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Analysis of geophysical networks derived from multiscale digital elevation models: a morphological approach 总被引：1，自引：0，他引：1
Tay L.T. Sagar B.S.D. Hean Teik Chuah 《Geoscience and Remote Sensing Letters, IEEE》2005,2(4):399-403
We provide a simple and elegant framework based on morphological transformations to generate multiscale digital elevation models (DEMs) and to extract topologically significant multiscale geophysical networks. These terrain features at multiple scales are collectively useful in deriving scaling laws, which exhibit several significant terrain characteristics. We present results derived from a part of Cameron Highlands DEM. 相似文献
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Abstract Artificial neural networks (ANN) have recently been popularly used in image classification. Input features to most ANNs are extracted based on a one class per pixel basis. This requires a large number of training samples and thus a slow training rate. In this paper, we describe the use of a windowing technique to extract textural features such as average intensity, second moment of intensity histogram and fractal surface dimension from an image. This method of image characterization reduces the number of training samples efficiently, yet retains a reasonable overall classification accuracy. The ANN is trained based on the back‐error propagation algorithm. The method is applied for landuse classification of Synthetic Aperture Radar (SAR) images. An example is given for a site in Kedah State, Malaysia. The SAR images (HH,HV,VV) were taken by the Canadian Centre for Remote Sensing (CCRS) CV‐580 airborne C‐band SAR system in November 1993 during their GlobeSAR mission in Malaysia. These multi‐polarization SAR images are co‐registered with a Landsat Thematic Mapper (TM) channel 5 image from same area. An overall classification accuracy of about 86.95% is achieved using windowing technique, as compared to 68.22% based on one class per pixel approach. This shows that through fractal and textural information, the windowing technique when applied in an ANN classifier has a great potential in remote sensing applications. 相似文献
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Bedload yields have been calculated using eight bedload equations at a total of 11 gauging sites in four coastal river basins in New South Wales. Comparisons of yields calculated by each equation at each site show enormous variations. Furthermore, on the Manning River, where calculations could be made on the four main tributaries and compared to those from the trunk channel below their combined confluence, there was no recognisable continuity of results. For the following reasons, the use of bedload formulae on these rivers appears to be a futile exercise. Firstly, the formulae appear to be inherently unstable under natural field conditions. Secondly, application of the formulae must rely on extrapolated flow data, as actual flow measurements are rarely conducted at discharges that are more than a small fraction of largest discharges recorded at any site. Thirdly, formulae must be applied assuming an unlimited availability of bed material; yet the rivers studied here behave as ‘conveyor belts’ of considerable power but with very low and irregular rates of sediment feed. Finally, temporal step‐functional shifts in climate and flow regimes are shown to have an important impact on estimation of sediment yields. The implication of these results is that, until there is a carefully monitored scientific program of bedload measurement or estimates of reservoir sedimentation on the rivers of south eastern Australia, there can be no reliable evaluation of sediment yields from these rivers. As a result, the impact of gravel extraction, the dispersal of mine tailings, or the construction of dams can not be adequately assessed for this region, nor probably for the rest of Australia. 相似文献
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