The analysis of landscape pattern through remote sensing data is relatively widespread in landscape ecology and landscape planning. However, the lack of comparability of results between different image-processing methods and across spatial resolutions limits the potential usefulness of landscape pattern indices. In this study, 96 sampling plots in Switzerland were investigated covering land-use intensities ranging from old-growth forest to intensive agricultural landscapes. The sampling plots were captured using fused Landsat ETM-IRS, Quickbird and aerial photograph data. In order to quantify landscape patterns, seven patch indices (derived by object-oriented classification) and six grey-value indices were extracted from the sampling plots. Principal component analysis was applied to the datasets, with the amount of variance in the first four axes compared among the sampling plots. Biplots of indices and sampling plots derived from all datasets were investigated with respect to land-use intensity patterns. PCA results indicated that increasing spatial resolution corresponded to a slight increase in explained variance. Moreover, image grey-values explained more variance between the sampling plots than segmented patch indices. Furthermore, biplots of grey-value indices were capable of grouping sampling plots according to the land-use intensity gradient, while segmented patch indices failed to adequately represent these.
The finite-element formulation proposed in this paper is for the frequency domain and covers the entire range from static/stationary fields to wave propagation. It does not involve any frequency-dependent thresholds, leads to complex symmetric system matrices and unique solutions, and applies to the most general structures, comprising both lossy and lossless regions. Compared with non-stabilized methods, e.g., the electric field formulation, the price to be paid is one extra scalar potential in the lossy region. Numerical examples demonstrate that the proposed method is well-suited for direct and iterative solvers, and remains stable in the static case.Index Terms-Electromagnetic fields, finite-element (FE) method, low-frequency (LF) stable, Maxwell equations, potential formulation.
Key WordsColumn liquid chromatography Anion exchange chromatography Polymeric bonded phase Pulsed amperometric detection Mono-, di-, oligosaccharides
SummaryThis paper reports on the use of a polymer-based, strong anion-exchange stationary phase for rapid, selective and sensitive analysis of physiological important mono-, di-and oligosaccharides by high-performance anion-exchange chromatography (HPAEC) with pulsed amperometric detection (PAD) under alkaline conditions. The adsorbent was obtained by direct nitration of 3 and 5 I~m, spherical non-porous highly cross-linked, styrene-divinylbenzene copolymer (PS-DVB) beads, followed by reduction of superficially introduced nitro groups with nascent hydrogen and quaternization of the resultant amino groups with iodomethane. Extended exposure to high pressure and strong alkaline conditions did not have any untoward effect on mechanical stability and chromatographic performance. A comparison of the 3 and 5 I~m beads showed, that the synthesized 3 I~m highly cross-linked PS-DVB particles are the preferred phase for the separation of monosaccharides and the 5 Ixm particles are preferable for the separation of oligosaccharides. To demonstrate the suitability for the analysis of complex samples, the optimized and validated system was used for the determination of glucose, fructose and sucrose in apple juice and other soft drinks such as Coca Cola. Finally, analysis within a few minutes without sample pretreatment down to a lower limit of detection of 0.174-0.504 I~g mL 1 at a linearitywith R 2 > 0.994 and a reproducibility higher than 98% further confirmed the efficiency of these polymeric sorbents.
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