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Glacial geomorphological mapping : A review of approaches and frameworks for best practice

Chandler, Benjamin M.P. ; Lovell, Harold ; Boston, Clare M. ; Lukas, Sven LU ; Barr, Iestyn D. ; Benediktsson, Ívar Örn LU ; Benn, Douglas I. ; Clark, Chris D. ; Darvill, Christopher M. and Evans, David J.A. , et al. (2018) In Earth-Science Reviews 185. p.806-846
Abstract

Geomorphological mapping is a well-established method for examining earth surface processes and landscape evolution in a range of environmental contexts. In glacial research, it provides crucial data for a wide range of process-oriented studies and palaeoglaciological reconstructions; in the latter case providing an essential geomorphological framework for establishing glacial chronologies. In recent decades, there have been significant developments in remote sensing and Geographical Information Systems (GIS), with a plethora of high-quality remotely-sensed datasets now (often freely) available. Most recently, the emergence of unmanned aerial vehicle (UAV) technology has allowed sub-decimetre scale aerial images and Digital Elevation... (More)

Geomorphological mapping is a well-established method for examining earth surface processes and landscape evolution in a range of environmental contexts. In glacial research, it provides crucial data for a wide range of process-oriented studies and palaeoglaciological reconstructions; in the latter case providing an essential geomorphological framework for establishing glacial chronologies. In recent decades, there have been significant developments in remote sensing and Geographical Information Systems (GIS), with a plethora of high-quality remotely-sensed datasets now (often freely) available. Most recently, the emergence of unmanned aerial vehicle (UAV) technology has allowed sub-decimetre scale aerial images and Digital Elevation Models (DEMs) to be obtained. Traditional field mapping methods still have an important role in glacial geomorphology, particularly in cirque glacier, valley glacier and icefield/ice-cap outlet settings. Field mapping is also used in ice sheet settings, but often takes the form of necessarily highly-selective ground-truthing of remote mapping. Given the increasing abundance of datasets and methods available for mapping, effective approaches are necessary to enable assimilation of data and ensure robustness. This paper provides a review and assessment of the various glacial geomorphological methods and datasets currently available, with a focus on their applicability in particular glacial settings. We distinguish two overarching ‘work streams’ that recognise the different approaches typically used in mapping landforms produced by ice masses of different sizes: (i) mapping of ice sheet geomorphological imprints using a combined remote sensing approach, with some field checking (where feasible); and (ii) mapping of alpine and plateau-style ice mass (cirque glacier, valley glacier, icefield and ice-cap) geomorphological imprints using remote sensing and considerable field mapping. Key challenges to accurate and robust geomorphological mapping are highlighted, often necessitating compromises and pragmatic solutions. The importance of combining multiple datasets and/or mapping approaches is emphasised, akin to multi-proxy approaches used in many Earth Science disciplines. Based on our review, we provide idealised frameworks and general recommendations to ensure best practice in future studies and aid in accuracy assessment, comparison, and integration of geomorphological data. These will be of particular value where geomorphological data are incorporated in large compilations and subsequently used for palaeoglaciological reconstructions. Finally, we stress that robust interpretations of glacial landforms and landscapes invariably requires additional chronological and/or sedimentological evidence, and that such data should ideally be collected as part of a holistic assessment of the overall glacier system.

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publication status
published
subject
keywords
Field mapping, Geomorphological mapping, GIS, Glacial geomorphology, Remote sensing
in
Earth-Science Reviews
volume
185
pages
41 pages
publisher
Elsevier
external identifiers
  • scopus:85051365154
ISSN
0012-8252
DOI
10.1016/j.earscirev.2018.07.015
language
English
LU publication?
yes
id
0c36a6b8-78b9-4d02-85c2-854ea76cdb5e
date added to LUP
2018-09-06 12:20:00
date last changed
2022-04-17 22:08:47
@article{0c36a6b8-78b9-4d02-85c2-854ea76cdb5e,
  abstract     = {{<p>Geomorphological mapping is a well-established method for examining earth surface processes and landscape evolution in a range of environmental contexts. In glacial research, it provides crucial data for a wide range of process-oriented studies and palaeoglaciological reconstructions; in the latter case providing an essential geomorphological framework for establishing glacial chronologies. In recent decades, there have been significant developments in remote sensing and Geographical Information Systems (GIS), with a plethora of high-quality remotely-sensed datasets now (often freely) available. Most recently, the emergence of unmanned aerial vehicle (UAV) technology has allowed sub-decimetre scale aerial images and Digital Elevation Models (DEMs) to be obtained. Traditional field mapping methods still have an important role in glacial geomorphology, particularly in cirque glacier, valley glacier and icefield/ice-cap outlet settings. Field mapping is also used in ice sheet settings, but often takes the form of necessarily highly-selective ground-truthing of remote mapping. Given the increasing abundance of datasets and methods available for mapping, effective approaches are necessary to enable assimilation of data and ensure robustness. This paper provides a review and assessment of the various glacial geomorphological methods and datasets currently available, with a focus on their applicability in particular glacial settings. We distinguish two overarching ‘work streams’ that recognise the different approaches typically used in mapping landforms produced by ice masses of different sizes: (i) mapping of ice sheet geomorphological imprints using a combined remote sensing approach, with some field checking (where feasible); and (ii) mapping of alpine and plateau-style ice mass (cirque glacier, valley glacier, icefield and ice-cap) geomorphological imprints using remote sensing and considerable field mapping. Key challenges to accurate and robust geomorphological mapping are highlighted, often necessitating compromises and pragmatic solutions. The importance of combining multiple datasets and/or mapping approaches is emphasised, akin to multi-proxy approaches used in many Earth Science disciplines. Based on our review, we provide idealised frameworks and general recommendations to ensure best practice in future studies and aid in accuracy assessment, comparison, and integration of geomorphological data. These will be of particular value where geomorphological data are incorporated in large compilations and subsequently used for palaeoglaciological reconstructions. Finally, we stress that robust interpretations of glacial landforms and landscapes invariably requires additional chronological and/or sedimentological evidence, and that such data should ideally be collected as part of a holistic assessment of the overall glacier system.</p>}},
  author       = {{Chandler, Benjamin M.P. and Lovell, Harold and Boston, Clare M. and Lukas, Sven and Barr, Iestyn D. and Benediktsson, Ívar Örn and Benn, Douglas I. and Clark, Chris D. and Darvill, Christopher M. and Evans, David J.A. and Ewertowski, Marek W. and Loibl, David and Margold, Martin and Otto, Jan Christoph and Roberts, David H. and Stokes, Chris R. and Storrar, Robert D. and Stroeven, Arjen P.}},
  issn         = {{0012-8252}},
  keywords     = {{Field mapping; Geomorphological mapping; GIS; Glacial geomorphology; Remote sensing}},
  language     = {{eng}},
  month        = {{10}},
  pages        = {{806--846}},
  publisher    = {{Elsevier}},
  series       = {{Earth-Science Reviews}},
  title        = {{Glacial geomorphological mapping : A review of approaches and frameworks for best practice}},
  url          = {{http://dx.doi.org/10.1016/j.earscirev.2018.07.015}},
  doi          = {{10.1016/j.earscirev.2018.07.015}},
  volume       = {{185}},
  year         = {{2018}},
}