地理科学进展 ›› 2008, Vol. 27 ›› Issue (1): 118-124.doi: 10.11820/dlkxjz.2008.01.016

• 地理信息与模型应用 • 上一篇    

基于DEM 的水系自动提取与分级研究进展

孙崇亮1,2, 王卷乐1   

  1. 1. 中国科学院地理科学与资源研究所, 北京100101
    2. 中国科学院研究生院, 北京100049
  • 收稿日期:2007-05-01 修回日期:2007-12-01 出版日期:2008-01-25 发布日期:2008-01-25
  • 作者简介:孙崇亮(1979-),男,汉族,博士研究生,主要从事遥感与地理信息系统应用研究.E- mail:suncl@lreis.ac.cn
  • 基金资助:

    国家科技基础条件平台建设项目(2005DKA32300).

The Progr ess on Automatic Basin Str eamline Extr acting &|Classifying Methods Based on DEM

SUN Chongliang1,2, WANG Juanle1   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101
    2. Graduate University of the Chinese Academy of Sciences, Beijing 100049
  • Received:2007-05-01 Revised:2007-12-01 Online:2008-01-25 Published:2008-01-25

摘要:

随着信息化技术的快速发展,基于DEM产品提取水系等数据已经变得不再困难,但是,目前无论在水系自 动提取方面还是自动分级方面,都存在很多需要改进之处。论文分析了自动提取河网水系与流域边界,以及河网水 系分级的研究进展,在此基础上总结了当前存在的问题:(1)水系自动提取中的洼地处理、平地区域流向处理等; (2)河网水系自动分级方法中的参数单一,准确性较差,并且缺少水系实体之间的互相关联关系等问题。在此基础 上,提出了基于地理特征建立水系分级模型以解决分级问题的构想。

关键词: 进展, 模型, 水系分级, 水系提取

Abstract:

With rapid development of the modern information technology, it is not a problem to extract waterlines automatically based on DEM products. However, there exist many problems to be solved whether on the current automatic water streamline extracting methods or on the current classifying methods based on DEM. The singularity of the classifying parameters leads to a lower precision of the water - streamline classifying order result, as well as a lack of interknit between waterlines. On this background, this paper analyzes the progresses on the study of automatic basin streamline extracting & classifying methods. At the same time, this paper concludes the current problems with the waterline auto- extracting methods based on DEM, such as the problems for disposal of the sink and plateau areas, as well as the problems with the waterline auto- classifying methods, such as mis- match between the newly produced results and the traditional maps. Last, the paper puts up the idea of constructing the waterline auto- classifying model based on FBGIS in order to solve the problems of current waterline auto- classifying methods.

Key words: model, progress, waterline classifying, waterline extracting