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DC Field | Value | Language |
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dc.contributor.author | Park, Edward | en_US |
dc.contributor.author | Merino, Eder | en_US |
dc.contributor.author | Lewis, Quinn W. | en_US |
dc.contributor.author | Lindsey, Eric Ostrom | en_US |
dc.contributor.author | Yang, Xiankun | en_US |
dc.date.accessioned | 2021-01-21T06:23:21Z | - |
dc.date.available | 2021-01-21T06:23:21Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Park, E., Merino, E., Lewis, Q. W., Lindsey, E. O., & Yang, X. (2020). A pathway to the automated global assessment of water level in reservoirs with Synthetic Aperture Radar (SAR). Remote Sensing, 12(8), 1353-. doi:10.3390/rs12081353 | en_US |
dc.identifier.issn | 2072-4292 | en_US |
dc.identifier.uri | https://hdl.handle.net/10356/146024 | - |
dc.description.abstract | Global measurements of reservoir water levels are crucial for understanding Earth’s hydrological dynamics, especially in the context of global industrialization and climate change. Although radar altimetry has been used to measure the water level of some reservoirs with high accuracy, it is not yet feasible unless the water body is sufficiently large or directly located at the satellite’s nadir. This study proposes a gauging method applicable to a wide range of reservoirs using Sentinel–1 Synthetic Aperture Radar data and a digital elevation model (DEM). The method is straightforward to implement and involves estimating the mean slope–corrected elevation of points along the reservoir shoreline. We test the model on six case studies and show that the estimated water levels are accurate to around 10% error on average of independently verified values. This study represents a substantial step toward the global gauging of lakes and reservoirs of all sizes and in any location where a DEM is available. | en_US |
dc.description.sponsorship | Nanyang Technological University | en_US |
dc.language.iso | en | en_US |
dc.relation | SUG–NAP (3/19 EP) | en_US |
dc.relation.ispartof | Remote Sensing | en_US |
dc.rights | © 2020 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | en_US |
dc.subject | Engineering::Environmental engineering | en_US |
dc.title | A pathway to the automated global assessment of water level in reservoirs with Synthetic Aperture Radar (SAR) | en_US |
dc.type | Journal Article | en |
dc.contributor.school | Asian School of the Environment | en_US |
dc.contributor.research | Earth Observatory of Singapore | en_US |
dc.identifier.doi | 10.3390/rs12081353 | - |
dc.description.version | Published version | en_US |
dc.identifier.issue | 8 | en_US |
dc.identifier.volume | 12 | en_US |
dc.subject.keywords | Reservoir | en_US |
dc.subject.keywords | Lakes | en_US |
dc.description.acknowledgement | The National Institute of Education (NIE) at Nanyang Technological University (NTU) Grant # SUG–NAP (3/19 EP) funded this research. | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | open | - |
Appears in Collections: | ASE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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remotesensing-12-01353.pdf | 4.3 MB | Adobe PDF | View/Open |
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