|Table of Contents|

Fractal Dimension Features from Catchment BoundaryProfile(CBP)of Small Watersheds in the NorthernShaanxi Province of China(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2019年04期
Page:
131-144
Research Field:
·地理学·
Publishing date:

Info

Title:
Fractal Dimension Features from Catchment BoundaryProfile(CBP)of Small Watersheds in the NorthernShaanxi Province of China
Author(s):
Kamila Kabo-bah1; 2; 3; Tang Guoan1; 4; Yang Xin1; 5; Na Jiaming4; Xiong Liyang5
(1.School of Geography,Nanjing Normal University,Nanjing 210023,China)(2.School of Geosciences,University of Energy and Natural Resources,Sunyani 214,Ghana)(3.Earth Observation Research and Innovation Centre(EORIC),University of Energy and Natural Resou
Keywords:
box counting; Higuchi; Hurst; digital elevation model(DEM); fractal dimension
PACS:
P208
DOI:
10.3969/j.issn.1001-4616.2019.04.019
Abstract:
The Loess Plateau of the Northern Shaanxi Province continues to be an important geomorphological research zone as a result of its history and geology evolution. This paper assessed the fractal properties of Catchment Boundary Profiles(CBP)generated from a 30 m ASTER Digital Elevation Model(DEM)for the study area. Three fractal models were applied:Box Counting,Higuchi and Hurst. The methods showed slight variation of fractal dimension’s(FD)estimates for each CBP,with close estimates between the Box Counting and Higuchi models. The Box counting method was the most consistent and accurate while the Higuchi overestimated in some cases. The FD results shows close similarity with CBP complexity and harmonic behaviour,revealing the fractals sensitivity to changes in geomorphological characteristics irrespective of the size of the object under investigation. The results also closely relate to previous works landform classification and dynamic analysis using other methods. The findings from this research would provide vital information for future land use planning purposes in the region and complement other research interested in the application of fractals for modelling on climate related studies.

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Last Update: 2019-12-31