RODEO: An algorithm and Google Earth Engine application for river discharge retrieval from Landsat
Satellite remote sensing of river discharge (RSQ) algorithms provide a useful source of observations to supplement river gauge records. RSQ algorithms have existed for over a decade yet their widespread use has been impeded by a lack of operational usability and quantitative characterization of unce...
Gespeichert in:
Veröffentlicht in: | Environmental modelling & software : with environment data news 2022-02, Vol.148, p.105254, Article 105254 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | 105254 |
container_title | Environmental modelling & software : with environment data news |
container_volume | 148 |
creator | Riggs, Ryan M. Allen, George H. David, Cédric H. Lin, Peirong Pan, Ming Yang, Xiao Gleason, Colin |
description | Satellite remote sensing of river discharge (RSQ) algorithms provide a useful source of observations to supplement river gauge records. RSQ algorithms have existed for over a decade yet their widespread use has been impeded by a lack of operational usability and quantitative characterization of uncertainty. Here we present RODEO, an algorithm for estimating river discharge using Landsat observations in near-real time. RODEO is validated with 456 gauges (median Kling-Gupta efficiency = 0.3) and uses a novel quantile rating curve technique that pairs Landsat river widths with discharge estimates from a global hydrologic model. RODEO also characterizes the uncertainty of RSQ estimates (estimated root-mean-square error = +7%), enabling RSQ retrievals to be used for data assimilation into hydrologic models. With the goal of expanding the RSQ user base, the RODEO algorithm is implemented as a freely available, off-the-shelf cloud-based Google Earth Engine application that provides RSQ estimates across North America from 1984-present.
•We present RODEO, a user-friendly application for estimating river discharge from Landsat 5, 7, and 8.•River widths can be quickly extracted from Landsat images and used to estimate discharge.•RODEO characterizes discharge uncertainty allowing for remote sensing measurements to be used for data assimilation. |
doi_str_mv | 10.1016/j.envsoft.2021.105254 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2638079783</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1364815221002966</els_id><sourcerecordid>2636752833</sourcerecordid><originalsourceid>FETCH-LOGICAL-c417t-ed46ae68099b6014fd9d320b05ec3864220497bebbca3e8cd660ef84e3b5f88d3</originalsourceid><addsrcrecordid>eNqFkE9rGzEQxZfSQtO0H6Eg6KWXdfVvtdpeSkjcJGAwhOQstNKsLbOW3JFsyLevjHPqpad5DL_3mHlN85XRBaNM_dgtIJ5ymsqCU87qruOdfNdcMd2LVvVcva9aKNlq1vGPzaecd5TSquVVMz6t75brn-QmEjtvEoay3RMbPblPaTMDWVosW7KMmxCB2MNhDs6WkCKZEhIMJ0DiQ3ZbixsgCAUDnOxMJkx7sqo52ZbPzYfJzhm-vM3r5uX38vn2oV2t7x9vb1atk6wvLXipLChNh2FUlMnJD15wOtIOnNBKck7l0I8wjs4K0M4rRWHSEsTYTVp7cd18v-QeMP05Qi5mXy-DebYR0jEbroTqO66FqOi3f9BdOmKs150pTfuh12equ1AOU84Ikzlg2Ft8NYyac_NmZ96aN-fmzaX56vt18UH99hQATXYBogMfEFwxPoX_JPwF-oaOyQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2638079783</pqid></control><display><type>article</type><title>RODEO: An algorithm and Google Earth Engine application for river discharge retrieval from Landsat</title><source>Elsevier ScienceDirect Journals</source><creator>Riggs, Ryan M. ; Allen, George H. ; David, Cédric H. ; Lin, Peirong ; Pan, Ming ; Yang, Xiao ; Gleason, Colin</creator><creatorcontrib>Riggs, Ryan M. ; Allen, George H. ; David, Cédric H. ; Lin, Peirong ; Pan, Ming ; Yang, Xiao ; Gleason, Colin</creatorcontrib><description>Satellite remote sensing of river discharge (RSQ) algorithms provide a useful source of observations to supplement river gauge records. RSQ algorithms have existed for over a decade yet their widespread use has been impeded by a lack of operational usability and quantitative characterization of uncertainty. Here we present RODEO, an algorithm for estimating river discharge using Landsat observations in near-real time. RODEO is validated with 456 gauges (median Kling-Gupta efficiency = 0.3) and uses a novel quantile rating curve technique that pairs Landsat river widths with discharge estimates from a global hydrologic model. RODEO also characterizes the uncertainty of RSQ estimates (estimated root-mean-square error = +7%), enabling RSQ retrievals to be used for data assimilation into hydrologic models. With the goal of expanding the RSQ user base, the RODEO algorithm is implemented as a freely available, off-the-shelf cloud-based Google Earth Engine application that provides RSQ estimates across North America from 1984-present.
•We present RODEO, a user-friendly application for estimating river discharge from Landsat 5, 7, and 8.•River widths can be quickly extracted from Landsat images and used to estimate discharge.•RODEO characterizes discharge uncertainty allowing for remote sensing measurements to be used for data assimilation.</description><identifier>ISSN: 1364-8152</identifier><identifier>EISSN: 1873-6726</identifier><identifier>DOI: 10.1016/j.envsoft.2021.105254</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Algorithms ; Cloud computing ; computer software ; Data collection ; Discharge uncertainty ; Estimates ; Gauges ; Google earth engine ; Hydrologic models ; Hydrology ; Internet ; Landsat ; Landsat satellites ; North America ; Rating curve ; Remote sensing ; Remote sensing of discharge ; River discharge ; River flow ; River width ; Rivers ; Rodeos ; RSQ ; Satellite observation ; Satellites ; Uncertainty ; Water discharge</subject><ispartof>Environmental modelling & software : with environment data news, 2022-02, Vol.148, p.105254, Article 105254</ispartof><rights>2021 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. Feb 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c417t-ed46ae68099b6014fd9d320b05ec3864220497bebbca3e8cd660ef84e3b5f88d3</citedby><cites>FETCH-LOGICAL-c417t-ed46ae68099b6014fd9d320b05ec3864220497bebbca3e8cd660ef84e3b5f88d3</cites><orcidid>0000-0001-8301-5301 ; 0000-0002-0046-832X ; 0000-0001-6834-9469 ; 0000-0002-7275-7470</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.envsoft.2021.105254$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,45974</link.rule.ids></links><search><creatorcontrib>Riggs, Ryan M.</creatorcontrib><creatorcontrib>Allen, George H.</creatorcontrib><creatorcontrib>David, Cédric H.</creatorcontrib><creatorcontrib>Lin, Peirong</creatorcontrib><creatorcontrib>Pan, Ming</creatorcontrib><creatorcontrib>Yang, Xiao</creatorcontrib><creatorcontrib>Gleason, Colin</creatorcontrib><title>RODEO: An algorithm and Google Earth Engine application for river discharge retrieval from Landsat</title><title>Environmental modelling & software : with environment data news</title><description>Satellite remote sensing of river discharge (RSQ) algorithms provide a useful source of observations to supplement river gauge records. RSQ algorithms have existed for over a decade yet their widespread use has been impeded by a lack of operational usability and quantitative characterization of uncertainty. Here we present RODEO, an algorithm for estimating river discharge using Landsat observations in near-real time. RODEO is validated with 456 gauges (median Kling-Gupta efficiency = 0.3) and uses a novel quantile rating curve technique that pairs Landsat river widths with discharge estimates from a global hydrologic model. RODEO also characterizes the uncertainty of RSQ estimates (estimated root-mean-square error = +7%), enabling RSQ retrievals to be used for data assimilation into hydrologic models. With the goal of expanding the RSQ user base, the RODEO algorithm is implemented as a freely available, off-the-shelf cloud-based Google Earth Engine application that provides RSQ estimates across North America from 1984-present.
•We present RODEO, a user-friendly application for estimating river discharge from Landsat 5, 7, and 8.•River widths can be quickly extracted from Landsat images and used to estimate discharge.•RODEO characterizes discharge uncertainty allowing for remote sensing measurements to be used for data assimilation.</description><subject>Algorithms</subject><subject>Cloud computing</subject><subject>computer software</subject><subject>Data collection</subject><subject>Discharge uncertainty</subject><subject>Estimates</subject><subject>Gauges</subject><subject>Google earth engine</subject><subject>Hydrologic models</subject><subject>Hydrology</subject><subject>Internet</subject><subject>Landsat</subject><subject>Landsat satellites</subject><subject>North America</subject><subject>Rating curve</subject><subject>Remote sensing</subject><subject>Remote sensing of discharge</subject><subject>River discharge</subject><subject>River flow</subject><subject>River width</subject><subject>Rivers</subject><subject>Rodeos</subject><subject>RSQ</subject><subject>Satellite observation</subject><subject>Satellites</subject><subject>Uncertainty</subject><subject>Water discharge</subject><issn>1364-8152</issn><issn>1873-6726</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNqFkE9rGzEQxZfSQtO0H6Eg6KWXdfVvtdpeSkjcJGAwhOQstNKsLbOW3JFsyLevjHPqpad5DL_3mHlN85XRBaNM_dgtIJ5ymsqCU87qruOdfNdcMd2LVvVcva9aKNlq1vGPzaecd5TSquVVMz6t75brn-QmEjtvEoay3RMbPblPaTMDWVosW7KMmxCB2MNhDs6WkCKZEhIMJ0DiQ3ZbixsgCAUDnOxMJkx7sqo52ZbPzYfJzhm-vM3r5uX38vn2oV2t7x9vb1atk6wvLXipLChNh2FUlMnJD15wOtIOnNBKck7l0I8wjs4K0M4rRWHSEsTYTVp7cd18v-QeMP05Qi5mXy-DebYR0jEbroTqO66FqOi3f9BdOmKs150pTfuh12equ1AOU84Ikzlg2Ft8NYyac_NmZ96aN-fmzaX56vt18UH99hQATXYBogMfEFwxPoX_JPwF-oaOyQ</recordid><startdate>202202</startdate><enddate>202202</enddate><creator>Riggs, Ryan M.</creator><creator>Allen, George H.</creator><creator>David, Cédric H.</creator><creator>Lin, Peirong</creator><creator>Pan, Ming</creator><creator>Yang, Xiao</creator><creator>Gleason, Colin</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7SC</scope><scope>7ST</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>SOI</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0001-8301-5301</orcidid><orcidid>https://orcid.org/0000-0002-0046-832X</orcidid><orcidid>https://orcid.org/0000-0001-6834-9469</orcidid><orcidid>https://orcid.org/0000-0002-7275-7470</orcidid></search><sort><creationdate>202202</creationdate><title>RODEO: An algorithm and Google Earth Engine application for river discharge retrieval from Landsat</title><author>Riggs, Ryan M. ; Allen, George H. ; David, Cédric H. ; Lin, Peirong ; Pan, Ming ; Yang, Xiao ; Gleason, Colin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c417t-ed46ae68099b6014fd9d320b05ec3864220497bebbca3e8cd660ef84e3b5f88d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Cloud computing</topic><topic>computer software</topic><topic>Data collection</topic><topic>Discharge uncertainty</topic><topic>Estimates</topic><topic>Gauges</topic><topic>Google earth engine</topic><topic>Hydrologic models</topic><topic>Hydrology</topic><topic>Internet</topic><topic>Landsat</topic><topic>Landsat satellites</topic><topic>North America</topic><topic>Rating curve</topic><topic>Remote sensing</topic><topic>Remote sensing of discharge</topic><topic>River discharge</topic><topic>River flow</topic><topic>River width</topic><topic>Rivers</topic><topic>Rodeos</topic><topic>RSQ</topic><topic>Satellite observation</topic><topic>Satellites</topic><topic>Uncertainty</topic><topic>Water discharge</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Riggs, Ryan M.</creatorcontrib><creatorcontrib>Allen, George H.</creatorcontrib><creatorcontrib>David, Cédric H.</creatorcontrib><creatorcontrib>Lin, Peirong</creatorcontrib><creatorcontrib>Pan, Ming</creatorcontrib><creatorcontrib>Yang, Xiao</creatorcontrib><creatorcontrib>Gleason, Colin</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Computer and Information Systems Abstracts</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Environment Abstracts</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Environmental modelling & software : with environment data news</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Riggs, Ryan M.</au><au>Allen, George H.</au><au>David, Cédric H.</au><au>Lin, Peirong</au><au>Pan, Ming</au><au>Yang, Xiao</au><au>Gleason, Colin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>RODEO: An algorithm and Google Earth Engine application for river discharge retrieval from Landsat</atitle><jtitle>Environmental modelling & software : with environment data news</jtitle><date>2022-02</date><risdate>2022</risdate><volume>148</volume><spage>105254</spage><pages>105254-</pages><artnum>105254</artnum><issn>1364-8152</issn><eissn>1873-6726</eissn><abstract>Satellite remote sensing of river discharge (RSQ) algorithms provide a useful source of observations to supplement river gauge records. RSQ algorithms have existed for over a decade yet their widespread use has been impeded by a lack of operational usability and quantitative characterization of uncertainty. Here we present RODEO, an algorithm for estimating river discharge using Landsat observations in near-real time. RODEO is validated with 456 gauges (median Kling-Gupta efficiency = 0.3) and uses a novel quantile rating curve technique that pairs Landsat river widths with discharge estimates from a global hydrologic model. RODEO also characterizes the uncertainty of RSQ estimates (estimated root-mean-square error = +7%), enabling RSQ retrievals to be used for data assimilation into hydrologic models. With the goal of expanding the RSQ user base, the RODEO algorithm is implemented as a freely available, off-the-shelf cloud-based Google Earth Engine application that provides RSQ estimates across North America from 1984-present.
•We present RODEO, a user-friendly application for estimating river discharge from Landsat 5, 7, and 8.•River widths can be quickly extracted from Landsat images and used to estimate discharge.•RODEO characterizes discharge uncertainty allowing for remote sensing measurements to be used for data assimilation.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.envsoft.2021.105254</doi><orcidid>https://orcid.org/0000-0001-8301-5301</orcidid><orcidid>https://orcid.org/0000-0002-0046-832X</orcidid><orcidid>https://orcid.org/0000-0001-6834-9469</orcidid><orcidid>https://orcid.org/0000-0002-7275-7470</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1364-8152 |
ispartof | Environmental modelling & software : with environment data news, 2022-02, Vol.148, p.105254, Article 105254 |
issn | 1364-8152 1873-6726 |
language | eng |
recordid | cdi_proquest_journals_2638079783 |
source | Elsevier ScienceDirect Journals |
subjects | Algorithms Cloud computing computer software Data collection Discharge uncertainty Estimates Gauges Google earth engine Hydrologic models Hydrology Internet Landsat Landsat satellites North America Rating curve Remote sensing Remote sensing of discharge River discharge River flow River width Rivers Rodeos RSQ Satellite observation Satellites Uncertainty Water discharge |
title | RODEO: An algorithm and Google Earth Engine application for river discharge retrieval from Landsat |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T18%3A39%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=RODEO:%20An%20algorithm%20and%20Google%20Earth%20Engine%20application%20for%20river%20discharge%20retrieval%20from%20Landsat&rft.jtitle=Environmental%20modelling%20&%20software%20:%20with%20environment%20data%20news&rft.au=Riggs,%20Ryan%20M.&rft.date=2022-02&rft.volume=148&rft.spage=105254&rft.pages=105254-&rft.artnum=105254&rft.issn=1364-8152&rft.eissn=1873-6726&rft_id=info:doi/10.1016/j.envsoft.2021.105254&rft_dat=%3Cproquest_cross%3E2636752833%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2638079783&rft_id=info:pmid/&rft_els_id=S1364815221002966&rfr_iscdi=true |