Using a cartographic modeling language to manipulate spectral satellite imagery

Land related information about the Earth's surface is commonIJ found in two forms: (1) map infornlation and (2) satellite image da ta. Satellite imagery provides a good visual picture of what is on the ground but complex image processing is required to interpret features in an image scene. Increasingly, methods are being sought to integrate the knowledge embodied in mop information into the interpretation task, or, alternatively, to bypass interpretation and perform biophysical modeling directly on derived data sources. A cartographic modeling language, as a generic map analysis package, is suggested as a means to integrate geographical knowledge and imagery in a process-oriented view of the Earth. Specialized cartographic models may be developed by users, which incorporate mapping information in performing land classification. In addition, a cartographic modeling language may be enhanced with operators suited to processing remotely sensed imagery. We demonstrate the usefulness of a cartographic modeling language for pre-processing satellite imagery, and define two nerv cartographic operators that evaluate image neighborhoods as post-processing operations to interpret thematic map values. The language and operators are demonstrated with an example image classification task.

Theory and applications of fuzzy Volterra integral equations

Formulations of fuzzy integral equations in terms of the Aumann integral do not reflect the behavior of corresponding crisp models. Consequently, they are ill-adapted to describe physical phenomena, even when vagueness and uncertainty are present. A similar situation for fuzzy ODEs has been obviated by interpretation in terms of families of differential inclusions. The paper extends this formalism to fuzzy integral equations and shows that the resulting solution sets and attainability sets are fuzzy and far better descriptions of uncertain models involving integral equations. The investigation is restricted to Volterra type equations with mildly restrictive conditions, but the methods are capable of extensive generalization to other types and more general assumptions. The results are illustrated by integral equations relating to control models with fuzzy uncertainties.

High resolution 3-D imaging via multi-pass SAR

Spaceborne/airborne synthetic aperture radar (SAR) systems provide high resolution two-dimensional terrain imagery. The paper proposes a technique for combining multiple SAR images, acquired on flight paths slightly separated in the elevation direction, to generate high resolution three-dimensional imagery. The technique could be viewed as an extension to interferometric SAR (InSAR) in that it generates topographic imagery with an additional dimension of resolution. The 3-D multi-pass SAR imaging system is typically characterised by a relatively short ambiguity length in the elevation direction. To minimise the associated ambiguities we exploit the relative phase information within the set of images to track the terrain landscape. The SAR images are then coherently combined, via a nonuniform DFT, over a narrow (in elevation) volume centred on the 'dominant' terrain ground plane. The paper includes a detailed description of the technique, background theory, including achievable resolution, and the results of an experimental study.

Mapping glider habitat in dry eucalypt forests for Montreal Process indicator 1.1: Fragmentation of forest types

Accurate habitat mapping is critical to landscape ecological studies such as required for developing and testing Montreal Process indicator 1.1e, fragmentation of forest types. This task poses a major challenge to remote sensing, especially in mixedspecies, variable-age forests such as dry eucalypt forests of subtropical eastern Australia. In this paper, we apply an innovative approach that uses a small section of one-metre resolution airborne data to calibrate a moderate spatial resolution model (30 m resolution; scale 1:50 000) based on Landsat Thematic Mapper data to estimate canopy structural properties in St Marys State Forest, near Maryborough, south-eastern Queensland. The approach applies an image-processing model that assumes each image pixel is significantly larger than individual tree crowns and gaps to estimate crown-cover percentage, stem density and mean crown diameter. These parameters were classified into three discrete habitat classes to match the ecology of four exudivorous arboreal species (yellowbellied glider Petaurus australis, sugar glider P. breviceps, squirrel glider P. norfolcensis , and feathertail glider Acrobates pygmaeus), and one folivorous arboreal marsupial, the greater glider Petauroides volans. These species were targeted due to the known ecological preference for old trees with hollows, and differences in their home range requirements. The overall mapping accuracy, visually assessed against transects (n = 93) interpreted from a digital orthophoto and validated in the field, was 79% (KHAT statistic = 0.72). The KHAT statistic serves as an indicator of the extent that the percentage correct values of the error matrix are due to ‘true’ agreement verses ‘chance’ agreement. This means that we are able to reliably report on the effect of habitat loss on target species, especially those with a large home range size (e.g. yellow-bellied glider). However, the classified habitat map failed to accurately capture the spatial patterning (e.g. patch size and shape) of stands with a trace or sub-dominance of senescent trees. This outcome makes the reporting of the effects of habitat fragmentation more problematic, especially for species with a small home range size (e.g. feathertail glider). With further model refinement and validation, however, this moderateresolution approach offers an important, cost eff e c t i v e advancement in mapping the age of dry eucalypt forests in the region.

Automated regional myocardial displacement for facilitating the interpretation of dobutamine echocardiography

Quantification of stress echocardiography may overcome the training requirements and subjective nature of visual wall motion score (WMS) assessment, but quantitative approaches may be difficult to apply and require significant time for image processing. The integral of long-axis myocardial velocity is displacement, which may be represented as a color map over the left ventricular myocardium. This study was designed to explore the feasibility and accuracy of measuring long-axis myocardial displacement, derived from tissue Doppler, for the detection of coronary artery disease (CAD) during dobutamine stress echocardiography (DBE). One hundred thirty patients underwent standard DBE, including 30 patients at low risk of CAD, 30 patients with normal coronary angiography (both groups studied to define normal ranges of displacement), and 70 patients who underwent coronary angiography in whom the accuracy of normal ranges was tested. Regional myocardial displacement was obtained by analysis of color tissue Doppler apical images acquired at peak stress. Displacement was compared with WMS, and with the presence of CAD by angiography. The analysis time was 3.2 +/- 1.5 minutes per patient. Segmental displacement was correlated with wall motion (normal 7.4 +/- 3.2 mm, ischemia 5.8 +/- 4.2 mm, viability 4.6 +/- 3.0 mm, scar 4.5 +/- 3.5 mm, p <0.001). Reversal of normal base-apex displacement was an insensitive (19%) but specific (90%) marker of CAD. The sum of displacements within each vascular territory had a sensitivity and specificity of 89% and 79%, respectively, for prediction of significant CAD, compared with 86% and 78%, respectively, for WMS (p = NS). The displacements in the basal segments had a sensitivity and specificity of 83% and 78%, respectively (p = NS). Regional myocardial displacement during DBE is feasible and offers a fast and accurate method for the diagnosis of CAD. (C),2002 by Excerpta Medica, Inc.

Empirical evidence for ultrametric structure in multi-layer perceptron error surfaces

Combinatorial optimization problems share an interesting property with spin glass systems in that their state spaces can exhibit ultrametric structure. We use sampling methods to analyse the error surfaces of feedforward multi-layer perceptron neural networks learning encoder problems. The third order statistics of these points of attraction are examined and found to be arranged in a highly ultrametric way. This is a unique result for a finite, continuous parameter space. The implications of this result are discussed.

Experimental investigation of contaminant transport in coastal groundwater

Contaminant transport in coastal aquifers is of increasing interest since, with the development of coastal areas, contaminants from surface sources may enter coastal aquifers and pollute the groundwater flow. Coastal groundwater flow is complicated because of the presence of a freshwater-saltwater diffusion zone and the tidal variation of sea level at the seaward end. This paper investigates experimentally the behaviour of contaminant plumes with different densities in an unconfined coastal aquifer. Experiments were performed in a flow tank filled with glass beads as the porous medium. Results show that the dense contaminant has a more diffusive front than the less dense one in the seaward direction towards the coastline. The plume becomes more diffusive when it travels closer to the saltwater interface. On the contrary, the less dense contaminant presents a relatively sharp outline. It tends to migrate in the upper portion of the aquifer and exits in a concentrated manner over a small discharge area at the coastline, not further seaward under the sea. Non-dimensional parameters show that instabilities occur in our experiments for a density difference of 1.2% or larger between the contaminant and the ambient water. The experimental results provide guidance for field monitoring and numerical modelling. (C) 2002 Elsevier Science Ltd. All rights reserved.

Resolution enhancement by subtraction of confocal signals taken at different pinhole sizes

Subtractive imaging in confocal fluorescence light microscopy is based on the subtraction of a suitably weighted widefield image from a confocal image. An approximation to a widefield image can be obtained by detection with an opened confocal pinhole. The subtraction of images enhances the resolution in-plane as well as along the optic axis. Due to the linearity of the approach, the effect of subtractive imaging in Fourier-space corresponds to a reduction of low spatial frequency contributions leading to a relative enhancement of the high frequencies. Along the direction of the optic axis this also results in an improved sectioning. Image processing can achieve a similar effect. However, a 3D volume dataset must be acquired and processed, yielding a result essentially identical to subtractive imaging but superior in signal-to-noise ratio. The latter can be increased further with the technique of weighted averaging in Fourier-space. A comparison of 2D and 3D experimental data analysed with subtractive imaging, the equivalent Fourier-space processing of the confocal data only, and Fourier-space weighted averaging is presented. (C) 2003 Elsevier Ltd. All rights reserved.