Slope Classification Systems and Their Slope Spectrum in Hill and Gully Area of the Loess Plateau

ZHAO Mudan; TANG Guoan; CHEN Zhengjiang; ZHU Hongchun

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Slope Classification Systems and Their Slope Spectrum in Hill and Gully Area of the Loess Plateau

- Slope Classification Systems and Their Slope Spectrum in Hill and Gully Area of the Loess Plateau
- Bulletin of Soiland Water Conservation Vol. 21, Issue 4, Pages: 33-36(2002)
- 作者机构：
  
  1. 西北大学城市与资源学系,西安市,710069
  2. 中国科学院水土保持研究所, 陕西杨凌,712100
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2002
- 稿件说明：
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ZHAO Mudan, TANG Guoan, CHEN Zhengjiang, et al. Slope Classification Systems and Their Slope Spectrum in Hill and Gully Area of the Loess Plateau[J]. Bulletin of Soiland Water Conservation, 2002, 21(4): 33-36.
DOI：

ZHAO Mudan, TANG Guoan, CHEN Zhengjiang, et al. Slope Classification Systems and Their Slope Spectrum in Hill and Gully Area of the Loess Plateau[J]. Bulletin of Soiland Water Conservation, 2002, 21(4): 33-36. DOI：

摘要

地面坡度是最重要的地形定量指标

建立科学合理的地面坡度分级体系是对坡度进行科学研究与坡度图制图必不可少的重要环节。总结了近年来在坡度分级研究方面的已有成果

将坡度分级方法归并为临界坡度分级、等差坡度分级、模糊坡度分级 3种方法。在说明了各种分类方法特点的基础上

探讨了其应用的适用性。以黄土丘陵沟壑区的韭园沟流域为实验样区

利用高精度 1∶ 1万比例尺的 DEM数据为信息源

建立了栅格数字坡度模型。利用分级统计的结果

对各种坡度分类方法所得到的地面坡谱进行了对比和分析

Abstract

Slope is the most important topographic variables. It is a critical work to establish a scientific and reasonable slope classification systems for terrain research and slope mapping. After a comprehensive summary to the previous works in this field

it is pointed out that slope classification scheme could be divided into three different types on the basis of their serving purpose

namely critical classification

equal interval classification and fuzzy classification. Their availability is analyzed after explaining the characteristics of the slope classifications. Taking Jiuyuangou area as the test area representing the loess hill gully terrain type

a digital slope model (DSM) was extracted from 1∶10 000 scaled DEMs. Different slope spectrums can be derived from DSMs according to the different slope classification systems

which shows a interesting discrepancy both in their distribution patterns and statistic values.

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references

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