首页> 外文学位 >A STRUCTURAL APPROACH TOWARDS DRAINAGE PATTERN RECOGNITION (REMOTE SENSING, PHOTOINTERPRETATION, IMAGE UNDERSTANDING, LANDFORMS).
【24h】

A STRUCTURAL APPROACH TOWARDS DRAINAGE PATTERN RECOGNITION (REMOTE SENSING, PHOTOINTERPRETATION, IMAGE UNDERSTANDING, LANDFORMS).

机译:识别排水模式的结构方法(遥感,光解,图像理解,地形)。

获取原文
获取原文并翻译 | 示例

摘要

The drainage pattern is the most important single characteristic for determining the structure and type of a landform. This research effort has developed a structural pattern recognition approach and the associated software for the identification of drainage patterns. A structural model for drainage pattern description was developed. This model included the decomposition of drainage patterns in a hierarchical organization of line segments. Every line segment was characterized by a set of attributes. The arcs connecting the nodes of the hierarchy were characterized by attributes of the relations between the line segments of the connected nodes. Drainage pattern attributes were designed to express the topologic and geometric relationships among the high-level segments of the drainage patterns. These attributes were derived as composite attributes or attribute functions. Classification was performed by a decision tree that facilitated the testing of the occurrence of certain key attributes between an input pattern and a stored description of a prototype. The DPA system has been evaluated with real and artificial patterns from all the eight classes and it has performed satisfactorily.
机译:排水方式是确定地形结构和类型最重要的单一特征。这项研究工作已经开发出一种结构模式识别方法以及用于识别排水模式的相关软件。开发了排水模式描述的结构模型。该模型包括线段的分层组织中排水模式的分解。每个线段都有一组属性。连接层次结构节点的弧线的特征是所连接节点的线段之间的关系属性。设计了排水模式属性,以表达排水模式的高级片段之间的拓扑和几何关系。这些属性是作为复合属性或属性函数导出的。分类由决策树执行,决策树有助于测试输入模式和原型的存储描述之间某些关键属性的出现。 DPA系统已通过所有八个类别的真实模式和人工模式进行了评估,并且运行令人满意。

著录项

  • 作者

    ARGIALAS, DEMETRE P.;

  • 作者单位

    The Ohio State University.;

  • 授予单位 The Ohio State University.;
  • 学科 Engineering Civil.
  • 学位 Ph.D.
  • 年度 1985
  • 页码 149 p.
  • 总页数 149
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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