Author:
Zahra Tuba,Paudel Uttam,Hayakawa Yuichi S.,Oguchi Takashi
Abstract
AbstractExtraction of knickpoints or knickzones from a Digital Elevation Model (DEM) has gained immense significance owing to the increasing implications of knickzones on landform development. However, existing methods for knickzone extraction tend to be subjective or require time-intensive data processing. This paper describes the proposed Knickzone Extraction Tool (KET), a new raster-based Python script deployed in the form of an ArcGIS toolset that automates the process of knickzone extraction and is both fast and more user-friendly. The KET is based on multi-scale analysis of slope gradients along a river course, where any locally steep segment (knickzone) can be extracted as an anomalously high local gradient. We also conducted a comparative analysis of the KET and other contemporary knickzone identification techniques. The relationship between knickzone distribution and its morphometric characteristics are also examined through a case study of a mountainous watershed in Japan.
Subject
General Earth and Planetary Sciences,Environmental Science (miscellaneous)
Cited by
18 articles.
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