A fuzzy c-means classification of elevation derivatives to extract the morphometric classification of landforms in Snowdonia, Wales
A fuzzy c-means classification of elevation derivatives to extract the morphometric classification of landforms in Snowdonia, Wales
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DOI：
10.1016/j.cageo.2007.05.005
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发表时间：
2007-10-01
影响因子：
4.4
通讯作者：
Bastin, L.
中科院分区：
文献类型：
--
作者：
Arrell, K. E.;Fisher, P. F.;Bastin, L.
高分辨率/大规模数字高程数据的全球覆盖范围不断扩大，使地貌形态的研究重新受到重视，为陆地表面的特征和量化提供了可访问的数据集。数字高程模型（DEM）提供了定量的高程数据，但它是从这些原始数据中表征和提取地貌上重要的措施（形态指标），形成更多信息和有用的数据集。与许多地理测量一样，从DEM中导出的形态测量依赖于观测尺度。本文报告的结果，采用模糊c-均值分类的样本DEM斯诺登尼亚。威尔士，在不同的分辨率作为输入的地形测量的数量，并在每个分辨率作为输出的地貌形态测量分类。分类表明，不同的景观成分或形态类是重要的，在不同的分辨率，形态类表现出分辨率的依赖性，在其地理范围。在不同分辨率的地貌形态分类的尺度依赖性和行为的检查提供了一个更全面和更全面的视图的类比一个单一的尺度分析。(C)2007爱思唯尔有限公司保留所有权利。
The increasing global coverage of high resolution/large-scale digital elevation data has allowed the study of geomorphological form to receive renewed attention by providing accessible datasets for the characterisation and quantification of land surfaces. Digital elevation models (DEMs) provide quantitative elevation data, but it is the characterisation and extraction of geomorphologically significant measures (morphometric indices) from these raw data that form more informative and useful datasets. Common to many geographical measures, morphometric measures derived from DEMs are dependent on the scale of observation. This paper reports results of employing a fuzzy c-means classification for a sample DEM from Snowdonia. Wales, with a number of morphometric measures at different resolutions as input, and morphometric classification of landforms at each resolution as output. The classifications reveal that different landscape components or morphometric classes are important at different resolutions, and that morphometric classes exhibit resolution dependency in their geographical extents. Examination of the scale dependency and behaviour of morphometric classifications of landforms at different resolutions provides a fuller and more holistic view of the classes present than a single-scale analysis. (C) 2007 Elsevier Ltd. All rights reserved.