Comparing Discharge Estimates Made via the BAM Algorithm in High-Order Arctic Rivers Derived Solely From Optical CubeSat, Landsat, and Sentinel-2 Data ...
Conventional satellite platforms are limited in their ability to monitor rivers at fine spatial and temporal scales: suffering from unavoidable trade-offs between spatial and temporal resolutions. CubeSat constellations, however, can provide global data at high spatial and temporal resolutions, albe...
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ftdatacite:10.17615/w1nw-mk10 2024-03-31T07:50:44+00:00 Comparing Discharge Estimates Made via the BAM Algorithm in High-Order Arctic Rivers Derived Solely From Optical CubeSat, Landsat, and Sentinel-2 Data ... Gleason, C.J. Feng, D. Pavelsky, T.M. Yang, X. 2019 https://dx.doi.org/10.17615/w1nw-mk10 https://cdr.lib.unc.edu/concern/articles/d791ss095 en eng Blackwell Publishing Ltd In Copyright http://rightsstatements.org/vocab/InC/1.0/ Text article-journal Article ScholarlyArticle 2019 ftdatacite https://doi.org/10.17615/w1nw-mk10 2024-03-04T11:43:12Z Conventional satellite platforms are limited in their ability to monitor rivers at fine spatial and temporal scales: suffering from unavoidable trade-offs between spatial and temporal resolutions. CubeSat constellations, however, can provide global data at high spatial and temporal resolutions, albeit with reduced spectral information. This study provides a first assessment of using CubeSat data for river discharge estimation in both gauged and ungauged settings. Discharge was estimated for 11 Arctic rivers with sizes ranging from 16 to >1,000 m wide using the Bayesian at-many-stations hydraulic geometry-Manning algorithm (BAM). BAM-at-many-stations hydraulic geometry solves for hydraulic geometry parameters to estimate flow and requires only river widths as input. Widths were retrieved from Landsat 8 and Sentinel-2 data sets and a CubeSat (the Planet company) data set, as well as their fusions. Results show satellite data fusion improves discharge estimation for both large (>100 m wide) and medium ... Text Arctic DataCite Metadata Store (German National Library of Science and Technology) Arctic |
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DataCite Metadata Store (German National Library of Science and Technology) |
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English |
description |
Conventional satellite platforms are limited in their ability to monitor rivers at fine spatial and temporal scales: suffering from unavoidable trade-offs between spatial and temporal resolutions. CubeSat constellations, however, can provide global data at high spatial and temporal resolutions, albeit with reduced spectral information. This study provides a first assessment of using CubeSat data for river discharge estimation in both gauged and ungauged settings. Discharge was estimated for 11 Arctic rivers with sizes ranging from 16 to >1,000 m wide using the Bayesian at-many-stations hydraulic geometry-Manning algorithm (BAM). BAM-at-many-stations hydraulic geometry solves for hydraulic geometry parameters to estimate flow and requires only river widths as input. Widths were retrieved from Landsat 8 and Sentinel-2 data sets and a CubeSat (the Planet company) data set, as well as their fusions. Results show satellite data fusion improves discharge estimation for both large (>100 m wide) and medium ... |
format |
Text |
author |
Gleason, C.J. Feng, D. Pavelsky, T.M. Yang, X. |
spellingShingle |
Gleason, C.J. Feng, D. Pavelsky, T.M. Yang, X. Comparing Discharge Estimates Made via the BAM Algorithm in High-Order Arctic Rivers Derived Solely From Optical CubeSat, Landsat, and Sentinel-2 Data ... |
author_facet |
Gleason, C.J. Feng, D. Pavelsky, T.M. Yang, X. |
author_sort |
Gleason, C.J. |
title |
Comparing Discharge Estimates Made via the BAM Algorithm in High-Order Arctic Rivers Derived Solely From Optical CubeSat, Landsat, and Sentinel-2 Data ... |
title_short |
Comparing Discharge Estimates Made via the BAM Algorithm in High-Order Arctic Rivers Derived Solely From Optical CubeSat, Landsat, and Sentinel-2 Data ... |
title_full |
Comparing Discharge Estimates Made via the BAM Algorithm in High-Order Arctic Rivers Derived Solely From Optical CubeSat, Landsat, and Sentinel-2 Data ... |
title_fullStr |
Comparing Discharge Estimates Made via the BAM Algorithm in High-Order Arctic Rivers Derived Solely From Optical CubeSat, Landsat, and Sentinel-2 Data ... |
title_full_unstemmed |
Comparing Discharge Estimates Made via the BAM Algorithm in High-Order Arctic Rivers Derived Solely From Optical CubeSat, Landsat, and Sentinel-2 Data ... |
title_sort |
comparing discharge estimates made via the bam algorithm in high-order arctic rivers derived solely from optical cubesat, landsat, and sentinel-2 data ... |
publisher |
Blackwell Publishing Ltd |
publishDate |
2019 |
url |
https://dx.doi.org/10.17615/w1nw-mk10 https://cdr.lib.unc.edu/concern/articles/d791ss095 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_rights |
In Copyright http://rightsstatements.org/vocab/InC/1.0/ |
op_doi |
https://doi.org/10.17615/w1nw-mk10 |
_version_ |
1795029120973799424 |