Riparian Wetland Mapping and Inundation Monitoring Using Amplitude and Bistatic Coherence Data From the TanDEM-X Mission
This article focuses on bistatic coherence as an additional feature complementing amplitudes in classification space, permitting to monitor temporal changes in water extent on the wetland comprising surface water and inundated vegetation. The research was conducted on a herbaceous wetland. The TanDE...
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Veröffentlicht in: | IEEE journal of selected topics in applied earth observations and remote sensing 2021, Vol.14, p.2432-2444 |
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description | This article focuses on bistatic coherence as an additional feature complementing amplitudes in classification space, permitting to monitor temporal changes in water extent on the wetland comprising surface water and inundated vegetation. The research was conducted on a herbaceous wetland. The TanDEM-X images were acquired during the science phase in bistatic mode with long perpendicular baselines. Two different sets of observations were computed: polarimetric amplitudes (PAs) and interferometric coherences in single-pass mode. Next, the datasets composed of a multitemporal stack of images were classified using object-based image analysis. The main outcome of the experiment is that bistatic coherences increased greatly the overall accuracy (OA) of expected thematic classes. The OA shows that thematic categories were classified with higher accuracy when the bistatic coherence complemented PAs. The OA is greater than 85% for all analyzed datatakes. The accuracy achieved using amplitudes only was higher than 70% but varied overtime. The bistatic coherence at X-band turned out to be really helpful in mapping high vegetation, which can be an indicator that this methodology can be directly used in the monitoring of common reed mowing or mapping highly invasive vegetation. Additionally, we could observe that short inundated vegetation was also mapped correctly, allowing flooded areas in this floodplain to be mapped with great precision throughout the growing season. |
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The research was conducted on a herbaceous wetland. The TanDEM-X images were acquired during the science phase in bistatic mode with long perpendicular baselines. Two different sets of observations were computed: polarimetric amplitudes (PAs) and interferometric coherences in single-pass mode. Next, the datasets composed of a multitemporal stack of images were classified using object-based image analysis. The main outcome of the experiment is that bistatic coherences increased greatly the overall accuracy (OA) of expected thematic classes. The OA shows that thematic categories were classified with higher accuracy when the bistatic coherence complemented PAs. The OA is greater than 85% for all analyzed datatakes. The accuracy achieved using amplitudes only was higher than 70% but varied overtime. The bistatic coherence at X-band turned out to be really helpful in mapping high vegetation, which can be an indicator that this methodology can be directly used in the monitoring of common reed mowing or mapping highly invasive vegetation. Additionally, we could observe that short inundated vegetation was also mapped correctly, allowing flooded areas in this floodplain to be mapped with great precision throughout the growing season.</description><identifier>ISSN: 1939-1404</identifier><identifier>EISSN: 2151-1535</identifier><identifier>DOI: 10.1109/JSTARS.2021.3054994</identifier><identifier>CODEN: IJSTHZ</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Accuracy ; Amplitudes ; Bistatic coherence ; Coherence ; Flooded areas ; flooded vegetation ; Flooding ; Floodplains ; Floods ; Image acquisition ; Image analysis ; Image processing ; Mapping ; Monitoring ; Mowing ; Polarimetry ; riparian wetland mapping ; Rivers ; Superhigh frequencies ; Surface water ; Synthetic aperture radar ; TanDEM-X (TDX) ; Temporal variations ; Vegetation ; Vegetation mapping ; Wetlands</subject><ispartof>IEEE journal of selected topics in applied earth observations and remote sensing, 2021, Vol.14, p.2432-2444</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c363t-a9e4cee4ab6c5ac17852f75c24a0c7d9a2639e140fa6f9a0f9ba9eb33ce96ebc3</citedby><cites>FETCH-LOGICAL-c363t-a9e4cee4ab6c5ac17852f75c24a0c7d9a2639e140fa6f9a0f9ba9eb33ce96ebc3</cites><orcidid>0000-0003-0929-4300 ; 0000-0002-9932-1810</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,2096,4010,27900,27901,27902</link.rule.ids></links><search><creatorcontrib>Mleczko, Magdalena</creatorcontrib><creatorcontrib>Mroz, Marek</creatorcontrib><creatorcontrib>Fitrzyk, Magdalena</creatorcontrib><title>Riparian Wetland Mapping and Inundation Monitoring Using Amplitude and Bistatic Coherence Data From the TanDEM-X Mission</title><title>IEEE journal of selected topics in applied earth observations and remote sensing</title><addtitle>JSTARS</addtitle><description>This article focuses on bistatic coherence as an additional feature complementing amplitudes in classification space, permitting to monitor temporal changes in water extent on the wetland comprising surface water and inundated vegetation. The research was conducted on a herbaceous wetland. The TanDEM-X images were acquired during the science phase in bistatic mode with long perpendicular baselines. Two different sets of observations were computed: polarimetric amplitudes (PAs) and interferometric coherences in single-pass mode. Next, the datasets composed of a multitemporal stack of images were classified using object-based image analysis. The main outcome of the experiment is that bistatic coherences increased greatly the overall accuracy (OA) of expected thematic classes. The OA shows that thematic categories were classified with higher accuracy when the bistatic coherence complemented PAs. The OA is greater than 85% for all analyzed datatakes. The accuracy achieved using amplitudes only was higher than 70% but varied overtime. The bistatic coherence at X-band turned out to be really helpful in mapping high vegetation, which can be an indicator that this methodology can be directly used in the monitoring of common reed mowing or mapping highly invasive vegetation. Additionally, we could observe that short inundated vegetation was also mapped correctly, allowing flooded areas in this floodplain to be mapped with great precision throughout the growing season.</description><subject>Accuracy</subject><subject>Amplitudes</subject><subject>Bistatic coherence</subject><subject>Coherence</subject><subject>Flooded areas</subject><subject>flooded vegetation</subject><subject>Flooding</subject><subject>Floodplains</subject><subject>Floods</subject><subject>Image acquisition</subject><subject>Image analysis</subject><subject>Image processing</subject><subject>Mapping</subject><subject>Monitoring</subject><subject>Mowing</subject><subject>Polarimetry</subject><subject>riparian wetland mapping</subject><subject>Rivers</subject><subject>Superhigh frequencies</subject><subject>Surface water</subject><subject>Synthetic aperture radar</subject><subject>TanDEM-X (TDX)</subject><subject>Temporal variations</subject><subject>Vegetation</subject><subject>Vegetation mapping</subject><subject>Wetlands</subject><issn>1939-1404</issn><issn>2151-1535</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNo9kc1u2zAQhIWgBeqmfYJcCOQsh7-SeHSdpHURo0DioL0RK2qV0LBJlZSB5u1LRUEuywU5M7vEVxQXjC4Zo_rq58Nudf-w5JSzpaBKai3PigVnipVMCfWhWDAtdMkklZ-KzyntKa14rcWi-HfvBogOPPmN4wF8R7YwDM4_kanf-JPvYHTBk23wbgxxenlMU10dh4MbTx2-Kr-5NGahJevwjBG9RXINI5DbGI5kfEayA399sy3_kK1LKQd-KT72cEj49e08Lx5vb3brH-Xdr--b9equtKISYwkapUWU0FZWgWV1o3hfK8slUFt3GnglNOaP9VD1Gmiv22xphbCoK2ytOC82c24XYG-G6I4QX0wAZ14vQnwyEPPiBzS6VbaStWBtJ6RitGW0on0Lfa01502Tsy7nrCGGvydMo9mHU_R5fcOl5o1SjRRZJWaVjSGliP37VEbNhMvMuMyEy7zhyq6L2eUQ8d2hhdA6I_wPZoWSBQ</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Mleczko, Magdalena</creator><creator>Mroz, Marek</creator><creator>Fitrzyk, Magdalena</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-0929-4300</orcidid><orcidid>https://orcid.org/0000-0002-9932-1810</orcidid></search><sort><creationdate>2021</creationdate><title>Riparian Wetland Mapping and Inundation Monitoring Using Amplitude and Bistatic Coherence Data From the TanDEM-X Mission</title><author>Mleczko, Magdalena ; Mroz, Marek ; Fitrzyk, Magdalena</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c363t-a9e4cee4ab6c5ac17852f75c24a0c7d9a2639e140fa6f9a0f9ba9eb33ce96ebc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Amplitudes</topic><topic>Bistatic coherence</topic><topic>Coherence</topic><topic>Flooded areas</topic><topic>flooded vegetation</topic><topic>Flooding</topic><topic>Floodplains</topic><topic>Floods</topic><topic>Image acquisition</topic><topic>Image analysis</topic><topic>Image processing</topic><topic>Mapping</topic><topic>Monitoring</topic><topic>Mowing</topic><topic>Polarimetry</topic><topic>riparian wetland mapping</topic><topic>Rivers</topic><topic>Superhigh frequencies</topic><topic>Surface water</topic><topic>Synthetic aperture radar</topic><topic>TanDEM-X (TDX)</topic><topic>Temporal variations</topic><topic>Vegetation</topic><topic>Vegetation mapping</topic><topic>Wetlands</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mleczko, Magdalena</creatorcontrib><creatorcontrib>Mroz, Marek</creatorcontrib><creatorcontrib>Fitrzyk, Magdalena</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</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>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE journal of selected topics in applied earth observations and remote sensing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mleczko, Magdalena</au><au>Mroz, Marek</au><au>Fitrzyk, Magdalena</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Riparian Wetland Mapping and Inundation Monitoring Using Amplitude and Bistatic Coherence Data From the TanDEM-X Mission</atitle><jtitle>IEEE journal of selected topics in applied earth observations and remote sensing</jtitle><stitle>JSTARS</stitle><date>2021</date><risdate>2021</risdate><volume>14</volume><spage>2432</spage><epage>2444</epage><pages>2432-2444</pages><issn>1939-1404</issn><eissn>2151-1535</eissn><coden>IJSTHZ</coden><abstract>This article focuses on bistatic coherence as an additional feature complementing amplitudes in classification space, permitting to monitor temporal changes in water extent on the wetland comprising surface water and inundated vegetation. 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The bistatic coherence at X-band turned out to be really helpful in mapping high vegetation, which can be an indicator that this methodology can be directly used in the monitoring of common reed mowing or mapping highly invasive vegetation. Additionally, we could observe that short inundated vegetation was also mapped correctly, allowing flooded areas in this floodplain to be mapped with great precision throughout the growing season.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/JSTARS.2021.3054994</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0003-0929-4300</orcidid><orcidid>https://orcid.org/0000-0002-9932-1810</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Amplitudes Bistatic coherence Coherence Flooded areas flooded vegetation Flooding Floodplains Floods Image acquisition Image analysis Image processing Mapping Monitoring Mowing Polarimetry riparian wetland mapping Rivers Superhigh frequencies Surface water Synthetic aperture radar TanDEM-X (TDX) Temporal variations Vegetation Vegetation mapping Wetlands |
title | Riparian Wetland Mapping and Inundation Monitoring Using Amplitude and Bistatic Coherence Data From the TanDEM-X Mission |
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