Computing uncertainty of physiographic features extracted from multiscale digital elevation models

Hani, A.F.M. and Sathyamoorthy, D. and Asirvadam, V.S. (2014) Computing uncertainty of physiographic features extracted from multiscale digital elevation models. Computers and Geosciences, 64. pp. 15-23. ISSN 00983004

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

In this paper, it is proposed that the mapping of uncertainties of the three predominant physiographic features of terrains, which are mountain, basins and piedmont slopes, using variation in the spatial resolution over which these landforms are defined, can be performed with fuzzy classification. The proposed methodology allows for the generation of fuzzy certainty maps which assign high levels of uncertainty to regions with high levels of change across scales. This paper demonstrates that fuzzy certainty maps provide a better quantification of landform character than Boolean landform maps alone. In terms of sensitivity to noise, the methodology is able to identify narrow bridges, and spurious landforms, and assign these errors with low certainty values. However, it is unable to identify spurious modifications to landform shape, with these errors being assigned high certainty values. Ground truth maps are required to identify these errors. © 2013 Elsevier Ltd.

Item Type: Article
Additional Information: cited By 3
Uncontrolled Keywords: Change classes; Digital elevation model; Fuzzy classification; Ground truth; Lifting schemes; Physiographic features; Spatial resolution, Entropy; Errors; Geomorphology, Landforms, computer simulation; digital elevation model; entropy; fuzzy mathematics; numerical model; uncertainty analysis
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 16:16
Last Modified: 09 Nov 2023 16:16
URI: https://khub.utp.edu.my/scholars/id/eprint/4378

Actions (login required)

View Item
View Item