ACME, a GIS tool for Automated Cirque Metric Extraction

Regional scale studies of glacial cirque metrics provide key insights on the (palaeo) environment related to the formation of these erosional landforms. The growing availability of high resolution terrain models means that more glacial cirques can be identified and mapped in the future. However, the...

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Bibliographic Details
Published inGeomorphology (Amsterdam, Netherlands) Vol. 278; pp. 280 - 286
Main Authors Spagnolo, Matteo, Pellitero, Ramon, Barr, Iestyn D., Ely, Jeremy C., Pellicer, Xavier M., Rea, Brice R.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.02.2017
Subjects
Automation
Extraction
Geomorphology
GIS
Glacial cirque
Glacial geomorphology
Hypsometry
Manuals
Metrics
Morphometry
Slopes
Terrain
GIS
Hypsometry
Metrics
Glacial cirque
Glacial geomorphology
Morphometry
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Summary:Regional scale studies of glacial cirque metrics provide key insights on the (palaeo) environment related to the formation of these erosional landforms. The growing availability of high resolution terrain models means that more glacial cirques can be identified and mapped in the future. However, the extraction of their metrics still largely relies on time consuming manual techniques or the combination of, more or less obsolete, GIS tools. In this paper, a newly coded toolbox is provided for the automated, and comparatively quick, extraction of 16 key glacial cirque metrics; including length, width, circularity, planar and 3D area, elevation, slope, aspect, plan closure and hypsometry. The set of tools, named ACME (Automated Cirque Metric Extraction), is coded in Python, runs in one of the most commonly used GIS packages (ArcGIS) and has a user friendly interface. A polygon layer of mapped cirques is required for all metrics, while a Digital Terrain Model and a point layer of cirque threshold midpoints are needed to run some of the tools. Results from ACME are comparable to those from other techniques and can be obtained rapidly, allowing large cirque datasets to be analysed and potentially important regional trends highlighted.
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ISSN:0169-555X
1872-695X
DOI:10.1016/j.geomorph.2016.11.018