REMOTE SENSING OF HIGH LATITUDE RIVERS: APPROACHES, INSIGHTS, AND FUTURE RAMIFICATIONS
High latitude rivers across the pan-Arctic domain are changing due to changes in climate and positive Arctic feedback loops. Understanding and contextualizing these changes is challenging due to a lack of data and methods for estimating and modeling river discharge, and mapping rivers. Remote sensin...
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ftunivmassamh:oai:scholarworks.umass.edu:dissertations_2-3572 2024-04-28T08:09:01+00:00 REMOTE SENSING OF HIGH LATITUDE RIVERS: APPROACHES, INSIGHTS, AND FUTURE RAMIFICATIONS Harlan, Merritt E 2022-06-16T17:00:38Z application/pdf https://scholarworks.umass.edu/dissertations_2/2542 https://doi.org/10.7275/28300904 https://scholarworks.umass.edu/context/dissertations_2/article/3572/viewcontent/Harlan_Dissertation_Revised.pdf unknown ScholarWorks@UMass Amherst https://scholarworks.umass.edu/dissertations_2/2542 doi:10.7275/28300904 https://scholarworks.umass.edu/context/dissertations_2/article/3572/viewcontent/Harlan_Dissertation_Revised.pdf http://creativecommons.org/licenses/by/4.0/ Doctoral Dissertations high latitude river discharge remote sensing satellite imagery hydrologic models deep learning Civil and Environmental Engineering Hydrology text 2022 ftunivmassamh https://doi.org/10.7275/28300904 2024-04-03T14:49:41Z High latitude rivers across the pan-Arctic domain are changing due to changes in climate and positive Arctic feedback loops. Understanding and contextualizing these changes is challenging due to a lack of data and methods for estimating and modeling river discharge, and mapping rivers. Remote sensing, and the availability of satellite imagery can provide ways to overcome these challenges. Through combining various forms of fieldwork, modeling, deep learning, and remote sensing, we contribute methodologies and knowledge to three key challenges associated with better understanding high latitude rivers. In the first chapter, we combine field data that can be rapidly deployed with remote sensing discharge algorithms to estimate river discharge in a field setting that has the potential to outperform traditional discharge estimation techniques. In the second chapter, we combine high resolution satellite imagery with a deep learning approach to map an important yet understudied type of small tundra stream, a beaded stream. The third chapter combines remotely sensed discharge estimates with gauge data to improve hydrologic model calibration. The outcomes of this work contribute important advancements towards improving our understanding of high latitude rivers. Text Arctic Tundra University of Massachusetts: ScholarWorks@UMass Amherst |
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Open Polar |
collection |
University of Massachusetts: ScholarWorks@UMass Amherst |
op_collection_id |
ftunivmassamh |
language |
unknown |
topic |
high latitude river discharge remote sensing satellite imagery hydrologic models deep learning Civil and Environmental Engineering Hydrology |
spellingShingle |
high latitude river discharge remote sensing satellite imagery hydrologic models deep learning Civil and Environmental Engineering Hydrology Harlan, Merritt E REMOTE SENSING OF HIGH LATITUDE RIVERS: APPROACHES, INSIGHTS, AND FUTURE RAMIFICATIONS |
topic_facet |
high latitude river discharge remote sensing satellite imagery hydrologic models deep learning Civil and Environmental Engineering Hydrology |
description |
High latitude rivers across the pan-Arctic domain are changing due to changes in climate and positive Arctic feedback loops. Understanding and contextualizing these changes is challenging due to a lack of data and methods for estimating and modeling river discharge, and mapping rivers. Remote sensing, and the availability of satellite imagery can provide ways to overcome these challenges. Through combining various forms of fieldwork, modeling, deep learning, and remote sensing, we contribute methodologies and knowledge to three key challenges associated with better understanding high latitude rivers. In the first chapter, we combine field data that can be rapidly deployed with remote sensing discharge algorithms to estimate river discharge in a field setting that has the potential to outperform traditional discharge estimation techniques. In the second chapter, we combine high resolution satellite imagery with a deep learning approach to map an important yet understudied type of small tundra stream, a beaded stream. The third chapter combines remotely sensed discharge estimates with gauge data to improve hydrologic model calibration. The outcomes of this work contribute important advancements towards improving our understanding of high latitude rivers. |
format |
Text |
author |
Harlan, Merritt E |
author_facet |
Harlan, Merritt E |
author_sort |
Harlan, Merritt E |
title |
REMOTE SENSING OF HIGH LATITUDE RIVERS: APPROACHES, INSIGHTS, AND FUTURE RAMIFICATIONS |
title_short |
REMOTE SENSING OF HIGH LATITUDE RIVERS: APPROACHES, INSIGHTS, AND FUTURE RAMIFICATIONS |
title_full |
REMOTE SENSING OF HIGH LATITUDE RIVERS: APPROACHES, INSIGHTS, AND FUTURE RAMIFICATIONS |
title_fullStr |
REMOTE SENSING OF HIGH LATITUDE RIVERS: APPROACHES, INSIGHTS, AND FUTURE RAMIFICATIONS |
title_full_unstemmed |
REMOTE SENSING OF HIGH LATITUDE RIVERS: APPROACHES, INSIGHTS, AND FUTURE RAMIFICATIONS |
title_sort |
remote sensing of high latitude rivers: approaches, insights, and future ramifications |
publisher |
ScholarWorks@UMass Amherst |
publishDate |
2022 |
url |
https://scholarworks.umass.edu/dissertations_2/2542 https://doi.org/10.7275/28300904 https://scholarworks.umass.edu/context/dissertations_2/article/3572/viewcontent/Harlan_Dissertation_Revised.pdf |
genre |
Arctic Tundra |
genre_facet |
Arctic Tundra |
op_source |
Doctoral Dissertations |
op_relation |
https://scholarworks.umass.edu/dissertations_2/2542 doi:10.7275/28300904 https://scholarworks.umass.edu/context/dissertations_2/article/3572/viewcontent/Harlan_Dissertation_Revised.pdf |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.7275/28300904 |
_version_ |
1797577516194463744 |