Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts

Glacier calving fronts are highly dynamic environments that are becoming ubiquitous as glaciers recede and, in many cases, develop proglacial lakes. Monitoring of calving fronts is necessary to fully quantify the glacier ablation budget and to warn nearby communities of the threat of hazards, such a...

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Main Authors: Taylor, LS, Quincey, DJ, Smith, MW
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2023
Subjects:
Online Access:https://eprints.whiterose.ac.uk/195718/
https://eprints.whiterose.ac.uk/195718/6/nhess-23-329-2023.pdf
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spelling ftleedsuniv:oai:eprints.whiterose.ac.uk:195718 2023-05-15T16:21:42+02:00 Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts Taylor, LS Quincey, DJ Smith, MW 2023-01-27 text https://eprints.whiterose.ac.uk/195718/ https://eprints.whiterose.ac.uk/195718/6/nhess-23-329-2023.pdf en eng Copernicus Publications https://eprints.whiterose.ac.uk/195718/6/nhess-23-329-2023.pdf Taylor, LS orcid.org/0000-0001-7916-0856 , Quincey, DJ and Smith, MW orcid.org/0000-0003-4361-9527 (2023) Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts. Natural Hazards and Earth System Sciences, 23 (1). pp. 329-341. ISSN 1561-8633 cc_by_4 CC-BY Article NonPeerReviewed 2023 ftleedsuniv 2023-02-02T23:16:46Z Glacier calving fronts are highly dynamic environments that are becoming ubiquitous as glaciers recede and, in many cases, develop proglacial lakes. Monitoring of calving fronts is necessary to fully quantify the glacier ablation budget and to warn nearby communities of the threat of hazards, such as glacial lake outburst floods (GLOFs), tsunami waves, and iceberg collapses. Time-lapse camera arrays, with structure-from-motion photogrammetry, can produce regular 3D models of glaciers to monitor changes in the ice but are seldom incorporated into monitoring systems owing to the high cost of equipment. In this proof-of-concept study at Fjallsjökull, Iceland, we present and test a low-cost, highly adaptable camera system based on Raspberry Pi computers and compare the resulting point cloud data to a reference cloud generated using an unoccupied aerial vehicle (UAV). The mean absolute difference between the Raspberry Pi and UAV point clouds is found to be 0.301 m with a standard deviation of 0.738 m. We find that high-resolution point clouds can be robustly generated from cameras positioned up to 1.5 km from the glacier (mean absolute difference 0.341 m, standard deviation 0.742 m). Combined, these experiments suggest that for monitoring calving events in glaciers, Raspberry Pi cameras are an affordable, flexible, and practical option for future scientific research. Owing to the connectivity capabilities of Raspberry Pi computers, this opens the possibility for real-time structure-from-motion reconstructions of glacier calving fronts for deployment as an early warning system to calving-triggered GLOFs. Article in Journal/Newspaper glacier Iceland White Rose Research Online (Universities of Leeds, Sheffield & York) Glacial Lake ENVELOPE(-129.463,-129.463,58.259,58.259) Resolution Point ENVELOPE(-27.117,-27.117,-59.433,-59.433)
institution Open Polar
collection White Rose Research Online (Universities of Leeds, Sheffield & York)
op_collection_id ftleedsuniv
language English
description Glacier calving fronts are highly dynamic environments that are becoming ubiquitous as glaciers recede and, in many cases, develop proglacial lakes. Monitoring of calving fronts is necessary to fully quantify the glacier ablation budget and to warn nearby communities of the threat of hazards, such as glacial lake outburst floods (GLOFs), tsunami waves, and iceberg collapses. Time-lapse camera arrays, with structure-from-motion photogrammetry, can produce regular 3D models of glaciers to monitor changes in the ice but are seldom incorporated into monitoring systems owing to the high cost of equipment. In this proof-of-concept study at Fjallsjökull, Iceland, we present and test a low-cost, highly adaptable camera system based on Raspberry Pi computers and compare the resulting point cloud data to a reference cloud generated using an unoccupied aerial vehicle (UAV). The mean absolute difference between the Raspberry Pi and UAV point clouds is found to be 0.301 m with a standard deviation of 0.738 m. We find that high-resolution point clouds can be robustly generated from cameras positioned up to 1.5 km from the glacier (mean absolute difference 0.341 m, standard deviation 0.742 m). Combined, these experiments suggest that for monitoring calving events in glaciers, Raspberry Pi cameras are an affordable, flexible, and practical option for future scientific research. Owing to the connectivity capabilities of Raspberry Pi computers, this opens the possibility for real-time structure-from-motion reconstructions of glacier calving fronts for deployment as an early warning system to calving-triggered GLOFs.
format Article in Journal/Newspaper
author Taylor, LS
Quincey, DJ
Smith, MW
spellingShingle Taylor, LS
Quincey, DJ
Smith, MW
Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts
author_facet Taylor, LS
Quincey, DJ
Smith, MW
author_sort Taylor, LS
title Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts
title_short Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts
title_full Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts
title_fullStr Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts
title_full_unstemmed Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts
title_sort evaluation of low-cost raspberry pi sensors for structure-from-motion reconstructions of glacier calving fronts
publisher Copernicus Publications
publishDate 2023
url https://eprints.whiterose.ac.uk/195718/
https://eprints.whiterose.ac.uk/195718/6/nhess-23-329-2023.pdf
long_lat ENVELOPE(-129.463,-129.463,58.259,58.259)
ENVELOPE(-27.117,-27.117,-59.433,-59.433)
geographic Glacial Lake
Resolution Point
geographic_facet Glacial Lake
Resolution Point
genre glacier
Iceland
genre_facet glacier
Iceland
op_relation https://eprints.whiterose.ac.uk/195718/6/nhess-23-329-2023.pdf
Taylor, LS orcid.org/0000-0001-7916-0856 , Quincey, DJ and Smith, MW orcid.org/0000-0003-4361-9527 (2023) Evaluation of low-cost Raspberry Pi sensors for structure-from-motion reconstructions of glacier calving fronts. Natural Hazards and Earth System Sciences, 23 (1). pp. 329-341. ISSN 1561-8633
op_rights cc_by_4
op_rightsnorm CC-BY
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