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首页> 外文学位 >Caracterisation des occupations du sol en milieu urbain par imagerie radar.
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Caracterisation des occupations du sol en milieu urbain par imagerie radar.

机译：用雷达图像表征城市地区的土地覆盖。

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摘要

This study aims to test the relevance of medium and high-resolution SAR images on the characterization of the types of land use in urban areas. To this end, we have relied on textural approaches based on second-order statistics. Specifically, we look for texture parameters most relevant for discriminating urban objects. We have used in this regard Radarsat-1 in fine polarization mode and Radarsat-2 HH fine mode in dual and quad polarization and ultrafine mode HH polarization. The land uses sought were dense building, medium density building, low density building, industrial and institutional buildings, low density vegetation, dense vegetation and water. We have identified nine texture parameters for analysis, grouped into families according to their mathematical definitions in a first step. The parameters of similarity / dissimilarity include Homogeneity, Contrast, the Differential Inverse Moment and Dissimilarity. The parameters of disorder are Entropy and the Second Angular Momentum. The Standard Deviation and Correlation are the dispersion parameters and the Average is a separate family. It is clear from experience that certain combinations of texture parameters from different family used in classifications yield good results while others produce kappa of very little interest. Furthermore, we realize that if the use of several texture parameters improves classifications, its performance ceils from three parameters. The calculation of correlations between the textures and their principal axes confirm the results.;Despite the good performance of this approach based on the complementarity of texture parameters, systematic errors due to the cardinal effects remain on classifications. To overcome this problem, a radiometric compensation model was developed based on the radar cross section (SER). A radar simulation from the digital surface model of the environment allowed us to extract the building backscatter zones and to analyze the related backscatter. Thus, we were able to devise a strategy of compensation of cardinal effects solely based on the responses of the objects according to their orientation from the plane of illumination through the radar's beam. It appeared that a compensation algorithm based on the radar cross section was appropriate. Some examples of the application of this algorithm on HH polarized RADARSAT-2 images are presented as well. Application of this algorithm will allow considerable gains with regard to certain forms of automation (classification and segmentation) at the level of radar imagery thus generating a higher level of quality in regard to visual interpretation. Application of this algorithm on RADARSAT-1 and RADARSAT-2 images with HH, HV, VH, and VV polarisations helped make considerable gains and eliminate most of the classification errors due to the cardinal effects.
机译：这项研究的目的是测试中高分辨率SAR图像与表征城市地区土地使用类型的相关性。为此，我们依靠基于二阶统计量的纹理方法。具体来说，我们寻找与区分城市物体最相关的纹理参数。在这方面，我们已使用处于精细偏振模式的Radarsat-1和处于双极化和四偏振以及超精细模式HH偏振的Radarsat-2 HH精细模式。寻求的土地用途是密集建筑，中密度建筑，低密度建筑，工业和公共建筑，低密度植被，茂密植被和水。第一步，我们已经确定了九个纹理参数进行分析，并根据它们的数学定义将它们分为几类。相似性/不相似性的参数包括同质性，对比度，微分逆矩和不相似性。障碍的参数是熵和第二角动量。标准偏差和相关性是色散参数，而平均值是一个单独的族。从经验中可以明显看出，在分类中使用的来自不同族的纹理参数的某些组合产生了良好的结果，而其他组合则产生的兴趣很小。此外，我们意识到，如果使用多个纹理参数可以改善分类，则其性能取决于三个参数。通过计算纹理与其主轴之间的相关性，可以确认结果。尽管基于纹理参数的互补性，该方法具有良好的性能，但是由于基数效应而导致的系统误差仍然存在于分类中。为了克服这个问题，开发了基于雷达横截面（SER）的辐射补偿模型。来自环境的数字表面模型的雷达仿真使我们能够提取建筑物的后向散射区并分析相关的后向散射。因此，我们能够仅根据物体从照明平面到雷达光束的方向来确定物体的响应，从而设计出一种基本效果的补偿策略。看来基于雷达横截面的补偿算法是合适的。还给出了该算法在HH极化RADARSAT-2图像上应用的一些示例。该算法的应用将在雷达图像级别的某些自动化形式（分类和分段）方面获得可观的收益，从而在视觉解释方面产生更高的质量。该算法在具有HH，HV，VH和VV极化的RADARSAT-1和RADARSAT-2图像上的应用有助于获得可观的收益，并消除了由于基数效应而引起的大多数分类错误。

著录项

  • 作者

    Codjia, Claude.;

  • 作者单位

    Universite de Montreal (Canada).;

  • 授予单位 Universite de Montreal (Canada).;
  • 学科 Remote Sensing.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 199 p.
  • 总页数 199
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 肿瘤学;
  • 关键词

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