地理科学 ›› 2012, Vol. 32 ›› Issue (3): 368-373.doi: 10.13249/j.cnki.sgs.2012.03.368

• • 上一篇    下一篇

基于ASTER GDEM数据喀斯特区域地貌类型划分与分析

马士彬1(), 安裕伦2()   

  1. 1. 贵州省六盘水师范学院生物与地理科学系, 贵州 六盘水 553004
    2. 贵州师范大学地理与环境科学学院, 贵州 贵阳 550001
  • 收稿日期:2010-11-10 修回日期:2011-01-18 出版日期:2012-03-25 发布日期:2012-03-25
  • 作者简介:

    作者简介:马士彬(1982-),男,黑龙江齐齐哈尔人,讲师,研究方向为环境遥感与信息系统。E-mail:msb88.com@163.com

  • 基金资助:
    贵州省科技攻关项目[黔科合GY字(2008)3022]、国家重点基础研究发展973计划项目(2006CB403200)、贵州省教育厅自然科学项目(黔教科2010098)资助

Auto-classification of Landform in Karst Region Based on ASTER GDEM

Shi-bin MA1(), Yu-lun AN2()   

  1. 1.Department of Biology and Geography, Liupanshui Normal University, Liupanshui, Guizhou 553004, China
    2. School of Geography and Environment, Guizhou Normal University, Guiyang, Guizhou 550001, China
  • Received:2010-11-10 Revised:2011-01-18 Online:2012-03-25 Published:2012-03-25

摘要:

以30 m分辨率ASTER GDEM数据为基础,通过GIS空间分析和非监督分类的方法进行地貌基本类型的自动划分。研究结果表明:① ASTERGDEM数据能够满足1:10万比例尺下喀斯特区域的地表形态表达; ② 以流域为单位提取地形因子符合地貌发育的基本规律,提取的地形因子能客观的反应地表真实形态; ③ 采用非监督分类法能够有效的实现1:10万比例尺下地貌基本形态的定量化、自动化分类。

关键词: 地貌类型, ASTER GDEM, 空间分析, 自动划分

Abstract:

Geomorphology is one of the most important parts which constitute the elements of physical geography. Based on the GDEM of 1:100000 ASTER, the optimum analysis window was verified and topographic factors were extracted in the unit of drainage area. With GIS spatial analysis and unsupervised classification, the general geomorphologic types in Karst Region were auto-classified. The study results indicate: (1) DEM at the scale of 1:100000 can fill the requirements to express the configuration of earth surface on meso-scale. (2) It confirms the basic regulation to select the analysis window and extract topographic factors taking the drainage area as a unit. Topographic factors extracted can reflect the actual configuration of earth surface more impersonally. (3) Multi-spectral image is combined with topographic factors. With the method of ISODATA unsupervised classification, it can implement the quantification of the general geomorphologic types and automatic classification effectively on meso-scale. The precision of the data extracted can meet the demands of computer automatic classification. These experimental results improve the application of ISODATA unsupervised classification in the automatic classification of geomorphology.

Key words: geomorphic type, ASTER GDEM, spatial analysis, auto-classification

中图分类号: 

  • P931/TP75