Detection and Delineation of Sorted Stone Circles in Antarctica
Sorted stone circles are natural surface patterns formed in periglacial environments. Their relation to permafrost conditions make them very helpful for better understanding the past climates where they were formed and have evolved and also for monitoring current underlying processes in case circles...
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ftdoajarticles:oai:doaj.org/article:438c9cab72da4ca69014f1dbe6018d7b 2023-05-15T13:53:03+02:00 Detection and Delineation of Sorted Stone Circles in Antarctica Francisco Pereira Jorge S. Marques Sandra Heleno Pedro Pina 2020-01-01T00:00:00Z https://doi.org/10.3390/rs12010160 https://doaj.org/article/438c9cab72da4ca69014f1dbe6018d7b EN eng MDPI AG https://www.mdpi.com/2072-4292/12/1/160 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs12010160 https://doaj.org/article/438c9cab72da4ca69014f1dbe6018d7b Remote Sensing, Vol 12, Iss 1, p 160 (2020) patterned ground permafrost uav dem template matching sliding band filter dynamic programming barton peninsula antarctica Science Q article 2020 ftdoajarticles https://doi.org/10.3390/rs12010160 2022-12-31T16:34:52Z Sorted stone circles are natural surface patterns formed in periglacial environments. Their relation to permafrost conditions make them very helpful for better understanding the past climates where they were formed and have evolved and also for monitoring current underlying processes in case circles are active. These metric scale patterns that occur in clusters of tens to thousands of circular elements, can be more comprehensively characterized if automated methods are used. This paper addresses their identification and delineation through the development and testing of a set of automated approaches, namely, template matching, sliding band filter, and dynamic programming. All of these methods take advantage of the 3D shape of the structures conveyed by digital elevation models (DEM), built from ultra-high resolution imagery captured by unmanned aerial vehicles (UAV) surveys developed in Barton Peninsula, King George Island, Antarctica (62°S). The best detection results achieve scores above 85%, while the delineations are performed with errors as low as 7%. Article in Journal/Newspaper Antarc* Antarctica King George Island permafrost Directory of Open Access Journals: DOAJ Articles King George Island Barton ENVELOPE(-58.733,-58.733,-62.233,-62.233) Barton Peninsula ENVELOPE(-58.741,-58.741,-62.227,-62.227) Remote Sensing 12 1 160 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
patterned ground permafrost uav dem template matching sliding band filter dynamic programming barton peninsula antarctica Science Q |
spellingShingle |
patterned ground permafrost uav dem template matching sliding band filter dynamic programming barton peninsula antarctica Science Q Francisco Pereira Jorge S. Marques Sandra Heleno Pedro Pina Detection and Delineation of Sorted Stone Circles in Antarctica |
topic_facet |
patterned ground permafrost uav dem template matching sliding band filter dynamic programming barton peninsula antarctica Science Q |
description |
Sorted stone circles are natural surface patterns formed in periglacial environments. Their relation to permafrost conditions make them very helpful for better understanding the past climates where they were formed and have evolved and also for monitoring current underlying processes in case circles are active. These metric scale patterns that occur in clusters of tens to thousands of circular elements, can be more comprehensively characterized if automated methods are used. This paper addresses their identification and delineation through the development and testing of a set of automated approaches, namely, template matching, sliding band filter, and dynamic programming. All of these methods take advantage of the 3D shape of the structures conveyed by digital elevation models (DEM), built from ultra-high resolution imagery captured by unmanned aerial vehicles (UAV) surveys developed in Barton Peninsula, King George Island, Antarctica (62°S). The best detection results achieve scores above 85%, while the delineations are performed with errors as low as 7%. |
format |
Article in Journal/Newspaper |
author |
Francisco Pereira Jorge S. Marques Sandra Heleno Pedro Pina |
author_facet |
Francisco Pereira Jorge S. Marques Sandra Heleno Pedro Pina |
author_sort |
Francisco Pereira |
title |
Detection and Delineation of Sorted Stone Circles in Antarctica |
title_short |
Detection and Delineation of Sorted Stone Circles in Antarctica |
title_full |
Detection and Delineation of Sorted Stone Circles in Antarctica |
title_fullStr |
Detection and Delineation of Sorted Stone Circles in Antarctica |
title_full_unstemmed |
Detection and Delineation of Sorted Stone Circles in Antarctica |
title_sort |
detection and delineation of sorted stone circles in antarctica |
publisher |
MDPI AG |
publishDate |
2020 |
url |
https://doi.org/10.3390/rs12010160 https://doaj.org/article/438c9cab72da4ca69014f1dbe6018d7b |
long_lat |
ENVELOPE(-58.733,-58.733,-62.233,-62.233) ENVELOPE(-58.741,-58.741,-62.227,-62.227) |
geographic |
King George Island Barton Barton Peninsula |
geographic_facet |
King George Island Barton Barton Peninsula |
genre |
Antarc* Antarctica King George Island permafrost |
genre_facet |
Antarc* Antarctica King George Island permafrost |
op_source |
Remote Sensing, Vol 12, Iss 1, p 160 (2020) |
op_relation |
https://www.mdpi.com/2072-4292/12/1/160 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs12010160 https://doaj.org/article/438c9cab72da4ca69014f1dbe6018d7b |
op_doi |
https://doi.org/10.3390/rs12010160 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
1 |
container_start_page |
160 |
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1766257999291088896 |