High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River
Quantifying planform changes of large and actively migrating rivers such as those in the tropical Amazon at multidecadal time scales, over large spatial domains, and with high spatiotemporal frequency is essential for advancing river morphodynamic theory, identifying controls on migration, and under...
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creator | Schwenk, Jon Khandelwal, Ankush Fratkin, Mulu Kumar, Vipin Foufoula‐Georgiou, Efi |
description | Quantifying planform changes of large and actively migrating rivers such as those in the tropical Amazon at multidecadal time scales, over large spatial domains, and with high spatiotemporal frequency is essential for advancing river morphodynamic theory, identifying controls on migration, and understanding the roles of climate and human influences on planform adjustments. This paper addresses the challenges of quantifying river planform changes from annual channel masks derived from Landsat imagery and introduces a set of efficient methods to map and measure changes in channel widths, the locations and rates of migration, accretion and erosion, and the space‐time characteristics of cutoff dynamics. The techniques are assembled in a comprehensive MATLAB toolbox called RivMAP (River Morphodynamics from Analysis of Planforms), which is applied to over 1500 km of the actively migrating and predominately meandering Ucayali River in Peru from 1985 to 2015. We find multiscale spatial and temporal variability around multidecadal trends in migration rates, erosion and accretion, and channel widths revealing a river dynamically adjusting to sediment and water fluxes. Confounding factors controlling planform morphodynamics including local inputs of sediment, cutoffs, and climate are parsed through the high temporal analysis.
Plain Language Summary
We use Landsat satellite imagery to map out movements of an extraordinarily active and complex river in South America. We mined over 135,000 images to create one snapshot of the river per year, and we developed a comprehensive toolbox to map and quantify changes in the river's position and width. We show annually‐resolved migration rates and patterns over 31 years and find that climate, cutoffs, and nearby sediment inputs are important controls on river planform changes.
Key Points
Annual planform changes mapped for large, dynamic meandering river from Landsat imagery
RivMAP toolbox offers novel image processing‐based techniques for analyzing channel masks
Application to Ucayali River identifies sediment, cutoff, and climate controls on planform morphodynamics |
doi_str_mv | 10.1002/2016EA000196 |
format | Article |
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Plain Language Summary
We use Landsat satellite imagery to map out movements of an extraordinarily active and complex river in South America. We mined over 135,000 images to create one snapshot of the river per year, and we developed a comprehensive toolbox to map and quantify changes in the river's position and width. We show annually‐resolved migration rates and patterns over 31 years and find that climate, cutoffs, and nearby sediment inputs are important controls on river planform changes.
Key Points
Annual planform changes mapped for large, dynamic meandering river from Landsat imagery
RivMAP toolbox offers novel image processing‐based techniques for analyzing channel masks
Application to Ucayali River identifies sediment, cutoff, and climate controls on planform morphodynamics</description><identifier>ISSN: 2333-5084</identifier><identifier>EISSN: 2333-5084</identifier><identifier>DOI: 10.1002/2016EA000196</identifier><language>eng</language><publisher>Hoboken: John Wiley & Sons, Inc</publisher><subject>Erosion rates ; Human influences ; image processing ; Landsat ; Landsat satellites ; MATLAB ; meander dynamics ; planform change ; Remote sensing ; river migration ; Rivers ; Scholarships & fellowships ; Software packages</subject><ispartof>Earth and space science (Hoboken, N.J.), 2017-02, Vol.4 (2), p.46-75</ispartof><rights>2016. The Authors.</rights><rights>2017. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4099-6d661c760d1eaf3c34cc94979f31e95870e529477450a4fbffe28da36a865ecd3</citedby><cites>FETCH-LOGICAL-c4099-6d661c760d1eaf3c34cc94979f31e95870e529477450a4fbffe28da36a865ecd3</cites><orcidid>0000-0003-1078-231X ; 0000-0001-5803-9686</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2F2016EA000196$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2F2016EA000196$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,861,1412,11543,27905,27906,45555,45556,46033,46457</link.rule.ids></links><search><creatorcontrib>Schwenk, Jon</creatorcontrib><creatorcontrib>Khandelwal, Ankush</creatorcontrib><creatorcontrib>Fratkin, Mulu</creatorcontrib><creatorcontrib>Kumar, Vipin</creatorcontrib><creatorcontrib>Foufoula‐Georgiou, Efi</creatorcontrib><title>High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River</title><title>Earth and space science (Hoboken, N.J.)</title><description>Quantifying planform changes of large and actively migrating rivers such as those in the tropical Amazon at multidecadal time scales, over large spatial domains, and with high spatiotemporal frequency is essential for advancing river morphodynamic theory, identifying controls on migration, and understanding the roles of climate and human influences on planform adjustments. This paper addresses the challenges of quantifying river planform changes from annual channel masks derived from Landsat imagery and introduces a set of efficient methods to map and measure changes in channel widths, the locations and rates of migration, accretion and erosion, and the space‐time characteristics of cutoff dynamics. The techniques are assembled in a comprehensive MATLAB toolbox called RivMAP (River Morphodynamics from Analysis of Planforms), which is applied to over 1500 km of the actively migrating and predominately meandering Ucayali River in Peru from 1985 to 2015. We find multiscale spatial and temporal variability around multidecadal trends in migration rates, erosion and accretion, and channel widths revealing a river dynamically adjusting to sediment and water fluxes. Confounding factors controlling planform morphodynamics including local inputs of sediment, cutoffs, and climate are parsed through the high temporal analysis.
Plain Language Summary
We use Landsat satellite imagery to map out movements of an extraordinarily active and complex river in South America. We mined over 135,000 images to create one snapshot of the river per year, and we developed a comprehensive toolbox to map and quantify changes in the river's position and width. We show annually‐resolved migration rates and patterns over 31 years and find that climate, cutoffs, and nearby sediment inputs are important controls on river planform changes.
Key Points
Annual planform changes mapped for large, dynamic meandering river from Landsat imagery
RivMAP toolbox offers novel image processing‐based techniques for analyzing channel masks
Application to Ucayali River identifies sediment, cutoff, and climate controls on planform morphodynamics</description><subject>Erosion rates</subject><subject>Human influences</subject><subject>image processing</subject><subject>Landsat</subject><subject>Landsat satellites</subject><subject>MATLAB</subject><subject>meander dynamics</subject><subject>planform change</subject><subject>Remote sensing</subject><subject>river migration</subject><subject>Rivers</subject><subject>Scholarships & fellowships</subject><subject>Software packages</subject><issn>2333-5084</issn><issn>2333-5084</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp90M9LwzAUB_AiCg7dzT8g4NVqfjVtvI0xnTBR3HYuWZq4jLSpSTvtwf_dlu2wk6f3eO_De_CNohsE7xGE-AFDxGYTCCHi7CwaYUJInMCMnp_0l9E4hN1gcMIgpqPod24-tyDUojGuUWXtvLDAq-Bs208q4DTwZq88qK2otPMlKLpKlEYGoL0rwUJURRDNI1htFfgw-9fJO2icsxv3A_rVcKq1zRE3vVlL0QlrBqv8dXShhQ1qfKxX0fpptprO48Xb88t0soglhZzHrGAMyZTBAimhiSRUSk55yjVBiidZClWCOU1TmkBB9UZrhbNCECYylihZkKvo9nC39u6rVaHJd671Vf8yx5hDTDgjaa_uDkp6F4JXOq-9KYXvcgTzIeP8NOOeowP_NlZ1_9p8tlxiBDn5A9oCfWo</recordid><startdate>201702</startdate><enddate>201702</enddate><creator>Schwenk, Jon</creator><creator>Khandelwal, Ankush</creator><creator>Fratkin, Mulu</creator><creator>Kumar, Vipin</creator><creator>Foufoula‐Georgiou, Efi</creator><general>John Wiley & Sons, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0003-1078-231X</orcidid><orcidid>https://orcid.org/0000-0001-5803-9686</orcidid></search><sort><creationdate>201702</creationdate><title>High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River</title><author>Schwenk, Jon ; Khandelwal, Ankush ; Fratkin, Mulu ; Kumar, Vipin ; Foufoula‐Georgiou, Efi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4099-6d661c760d1eaf3c34cc94979f31e95870e529477450a4fbffe28da36a865ecd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Erosion rates</topic><topic>Human influences</topic><topic>image processing</topic><topic>Landsat</topic><topic>Landsat satellites</topic><topic>MATLAB</topic><topic>meander dynamics</topic><topic>planform change</topic><topic>Remote sensing</topic><topic>river migration</topic><topic>Rivers</topic><topic>Scholarships & fellowships</topic><topic>Software packages</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Schwenk, Jon</creatorcontrib><creatorcontrib>Khandelwal, Ankush</creatorcontrib><creatorcontrib>Fratkin, Mulu</creatorcontrib><creatorcontrib>Kumar, Vipin</creatorcontrib><creatorcontrib>Foufoula‐Georgiou, Efi</creatorcontrib><collection>Wiley Online Library</collection><collection>Wiley Online Library Journals</collection><collection>CrossRef</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Earth and space science (Hoboken, N.J.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Schwenk, Jon</au><au>Khandelwal, Ankush</au><au>Fratkin, Mulu</au><au>Kumar, Vipin</au><au>Foufoula‐Georgiou, Efi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River</atitle><jtitle>Earth and space science (Hoboken, N.J.)</jtitle><date>2017-02</date><risdate>2017</risdate><volume>4</volume><issue>2</issue><spage>46</spage><epage>75</epage><pages>46-75</pages><issn>2333-5084</issn><eissn>2333-5084</eissn><abstract>Quantifying planform changes of large and actively migrating rivers such as those in the tropical Amazon at multidecadal time scales, over large spatial domains, and with high spatiotemporal frequency is essential for advancing river morphodynamic theory, identifying controls on migration, and understanding the roles of climate and human influences on planform adjustments. This paper addresses the challenges of quantifying river planform changes from annual channel masks derived from Landsat imagery and introduces a set of efficient methods to map and measure changes in channel widths, the locations and rates of migration, accretion and erosion, and the space‐time characteristics of cutoff dynamics. The techniques are assembled in a comprehensive MATLAB toolbox called RivMAP (River Morphodynamics from Analysis of Planforms), which is applied to over 1500 km of the actively migrating and predominately meandering Ucayali River in Peru from 1985 to 2015. We find multiscale spatial and temporal variability around multidecadal trends in migration rates, erosion and accretion, and channel widths revealing a river dynamically adjusting to sediment and water fluxes. Confounding factors controlling planform morphodynamics including local inputs of sediment, cutoffs, and climate are parsed through the high temporal analysis.
Plain Language Summary
We use Landsat satellite imagery to map out movements of an extraordinarily active and complex river in South America. We mined over 135,000 images to create one snapshot of the river per year, and we developed a comprehensive toolbox to map and quantify changes in the river's position and width. We show annually‐resolved migration rates and patterns over 31 years and find that climate, cutoffs, and nearby sediment inputs are important controls on river planform changes.
Key Points
Annual planform changes mapped for large, dynamic meandering river from Landsat imagery
RivMAP toolbox offers novel image processing‐based techniques for analyzing channel masks
Application to Ucayali River identifies sediment, cutoff, and climate controls on planform morphodynamics</abstract><cop>Hoboken</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1002/2016EA000196</doi><tpages>30</tpages><orcidid>https://orcid.org/0000-0003-1078-231X</orcidid><orcidid>https://orcid.org/0000-0001-5803-9686</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Erosion rates Human influences image processing Landsat Landsat satellites MATLAB meander dynamics planform change Remote sensing river migration Rivers Scholarships & fellowships Software packages |
title | High spatiotemporal resolution of river planform dynamics from Landsat: The RivMAP toolbox and results from the Ucayali River |
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