An Analysis on Fractal Characeeristics of Typical Landform Patterns in Northern Shaanxi Loess Plateau Based on DEM

CAI Ling-yan; TANG Guo-an; XIONG Li-yang; Kamila Justyna Lis; XIE Ting; Li Ya-ping

doi:10.13961/j.cnki.stbctb.2014.03.027

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An Analysis on Fractal Characeeristics of Typical Landform Patterns in Northern Shaanxi Loess Plateau Based on DEM

- An Analysis on Fractal Characeeristics of Typical Landform Patterns in Northern Shaanxi Loess Plateau Based on DEM
- Bulletin of Soiland Water Conservation Vol. 33, Issue 3, Pages: 141-144(2014)
- 作者机构：
  
  南京师范大学地理科学学院,江苏,南京,210023
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2014.03.027
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- Published：2014
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CAI Ling-yan, TANG Guo-an, XIONG Li-yang, et al. An Analysis on Fractal Characeeristics of Typical Landform Patterns in Northern Shaanxi Loess Plateau Based on DEM[J]. Bulletin of Soiland Water Conservation, 2014, 33(3): 141-144.
DOI：

CAI Ling-yan, TANG Guo-an, XIONG Li-yang, et al. An Analysis on Fractal Characeeristics of Typical Landform Patterns in Northern Shaanxi Loess Plateau Based on DEM[J]. Bulletin of Soiland Water Conservation, 2014, 33(3): 141-144. DOI： 10.13961/j.cnki.stbctb.2014.03.027.

摘要

应用分形理论与方法

结合陕北黄土高原1:5万DEM数据

通过河网分形维数和稳定性系数计算

研究了陕北黄土地貌空间分布特征。结果表明: (1) 陕北黄土高原不同地貌类型分形结构复杂程度各异

表现出不同大小的水系分维值和稳定性系数

其中

黄土峁状、梁状丘陵沟壑区地貌结构最为复杂

分维值最大

稳定性系数最小。黄土残塬、黄土塬区分维值次之。黄土-风沙过渡区地形结构简单

地势相对平坦

分维值最低

稳定性程度最高。(2) 以分形参数作为定量化指标进行黄土地貌特征研究是可行的

DEM数据集是研究过程中的核心和基础。分形值所描述的分形特征与地貌类型、地质结构等有一定的相关性。此外

对分形几何的地学机理还需要进一步分析。

Abstract

Adapting the fractal analysis method and raster DEMs of 25 m×25 m

this paper probes into the spatial distribution of landform patterns in the loess landforms of Northern Shaanxi Province by calculating the fractal dimension and stability coefficient of stream-network. Experimental results show that: (1) The complexity of fractal structure differs with various types of loess landforms

embodied mainly in diverse fractal dimensions and stability coefficients. Among these

loess hill and ridge regions possess the highest fractal dimension and the lowest stability coefficient

reflecting its most complex geomorphological structure in the area; loess tableland and scattered loess tableland regions rank the second; and the transitional regions between loess and desert

with rather smooth and simple terrain

present the lowest fractal dimension and the highest stability coefficient. (2) It is proved that the fractal parameter based investigation on the geomorphic features of loess landforms is feasible

and DEM datasets can play a critical and fundamental role in the process. The outcomes derived from fractal dimension show a strong correlation to geomorphic type or geologic structure to some extent. Moreover

more attentions should be paid on its geographical mechanisms.

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