...
首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Classification of sediments on exposed tidal flats in the German Bight using mufti-frequency radar data
【24h】

Classification of sediments on exposed tidal flats in the German Bight using mufti-frequency radar data

机译:利用多频雷达数据对德国湾裸露的滩涂中的沉积物进行分类

获取原文
获取原文并翻译 | 示例
           

摘要

We present a new method for the extraction of roughness parameters of sand ripples on exposed tidal flats from mufti-frequency synthetic aperture radar (SAR) data. The method is based on the Integral Equation Model (IEM) which predicts the normalized radar cross-section (MRCS) of randomly rough dielectric surfaces. The data used for this analysis were acquired in the German Bight of the North Sea by the Spaceborne Imaging Radar-C/X-Band SAR (SIR-C/X-SAR) in 1994. In-situ measurements of the root-mean-squared (rms) height and the correlation length of the sand ripples clearly demonstrate a relationship between these roughness parameters and the C-band NRCS determined from an ERS SAR image. Using the IEM we have calculated NRCS isolines for the three frequency bands deployed by SIR-C/X-SAR (L, C, and X band), as a function of the rms height and the correlation length of the sand ripples. For each SIR-C/X-SAR image pixel these two roughness parameters were determined from the intersections of the NRCS isolines at different radar bands, and they were used for a crude sediment classification for a small test area at the German North Sea coast. Comparing our results with available sediment maps, we conclude that the presented method is very promising for tidal flat classification by using data from presently existing airborne and future spaceborne mufti-frequency SAR systems. (c) 2007 Elsevier Inc. All rights reserved.
机译:我们提出了一种从多频合成孔径雷达(SAR)数据中提取潮汐滩上沙纹粗糙度参数的新方法。该方法基于积分方程模型(IEM),该模型可预测随机粗糙介电表面的归一化雷达横截面(MRCS)。用于此分析的数据是在1994年由星载成像雷达-C / X-Band SAR(SIR-C / X-SAR)在北海的德国湾获得的。平方(均方根)高度和沙子波纹的相关长度清楚地表明了这些粗糙度参数与从ERS SAR图像确定的C波段NRCS之间的关系。使用IEM,我们已经计算了SIR-C / X-SAR部署的三个频带(L,C和X频带)的NRCS等值线,作为rms高度和沙纹的相关长度的函数。对于每个SIR-C / X-SAR图像像素,这两个粗糙度参数是从不同雷达波段的NRCS等值线的交点确定的,它们被用于德国北海沿岸一小区域的粗沉积物分类。将我们的结果与可用的泥沙图进行比较,我们得出结论,通过使用当前现有的机载和未来的星载多频SAR系统的数据,所提出的方法对于潮滩分类非常有前途。 (c)2007 Elsevier Inc.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号