Detecting plume-driven polynyas from dual-pol SAR imagery
Antarctic ocean temperatures are rising due to climate change, causing land ice to melt at increasingly higher rates. Ice shelf bottom melt is a key factor responsible for Antarctic ice mass loss and as such understanding melt processes in the Antarctic is therefore key to more accurately predict ho...
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fttudelft:oai:tudelft.nl:uuid:3931c184-4236-4e49-8254-104bbc881b7e 2023-07-30T03:59:03+02:00 Detecting plume-driven polynyas from dual-pol SAR imagery Zitman, Jelle (author) Lhermitte, S.L.M. (mentor) Wouters, B. (mentor) Izeboud, M. (mentor) Delft University of Technology (degree granting institution) 2022-08-25 http://resolver.tudelft.nl/uuid:3931c184-4236-4e49-8254-104bbc881b7e en eng http://resolver.tudelft.nl/uuid:3931c184-4236-4e49-8254-104bbc881b7e © 2022 Jelle Zitman Classification Polynya SAR Basal Melt master thesis 2022 fttudelft 2023-07-08T20:45:38Z Antarctic ocean temperatures are rising due to climate change, causing land ice to melt at increasingly higher rates. Ice shelf bottom melt is a key factor responsible for Antarctic ice mass loss and as such understanding melt processes in the Antarctic is therefore key to more accurately predict how the global sea level will respond to climate change in the foreseeable future. Basal melt results in the formation of both basal melt channels underneath an ice shelf and persistent sea ice wakes (named plume-driven polynyas) at the ice shelf shoreline. The goal of this research is to develop a method that can help to automatically infer basal melt locations along the Antarctic shoreline with significantly increased spatio-temporal resolution compared to previously researched basal melt detection methods. We infer basal melt locations by detecting plume-driven polynyas. We used dual-pol (HH/HV) Sentinel-1 EW SAR data (40x40m resolution) in combination with GLCM textural features as input for a random forest classification that differentiates images as water or ice in four sub-classes: undisturbed ’open’ water, disturbed ’rough’ water, sea ice and (floating) land ice. We assessed what the advantages and limitations of this approach were for plume-driven polynya detection by performing water-ice (sub-class) classifications and examining which GLCM features proved most useful, what GLCM window size is preferred, and how classification can be aided by post-processing classified images. We computed GLCM textures for window sizes w = [5,11,21] and created a classifier for each choice (GLCM5, GLCM11 and GLC21) and compared results to a classifier based on original dual-pol SAR data (BASE). Via cross validated recursive feature elimination we determined that ’sum average’ (HH and HV polarization) and ’difference variance’ (HV polarization) were most useful for separation of water and ice classes (HH_savg, HV_savg and HV_dvar). Our results have shown that using GLCM texture based dual-pol classifiers improves water-ice ... Master Thesis Antarc* Antarctic Antarctic Ocean Ice Shelf Sea ice Delft University of Technology: Institutional Repository Antarctic The Antarctic Antarctic Ocean |
institution |
Open Polar |
collection |
Delft University of Technology: Institutional Repository |
op_collection_id |
fttudelft |
language |
English |
topic |
Classification Polynya SAR Basal Melt |
spellingShingle |
Classification Polynya SAR Basal Melt Zitman, Jelle (author) Detecting plume-driven polynyas from dual-pol SAR imagery |
topic_facet |
Classification Polynya SAR Basal Melt |
description |
Antarctic ocean temperatures are rising due to climate change, causing land ice to melt at increasingly higher rates. Ice shelf bottom melt is a key factor responsible for Antarctic ice mass loss and as such understanding melt processes in the Antarctic is therefore key to more accurately predict how the global sea level will respond to climate change in the foreseeable future. Basal melt results in the formation of both basal melt channels underneath an ice shelf and persistent sea ice wakes (named plume-driven polynyas) at the ice shelf shoreline. The goal of this research is to develop a method that can help to automatically infer basal melt locations along the Antarctic shoreline with significantly increased spatio-temporal resolution compared to previously researched basal melt detection methods. We infer basal melt locations by detecting plume-driven polynyas. We used dual-pol (HH/HV) Sentinel-1 EW SAR data (40x40m resolution) in combination with GLCM textural features as input for a random forest classification that differentiates images as water or ice in four sub-classes: undisturbed ’open’ water, disturbed ’rough’ water, sea ice and (floating) land ice. We assessed what the advantages and limitations of this approach were for plume-driven polynya detection by performing water-ice (sub-class) classifications and examining which GLCM features proved most useful, what GLCM window size is preferred, and how classification can be aided by post-processing classified images. We computed GLCM textures for window sizes w = [5,11,21] and created a classifier for each choice (GLCM5, GLCM11 and GLC21) and compared results to a classifier based on original dual-pol SAR data (BASE). Via cross validated recursive feature elimination we determined that ’sum average’ (HH and HV polarization) and ’difference variance’ (HV polarization) were most useful for separation of water and ice classes (HH_savg, HV_savg and HV_dvar). Our results have shown that using GLCM texture based dual-pol classifiers improves water-ice ... |
author2 |
Lhermitte, S.L.M. (mentor) Wouters, B. (mentor) Izeboud, M. (mentor) Delft University of Technology (degree granting institution) |
format |
Master Thesis |
author |
Zitman, Jelle (author) |
author_facet |
Zitman, Jelle (author) |
author_sort |
Zitman, Jelle (author) |
title |
Detecting plume-driven polynyas from dual-pol SAR imagery |
title_short |
Detecting plume-driven polynyas from dual-pol SAR imagery |
title_full |
Detecting plume-driven polynyas from dual-pol SAR imagery |
title_fullStr |
Detecting plume-driven polynyas from dual-pol SAR imagery |
title_full_unstemmed |
Detecting plume-driven polynyas from dual-pol SAR imagery |
title_sort |
detecting plume-driven polynyas from dual-pol sar imagery |
publishDate |
2022 |
url |
http://resolver.tudelft.nl/uuid:3931c184-4236-4e49-8254-104bbc881b7e |
geographic |
Antarctic The Antarctic Antarctic Ocean |
geographic_facet |
Antarctic The Antarctic Antarctic Ocean |
genre |
Antarc* Antarctic Antarctic Ocean Ice Shelf Sea ice |
genre_facet |
Antarc* Antarctic Antarctic Ocean Ice Shelf Sea ice |
op_relation |
http://resolver.tudelft.nl/uuid:3931c184-4236-4e49-8254-104bbc881b7e |
op_rights |
© 2022 Jelle Zitman |
_version_ |
1772809761372241920 |