53 resultados para spatial resolution
em University of Queensland eSpace - Australia
Resumo:
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).
Resumo:
An anaerobic landfill leachate bioreactor was operated with crystalline cellulose and sterile landfill leacbate until a steady state was reached. Cellulose hydrolysis, acidogenesis, and methanogenesis were measured. Microorganisms attached to the cellulose surfaces were hypothesized to be the cellulose hydrolyzers. 16S rRNA gene clone libraries were prepared from this attached fraction and also from the mixed fraction (biomass associated with cellulose particles and in the planktonic phase). Both clone libraries were dominated by Firmicutes phylum sequences (100% of the attached library and 90% of the mixed library), and the majority fell into one of five lineages of the clostridia. Clone group 1 (most closely related to Clostridium stercorarium), clone group 2 (most closely related to Clostridium thermocellum), and clone group 5 (most closely related to Bacteroides cellulosolvens) comprised sequences in Clostridium group III. Clone group 3 sequences were in Clostridium group XIVa (most closely related to Clostridium sp. strain XB90). Clone group 4 sequences were affiliated with a deeply branching clostridial lineage peripherally associated with Clostridium group VI. This monophyletic group comprises a new Clostridium cluster, designated cluster VIa. Specific fluorescence in situ hybridization (FISH) probes for the five groups were designed and synthesized, and it was demonstrated in FISH experiments that bacteria targeted by the probes for clone groups 1, 2, 4, and 5 were very abundant on the surfaces of the cellulose particles and likely the key cellulolytic microorganisms in the landfill bioreactor. The FISH probe for clone group 3 targeted cells in the planktonic phase, and these organisms were hypothesized to be glucose fermenters.
Resumo:
Socioeconomic considerations should have an important place in reserve design, Systematic reserve-selection tools allow simultaneous optimization for ecological objectives while minimizing costs but are seldom used to incorporate socioeconomic costs in the reserve-design process. The sensitivity of this process to biodiversity data resolution has been studied widely but the issue of socioeconomic data resolution has not previously been considered. We therefore designed marine reserves for biodiversity conservation with the constraint of minimizing commercial fishing revenue losses and investigated how economic data resolution affected the results. Incorporating coarse-resolution economic data from official statistics generated reserves that were only marginally less costly to the fishery than those designed with no attempt to minimize economic impacts. An intensive survey yielded fine-resolution data that, when incorporated in the design process, substantially reduced predicted fishery losses. Such an approach could help minimize fisher displacement because the least profitable grounds are selected for the reserve. Other work has shown that low-resolution biodiversity data can lead to underestimation of the conservation value of some sites, and a risk of overlooking the most valuable areas, and we have similarly shown that low-resolution economic data can cause underestimation of the profitability of some sites and a risk of inadvertently including these in the reserve. Detailed socioeconomic data are therefore an essential input for the design of cost-effective reserve networks.
Resumo:
Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone health. The objective of this work was to determine if the structural attributes of savanna riparian zones in northern Australia can be detected from commercially available remotely sensed image data. Two QuickBird images and coincident field data covering sections of the Daly River and the South Alligator River - Barramundie Creek in the Northern Territory were used. Semi-variograms were calculated to determine the characteristic spatial scales of riparian zone features, both vegetative and landform. Interpretation of semi-variograms showed that structural dimensions of riparian environments could be detected and estimated from the QuickBird image data. The results also show that selecting the correct spatial resolution and spectral bands is essential to maximize the accuracy of mapping spatial characteristics of savanna riparian features. The distribution of foliage projective cover of riparian vegetation affected spectral reflectance variations in individual spectral bands differently. Pan-sharpened image data enabled small-scale information extraction (< 6 m) on riparian zone structural parameters. The semi-variogram analysis results provide the basis for an inversion approach using high spatial resolution satellite image data to map indicators of savanna riparian zone health.
Resumo:
Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone condition. The objective of this work was to compare the Tropical Rapid Appraisal of Riparian Condition (TRARC) method to a satellite image based approach. TRARC was developed for rapid assessment of the environmental condition of savanna riparian zones. The comparison assessed mapping accuracy, representativeness of TRARC assessment, cost-effectiveness, and suitability for multi-temporal analysis. Two multi-spectral QuickBird images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map riparian health indicators (RHIs) including percentage canopy cover, organic litter, canopy continuity, stream bank stability, and extent of tree clearing. Spectral vegetation indices, image segmentation and supervised classification were used to produce RHI maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based RHI measurements. Results showed that TRARC transects were required to cover at least 3% of the study area to obtain a representative sample. The mapping accuracy and costs of the image based approach were compared to those of the ground based TRARC approach. Results proved that TRARC was more cost-effective at smaller scales (1-100km), while image based assessment becomes more feasible at regional scales (100-1000km). Finally, the ability to use both the image and field based approaches for multi-temporal analysis of RHIs was assessed. Change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method was only able to identify more gross scale changes. In conclusion, results from both methods were considered to complement each other if used at appropriate spatial scales.
Resumo:
Bulk density of undisturbed soil samples can be measured using computed tomography (CT) techniques with a spatial resolution of about 1 mm. However, this technique may not be readily accessible. On the other hand, x-ray radiographs have only been considered as qualitative images to describe morphological features. A calibration procedure was set up to generate two-dimensional, high-resolution bulk density images from x-ray radiographs made with a conventional x-ray diffraction apparatus. Test bricks were made to assess the accuracy of the method. Slices of impregnated soil samples were made using hardsetting seedbeds that had been gamma scanned at 5-mm depth increments in a previous study. The calibration procedure involved three stages: (i) calibration of the image grey levels in terms of glass thickness using a staircase made from glass cover slips, (ii) measurement of ratio between the soil and resin mass attenuation coefficients and the glass mass attenuation coefficient, using compacted bricks of known thickness and bulk density, and (iii) image correction accounting for the heterogeneity of the irradiation field. The procedure was simple, rapid, and the equipment was easily accessible. The accuracy of the bulk density determination was good (mean relative error 0.015), The bulk density images showed a good spatial resolution, so that many structural details could be observed. The depth functions were consistent with both the global shrinkage and the gamma probe data previously obtained. The suggested method would be easily applied to the new fuzzy set approach of soil structure, which requires generation of bulk density images. Also, it would be an invaluable tool for studies requiring high-resolution bulk density measurement, such as studies on soil surface crusts.
Resumo:
On 7 February 2000 an atypical orange discolouration of snowfields in the central Southern Alps, New Zealand occurred following the passage of a cold front. Analysis of snow samples identified fine orangey-brown dust mixed with much coarser grey dust. Air parcel forward trajectories from dust sources in southern and central Australia, where dust storms were reported on 4 February 2000, were computed to identify the deposits source. Geochemical analyses of the dust deposit using 26 trace elements, unaffected by regional air pollution and gravitational sorting, indicate that 20% of the dust was sourced from western New South Wales, with 45% from the eastern Eyre Peninsula of South Australia and the remaining 35% was local New Zealand dust. This provenancing approach provides a spatial resolution of long travelled dust sourcing not previously achieved. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
Reasons for performing study: Obtaining magnetic resonance images of the inner hoof wall tissue at the microscopic level would enable early accurate diagnosis of laminitis and therefore more effective therapy. Objectives: To optimise magnetic resonance imaging (MRI) parameters in order to obtain the highest possible resolution of the structures beneath the equine hoof wall. Methods: Magnetic resonance microscopy (MRM) was performed in front feet from 6 cadaver horses using T-2-weighted fast spin echo (FSE-T-2), and T-1-weighted gradient echo (GRE-T-1) sequences. Results: In T-2 weighted FSE images most of the stratum medium showed no signal, however the coronary, terminal and sole papillae were visible. The stratum lamellatum was clearly visible and primary epidermal lamellae could be differentiated from dermal lamellae. Conclusion: Most structures beneath the hoof wall were differentiated. Conventional scanners for diagnostic MRI in horses are low or high field. However this study used ultra-high field scanners currently not available for clinical use. Signal-to-noise ratio (SIN) increases as a function of field strength. An increase of spatial resolution of the image results in a decreased SIN. SIN can also be improved with better coils and the resolution of high field MRI scanners will increase as technology develops and surface array coils become more readily available. Potential relevance: Although MR images with microscopic resolution were obtained ex vivo, this study demonstrates the potential for detection of lamellar pathology as it occurs. Early recognition of the development of laminitis to instigate effective therapy at an earlier stage and may improve the outcome for laminitic horses. Clinical MR is now readily available at 3 T, while 4 T, 7 T and 9 T systems are being used for human whole body applications.
Resumo:
Traditional field sampling approaches for ecological studies of restored habitat can only cover small areas in detail, con be time consuming, and are often invasive and destructive. Spatially extensive and non-invasive remotely sensed data can make field sampling more focused and efficient. The objective of this work was to investigate the feasibility and accuracy of hand-held and airborne remotely sensed data to estimate vegetation structural parameters for an indicator plant species in a restored wetland. High spatial resolution, digital, multispectral camera images were captured from an aircraft over Sweetwater Marsh (San Diego County, California) during each growing season between 1992-1996. Field data were collected concurrently, which included plant heights, proportional ground cover and canopy architecture type, and spectral radiometer measurements. Spartina foliosa (Pacific cordgrass) is the indicator species for the restoration monitoring. A conceptual model summarizing the controls on the spectral reflectance properties of Pacific cordgrass was established. Empirical models were developed relating the stem length, density, and canopy architecture of cordgrass to normalized-difference-vegetation-index values. The most promising results were obtained from empirical estimates of total ground cover using image data that had been stratified into high, middle, and low marsh zones. As part of on-going restoration monitoring activities, this model is being used to provide maps of estimated vegetation cover.
Resumo:
The Montreal Process indicators are intended to provide a common framework for assessing and reviewing progress toward sustainable forest management. The potential of a combined geometrical-optical/spectral mixture analysis model was assessed for mapping the Montreal Process age class and successional age indicators at a regional scale using Landsat Thematic data. The project location is an area of eucalyptus forest in Emu Creek State Forest, Southeast Queensland, Australia. A quantitative model relating the spectral reflectance of a forest to the illumination geometry, slope, and aspect of the terrain surface and the size, shape, and density, and canopy size. Inversion of this model necessitated the use of spectral mixture analysis to recover subpixel information on the fractional extent of ground scene elements (such as sunlit canopy, shaded canopy, sunlit background, and shaded background). Results obtained fron a sensitivity analysis allowed improved allocation of resources to maximize the predictive accuracy of the model. It was found that modeled estimates of crown cover projection, canopy size, and tree densities had significant agreement with field and air photo-interpreted estimates. However, the accuracy of the successional stage classification was limited. The results obtained highlight the potential for future integration of high and moderate spatial resolution-imaging sensors for monitoring forest structure and condition. (C) Elsevier Science Inc., 2000.