Integrating Depth Measurements From Gaging Stations With Image Archives for Spectrally Based Remote Sensing of River Bathymetry
Remote sensing can be an effective tool for mapping river bathymetry, but the need for direct measurements to calibrate image‐derived depth estimates impedes broader application of this approach. One way to circumvent the need for field campaigns dedicated to calibration is to capitalize upon existi...
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| Veröffentlicht in: | Water resources research 2024-07, Vol.60 (7), p.n/a |
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| creator | Legleiter, Carl J. Overstreet, Brandon T. Kinzel, Paul J. |
| description | Remote sensing can be an effective tool for mapping river bathymetry, but the need for direct measurements to calibrate image‐derived depth estimates impedes broader application of this approach. One way to circumvent the need for field campaigns dedicated to calibration is to capitalize upon existing data. In this study, we introduce a framework for Bathymetric Mapping using Gage Records and Image Databases (BaMGRID). This workflow involves retrieving depth measurements made during gaging station site visits, downloading archived multispectral images, and then combining these two data sets to establish a relationship between depth and reflectance. We developed a processing chain that involves using application programming interfaces to obtain both depth measurements made during site visits and images centered on the gage and then linking depth to reflectance via an optimal band ratio analysis (OBRA) algorithm modified for small sample sizes. Applying this workflow to selected gages within two river basins indicated that depth retrieval from multispectral satellite images could be highly accurate, but with variable results from one image to the next at a given site. High resolution aerial photography was less conducive to bathymetric mapping in one of the basin considered. Of the four predictors of depth retrieval performance we evaluated (mean and standard deviation of depth, width, and an index of water clarity), only width was consistently significantly correlated with OBRA R2 (p |
| doi_str_mv | 10.1029/2024WR037295 |
| format | Article |
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Key Points
Combine depth measurements made during site visits to gaging stations with archived images to enable remote sensing of river bathymetry
Multispectral satellite images acquired daily can yield highly accurate depth estimates, but high resolution air photos were less accurate
Bathymetric Mapping using Gage Records and Image Databases (BaMGRID) is well suited to site‐by‐site analysis for reach‐scale applications</description><identifier>ISSN: 0043-1397</identifier><identifier>EISSN: 1944-7973</identifier><identifier>DOI: 10.1029/2024WR037295</identifier><language>eng</language><publisher>Washington: John Wiley & Sons, Inc</publisher><subject>Aerial photography ; Algorithms ; Application programming interface ; Archives & records ; basins ; Bathymeters ; Bathymetry ; depth ; Depth measurement ; Discharge measurement ; Gaging stations ; Gauges ; Image resolution ; Interfaces ; Mapping ; Reflectance ; Remote sensing ; Retrieval ; River basins ; Rivers ; Satellite imagery ; satellite images ; Satellite photography ; satellites ; standard deviation ; Stream discharge ; water ; Water depth ; water quality ; Workflow</subject><ispartof>Water resources research, 2024-07, Vol.60 (7), p.n/a</ispartof><rights>Published 2024. This article is a U.S. Government work and is in the public domain in the USA.</rights><rights>Published 2024. This article is a U.S. Government work and is in the public domain in the USA. This article 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><cites>FETCH-LOGICAL-a2882-a81db4fd3ca0f0b873509369d044a8ddf9feb3438d04e9aabb971a44bec5c1243</cites><orcidid>0000-0003-0940-8013 ; 0000-0001-7845-6671</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2024WR037295$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2024WR037295$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,1412,11495,11543,27905,27906,45555,45556,46033,46449,46457,46873</link.rule.ids></links><search><creatorcontrib>Legleiter, Carl J.</creatorcontrib><creatorcontrib>Overstreet, Brandon T.</creatorcontrib><creatorcontrib>Kinzel, Paul J.</creatorcontrib><title>Integrating Depth Measurements From Gaging Stations With Image Archives for Spectrally Based Remote Sensing of River Bathymetry</title><title>Water resources research</title><description>Remote sensing can be an effective tool for mapping river bathymetry, but the need for direct measurements to calibrate image‐derived depth estimates impedes broader application of this approach. One way to circumvent the need for field campaigns dedicated to calibration is to capitalize upon existing data. In this study, we introduce a framework for Bathymetric Mapping using Gage Records and Image Databases (BaMGRID). This workflow involves retrieving depth measurements made during gaging station site visits, downloading archived multispectral images, and then combining these two data sets to establish a relationship between depth and reflectance. We developed a processing chain that involves using application programming interfaces to obtain both depth measurements made during site visits and images centered on the gage and then linking depth to reflectance via an optimal band ratio analysis (OBRA) algorithm modified for small sample sizes. Applying this workflow to selected gages within two river basins indicated that depth retrieval from multispectral satellite images could be highly accurate, but with variable results from one image to the next at a given site. High resolution aerial photography was less conducive to bathymetric mapping in one of the basin considered. Of the four predictors of depth retrieval performance we evaluated (mean and standard deviation of depth, width, and an index of water clarity), only width was consistently significantly correlated with OBRA R2 (p < 0.026). Currently, BaMGRID is best‐suited for site‐by‐site analysis to support practical applications at the reach scale; continuous, basin‐wide mapping of river bathymetry will require additional research.
Key Points
Combine depth measurements made during site visits to gaging stations with archived images to enable remote sensing of river bathymetry
Multispectral satellite images acquired daily can yield highly accurate depth estimates, but high resolution air photos were less accurate
Bathymetric Mapping using Gage Records and Image Databases (BaMGRID) is well suited to site‐by‐site analysis for reach‐scale applications</description><subject>Aerial photography</subject><subject>Algorithms</subject><subject>Application programming interface</subject><subject>Archives & records</subject><subject>basins</subject><subject>Bathymeters</subject><subject>Bathymetry</subject><subject>depth</subject><subject>Depth measurement</subject><subject>Discharge measurement</subject><subject>Gaging stations</subject><subject>Gauges</subject><subject>Image resolution</subject><subject>Interfaces</subject><subject>Mapping</subject><subject>Reflectance</subject><subject>Remote sensing</subject><subject>Retrieval</subject><subject>River basins</subject><subject>Rivers</subject><subject>Satellite imagery</subject><subject>satellite images</subject><subject>Satellite photography</subject><subject>satellites</subject><subject>standard deviation</subject><subject>Stream discharge</subject><subject>water</subject><subject>Water depth</subject><subject>water quality</subject><subject>Workflow</subject><issn>0043-1397</issn><issn>1944-7973</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp90c9r2zAUB3AxVliW9rY_QLDLDnWrX7akY5o1bSCl4HTkaGT7OXGxrVRSVnzqv16F9FB22OnBex--PPgi9IOSK0qYvmaEiU1OuGQ6_YImVAuRSC35VzQhRPCEci2_oe_ePxNCRZrJCXpbDgG2zoR22OLfsA87_ADGHxz0MASPF872-M5sj-d1iMwOHm_ayJa92QKeuWrX_gWPG-vweg9VcKbrRnxjPNQ4h94GwGsY_DHANjiP2MVr2I09BDeeo7PGdB4uPuYU_VncPs3vk9Xj3XI-WyWGKcUSo2hdiqbmlSENKZXkKdE80zURwqi6bnQDJRdcxQVoY8pSS2qEKKFKK8oEn6Jfp9y9sy8H8KHoW19B15kB7MEXnKZckkzoLNKf_9Bne3BD_K7gRKWZkIqyqC5PqnLWewdNsXdtb9xYUFIc2yg-txE5P_HXtoPxv7bY5POcSa4YfweEn4y-</recordid><startdate>202407</startdate><enddate>202407</enddate><creator>Legleiter, Carl J.</creator><creator>Overstreet, Brandon T.</creator><creator>Kinzel, Paul J.</creator><general>John Wiley & Sons, Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7QL</scope><scope>7T7</scope><scope>7TG</scope><scope>7U9</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H94</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>M7N</scope><scope>P64</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0003-0940-8013</orcidid><orcidid>https://orcid.org/0000-0001-7845-6671</orcidid></search><sort><creationdate>202407</creationdate><title>Integrating Depth Measurements From Gaging Stations With Image Archives for Spectrally Based Remote Sensing of River Bathymetry</title><author>Legleiter, Carl J. ; Overstreet, Brandon T. ; Kinzel, Paul J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a2882-a81db4fd3ca0f0b873509369d044a8ddf9feb3438d04e9aabb971a44bec5c1243</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aerial photography</topic><topic>Algorithms</topic><topic>Application programming interface</topic><topic>Archives & records</topic><topic>basins</topic><topic>Bathymeters</topic><topic>Bathymetry</topic><topic>depth</topic><topic>Depth measurement</topic><topic>Discharge measurement</topic><topic>Gaging stations</topic><topic>Gauges</topic><topic>Image resolution</topic><topic>Interfaces</topic><topic>Mapping</topic><topic>Reflectance</topic><topic>Remote sensing</topic><topic>Retrieval</topic><topic>River basins</topic><topic>Rivers</topic><topic>Satellite imagery</topic><topic>satellite images</topic><topic>Satellite photography</topic><topic>satellites</topic><topic>standard deviation</topic><topic>Stream discharge</topic><topic>water</topic><topic>Water depth</topic><topic>water quality</topic><topic>Workflow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Legleiter, Carl J.</creatorcontrib><creatorcontrib>Overstreet, Brandon T.</creatorcontrib><creatorcontrib>Kinzel, Paul J.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Free Content</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Water resources research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Legleiter, Carl J.</au><au>Overstreet, Brandon T.</au><au>Kinzel, Paul J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrating Depth Measurements From Gaging Stations With Image Archives for Spectrally Based Remote Sensing of River Bathymetry</atitle><jtitle>Water resources research</jtitle><date>2024-07</date><risdate>2024</risdate><volume>60</volume><issue>7</issue><epage>n/a</epage><issn>0043-1397</issn><eissn>1944-7973</eissn><abstract>Remote sensing can be an effective tool for mapping river bathymetry, but the need for direct measurements to calibrate image‐derived depth estimates impedes broader application of this approach. One way to circumvent the need for field campaigns dedicated to calibration is to capitalize upon existing data. In this study, we introduce a framework for Bathymetric Mapping using Gage Records and Image Databases (BaMGRID). This workflow involves retrieving depth measurements made during gaging station site visits, downloading archived multispectral images, and then combining these two data sets to establish a relationship between depth and reflectance. We developed a processing chain that involves using application programming interfaces to obtain both depth measurements made during site visits and images centered on the gage and then linking depth to reflectance via an optimal band ratio analysis (OBRA) algorithm modified for small sample sizes. Applying this workflow to selected gages within two river basins indicated that depth retrieval from multispectral satellite images could be highly accurate, but with variable results from one image to the next at a given site. High resolution aerial photography was less conducive to bathymetric mapping in one of the basin considered. Of the four predictors of depth retrieval performance we evaluated (mean and standard deviation of depth, width, and an index of water clarity), only width was consistently significantly correlated with OBRA R2 (p < 0.026). Currently, BaMGRID is best‐suited for site‐by‐site analysis to support practical applications at the reach scale; continuous, basin‐wide mapping of river bathymetry will require additional research.
Key Points
Combine depth measurements made during site visits to gaging stations with archived images to enable remote sensing of river bathymetry
Multispectral satellite images acquired daily can yield highly accurate depth estimates, but high resolution air photos were less accurate
Bathymetric Mapping using Gage Records and Image Databases (BaMGRID) is well suited to site‐by‐site analysis for reach‐scale applications</abstract><cop>Washington</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1029/2024WR037295</doi><tpages>33</tpages><orcidid>https://orcid.org/0000-0003-0940-8013</orcidid><orcidid>https://orcid.org/0000-0001-7845-6671</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Water resources research, 2024-07, Vol.60 (7), p.n/a |
| issn | 0043-1397 1944-7973 |
| language | eng |
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| source | Wiley Online Library Journals Frontfile Complete; Wiley-Blackwell AGU Digital Library; Wiley Online Library Open Access |
| subjects | Aerial photography Algorithms Application programming interface Archives & records basins Bathymeters Bathymetry depth Depth measurement Discharge measurement Gaging stations Gauges Image resolution Interfaces Mapping Reflectance Remote sensing Retrieval River basins Rivers Satellite imagery satellite images Satellite photography satellites standard deviation Stream discharge water Water depth water quality Workflow |
| title | Integrating Depth Measurements From Gaging Stations With Image Archives for Spectrally Based Remote Sensing of River Bathymetry |
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