant distances uphill from discharge areas. The possibility of geological sources of this salt was examined by comparing random point distributions with the location of saline points with distance downhill from geological units (excluding points near discharge zones). The distribution of some saline outbreaks was consistent with the occurrence of Cambro-Ordovician metasediments, Devonian limestone, Upper Devonian-Lower Carboniferous volcanics, and Triassic sediments. Copyright (C) 2000 John Wiley & Sons, Ltd.
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The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).
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In this Study we examine the spectral and morphometric properties of the four important lunar mare dome fields near Cauchy, Arago, Hortensius. and Milichius. We utilize Clementine UV vis mulfispectral data to examine the soil composition of the mare domes while employing telescopic CCD imagery to compute digital elevation maps in order to determine their morphometric properties, especially flank slope, height, and edifice Volume. After reviewing previous attempts to determine topographic data for lunar domes, we propose an image-based 3D reconstruction approach which is based on a combination of photoclinometry and shape from shading. Accordingly, we devise a classification scheme for lunar Marc domes which is based on a principal component analysis of the determined spectral and morphometric features. For the effusive mare domes of the examined fields we establish four Classes, two of which are further divided into two subclasses, respectively, where each class represents distinct combinations of spectral and morphometric dome properties. As a general trend, shallow and steep domes formed out of low-TiO2 basalts are observed in the Hortensius and Milichius dome fields, while the domes near Cauchy and Arago that consist of high-TiO2 basalts are all very shallow. The intrusive domes of our data set cover a wide continuous range of spectral and morphometric quantities, generally characterized by larger diameters and shallower flank slopes than effusive domes. A comparison to effusive and intrusive mare domes in other lunar regions, highland domes, and lunar cones has shown that the examined four mare dome fields display Such a richness in spectral properties and 3D dome shape that the established representation remains valid in a more global context. Furthermore, we estimate the physical parameters of dome formation for the examined domes based on a rheologic model. Each class of effusive domes defined in terms of spectral and morphometric properties is characterized by its specific range of values for lava viscosity, effusion rate, and duration of the effusion process. For our data set we report lava viscosities between about 10(2) and 10(8) Pas, effusion rates between 25 and 600 m(3) s(-1), and durations of the effusion process between three weeks and 18 years. Lava viscosity decreases with increasing R-415/R-750 spectral ratio and thus TiO2 content; however, the correlation is not strong, implying an important influence of further parameters like effusion temperature on lava viscosity.
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Fixed-point roundoff noise in digital implementation of linear systems arises due to overflow, quantization of coefficients and input signals, and arithmetical errors. In uniform white-noise models, the last two types of roundoff errors are regarded as uniformly distributed independent random vectors on cubes of suitable size. For input signal quantization errors, the heuristic model is justified by a quantization theorem, which cannot be directly applied to arithmetical errors due to the complicated input-dependence of errors. The complete uniform white-noise model is shown to be valid in the sense of weak convergence of probabilistic measures as the lattice step tends to zero if the matrices of realization of the system in the state space satisfy certain nonresonance conditions and the finite-dimensional distributions of the input signal are absolutely continuous.
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A field study in three vineyards in southern Queensland (Australia) was carried out to develop predictive models for individual leaf area and shoot leaf area of two cultivars (Cabernet Sauvignon and Shiraz) of grapevines (Vitis Vinifera L.). Digital image analysis was used to measure leaf vein length and leaf area. Stepwise regressions of untransformed and transformed models consisting of up to six predictor variables for leaf area and three predictor variables for shoot leaf area were carried out to obtain the most efficient models. High correlation coefficients were found for log10 transformed individual leaf and shoot leaf area models. The significance of predictor variables in the models varied across vineyards and cultivars, demonstrating the discontinuous and heterogeneous nature of vineyards. The application of this work in a grapevine modeling environment and in a dynamic vineyard management context are discussed. Sample sizes for quantification of individual leaf areas and areas of leaves on shoots are proposed based on target margins of errors of sampled data.
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Entry stair in foreground.
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As seen from pool deck, looking towards The Nest. Kitchen skylight above right.
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Upper level of North-West elevation, kitchen skylight on left.