Correction of Atmospheric Phase Screen in Time Series InSAR Using WRF Model for Monitoring Volcanic Activities
One of the main limitations in measuring ground deformation using synthetic aperture radar interferometry (InSAR) is atmospheric phase delay effects. In volcanic regions, the atmospheric phase delay effects can cause serious problems in detecting volcanic unrest because atmospheric thickness is inve...
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Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2014-05, Vol.52 (5), p.2678-2689 |
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description | One of the main limitations in measuring ground deformation using synthetic aperture radar interferometry (InSAR) is atmospheric phase delay effects. In volcanic regions, the atmospheric phase delay effects can cause serious problems in detecting volcanic unrest because atmospheric thickness is inversely related with the elevation of a volcanic mountain. It is commonly known that the atmospheric phase screen (APS) can be decomposed spatially into stratified and turbulent components. In this paper, the stratified and turbulent atmospheric conditions of a volcanic area were simulated using weather research and forecasting (WRF) model, and the simulated atmospheric conditions were compared with in situ radiosonde data. The comparison results proved that the stratified APS from the WRF model could reflect the reasonable patterns of seasonal changes and vertical profiles with dependable quality. We also found that the stratified APS was significantly correlated with time and sometimes severely contaminated the quality of volcanic deformation estimation. These results indicate that the temporal high-pass (HP) filtering, which has been usually applied in time series InSAR analysis for extracting and removing APS, cannot work properly in volcanic area. Thus, we propose a new method that employs the stratified APS obtained from the WRF model by correlating with topography and the (residual) turbulent APS that can be effectively eliminated by temporal HP filtering in persistent scatterer interferometry (PSI). We applied the proposed method (atmosphere-corrected PSI) to Advanced Land Observing Satellite Phased Array type L-band SAR data that cover Shinmoedake volcano, Japan, and found that the estimated surface deformation and APS agreed well with those measured from GPS and Moderate-Resolution Imaging Spectroradiometer data, respectively. |
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In volcanic regions, the atmospheric phase delay effects can cause serious problems in detecting volcanic unrest because atmospheric thickness is inversely related with the elevation of a volcanic mountain. It is commonly known that the atmospheric phase screen (APS) can be decomposed spatially into stratified and turbulent components. In this paper, the stratified and turbulent atmospheric conditions of a volcanic area were simulated using weather research and forecasting (WRF) model, and the simulated atmospheric conditions were compared with in situ radiosonde data. The comparison results proved that the stratified APS from the WRF model could reflect the reasonable patterns of seasonal changes and vertical profiles with dependable quality. We also found that the stratified APS was significantly correlated with time and sometimes severely contaminated the quality of volcanic deformation estimation. These results indicate that the temporal high-pass (HP) filtering, which has been usually applied in time series InSAR analysis for extracting and removing APS, cannot work properly in volcanic area. Thus, we propose a new method that employs the stratified APS obtained from the WRF model by correlating with topography and the (residual) turbulent APS that can be effectively eliminated by temporal HP filtering in persistent scatterer interferometry (PSI). We applied the proposed method (atmosphere-corrected PSI) to Advanced Land Observing Satellite Phased Array type L-band SAR data that cover Shinmoedake volcano, Japan, and found that the estimated surface deformation and APS agreed well with those measured from GPS and Moderate-Resolution Imaging Spectroradiometer data, respectively.</description><identifier>ISSN: 0196-2892</identifier><identifier>EISSN: 1558-0644</identifier><identifier>DOI: 10.1109/TGRS.2013.2264532</identifier><identifier>CODEN: IGRSD2</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Applied geophysics ; Atmospheric measurements ; Atmospheric modeling ; Atmospheric phase screen (APS) ; Atmospherics ; Computational fluid dynamics ; Data models ; Deformation ; Delays ; Earth sciences ; Earth, ocean, space ; Exact sciences and technology ; Filtering ; Interferometry ; Internal geophysics ; Mathematical models ; Meteorology ; Predictive models ; Strain ; stratified APS ; Synthetic aperture radar ; Time series ; time series interferometric synthetic aperture radar (InSAR) ; Turbulence ; volcano ; weather research and forecasting (WRF)</subject><ispartof>IEEE transactions on geoscience and remote sensing, 2014-05, Vol.52 (5), p.2678-2689</ispartof><rights>2015 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) May 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c432t-e8df13d4f017d4e693ff3a59179c664f3de7923e16462fb5d5d6195b5009dfbf3</citedby><cites>FETCH-LOGICAL-c432t-e8df13d4f017d4e693ff3a59179c664f3de7923e16462fb5d5d6195b5009dfbf3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6547675$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54737</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28496104$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Jung, Jungkyo</creatorcontrib><creatorcontrib>Kim, Duk-jin</creatorcontrib><creatorcontrib>Park, Sang-Eun</creatorcontrib><title>Correction of Atmospheric Phase Screen in Time Series InSAR Using WRF Model for Monitoring Volcanic Activities</title><title>IEEE transactions on geoscience and remote sensing</title><addtitle>TGRS</addtitle><description>One of the main limitations in measuring ground deformation using synthetic aperture radar interferometry (InSAR) is atmospheric phase delay effects. In volcanic regions, the atmospheric phase delay effects can cause serious problems in detecting volcanic unrest because atmospheric thickness is inversely related with the elevation of a volcanic mountain. It is commonly known that the atmospheric phase screen (APS) can be decomposed spatially into stratified and turbulent components. In this paper, the stratified and turbulent atmospheric conditions of a volcanic area were simulated using weather research and forecasting (WRF) model, and the simulated atmospheric conditions were compared with in situ radiosonde data. The comparison results proved that the stratified APS from the WRF model could reflect the reasonable patterns of seasonal changes and vertical profiles with dependable quality. We also found that the stratified APS was significantly correlated with time and sometimes severely contaminated the quality of volcanic deformation estimation. These results indicate that the temporal high-pass (HP) filtering, which has been usually applied in time series InSAR analysis for extracting and removing APS, cannot work properly in volcanic area. Thus, we propose a new method that employs the stratified APS obtained from the WRF model by correlating with topography and the (residual) turbulent APS that can be effectively eliminated by temporal HP filtering in persistent scatterer interferometry (PSI). We applied the proposed method (atmosphere-corrected PSI) to Advanced Land Observing Satellite Phased Array type L-band SAR data that cover Shinmoedake volcano, Japan, and found that the estimated surface deformation and APS agreed well with those measured from GPS and Moderate-Resolution Imaging Spectroradiometer data, respectively.</description><subject>Applied geophysics</subject><subject>Atmospheric measurements</subject><subject>Atmospheric modeling</subject><subject>Atmospheric phase screen (APS)</subject><subject>Atmospherics</subject><subject>Computational fluid dynamics</subject><subject>Data models</subject><subject>Deformation</subject><subject>Delays</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>Filtering</subject><subject>Interferometry</subject><subject>Internal geophysics</subject><subject>Mathematical models</subject><subject>Meteorology</subject><subject>Predictive models</subject><subject>Strain</subject><subject>stratified APS</subject><subject>Synthetic aperture radar</subject><subject>Time series</subject><subject>time series interferometric synthetic aperture radar (InSAR)</subject><subject>Turbulence</subject><subject>volcano</subject><subject>weather research and forecasting (WRF)</subject><issn>0196-2892</issn><issn>1558-0644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><recordid>eNqFkU9rGzEQxUVpoW7aD1B6EZRCL-tq9Hd1NCZJAwkpttMel7V21CisJVdaF_rtK2OTQy89zQzv9x4Mj5D3wOYAzH7ZXK_Wc85AzDnXUgn-gsxAqbZhWsqXZMbA6oa3lr8mb0p5YgykAjMjcZlyRjeFFGnydDHtUtk_Yg6OfnvsC9K1y4iRhkg3YVfPKmGhN3G9WNGHEuJP-mN1Re_SgCP1Kdcthinlo_A9ja6PNWlR83-HqRrfkle-Hwu-O88L8nB1uVl-bW7vr2-Wi9vGScGnBtvBgxikZ2AGidoK70WvLBjrtJZeDGgsFwhaau63alCDBqu2ijE7-K0XF-TzKXef068DlqnbheJwHPuI6VA6MIYJsEbA_1ElQXKubFvRj_-gT-mQY32kUsAlgJG2UnCiXE6lZPTdPoddn_90wLpjWd2xrO5YVncuq3o-nZP74vrR5z66UJ6NvJVWA5OV-3DiAiI-y1pJo40SfwEYL5up</recordid><startdate>20140501</startdate><enddate>20140501</enddate><creator>Jung, Jungkyo</creator><creator>Kim, Duk-jin</creator><creator>Park, Sang-Eun</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</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>IQODW</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>7SP</scope><scope>F28</scope></search><sort><creationdate>20140501</creationdate><title>Correction of Atmospheric Phase Screen in Time Series InSAR Using WRF Model for Monitoring Volcanic Activities</title><author>Jung, Jungkyo ; Kim, Duk-jin ; Park, Sang-Eun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c432t-e8df13d4f017d4e693ff3a59179c664f3de7923e16462fb5d5d6195b5009dfbf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Applied geophysics</topic><topic>Atmospheric measurements</topic><topic>Atmospheric modeling</topic><topic>Atmospheric phase screen (APS)</topic><topic>Atmospherics</topic><topic>Computational fluid dynamics</topic><topic>Data models</topic><topic>Deformation</topic><topic>Delays</topic><topic>Earth sciences</topic><topic>Earth, ocean, space</topic><topic>Exact sciences and technology</topic><topic>Filtering</topic><topic>Interferometry</topic><topic>Internal geophysics</topic><topic>Mathematical models</topic><topic>Meteorology</topic><topic>Predictive models</topic><topic>Strain</topic><topic>stratified APS</topic><topic>Synthetic aperture radar</topic><topic>Time series</topic><topic>time series interferometric synthetic aperture radar (InSAR)</topic><topic>Turbulence</topic><topic>volcano</topic><topic>weather research and forecasting (WRF)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jung, Jungkyo</creatorcontrib><creatorcontrib>Kim, Duk-jin</creatorcontrib><creatorcontrib>Park, Sang-Eun</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>Pascal-Francis</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>Electronics & Communications Abstracts</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>IEEE transactions on geoscience and remote sensing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jung, Jungkyo</au><au>Kim, Duk-jin</au><au>Park, Sang-Eun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Correction of Atmospheric Phase Screen in Time Series InSAR Using WRF Model for Monitoring Volcanic Activities</atitle><jtitle>IEEE transactions on geoscience and remote sensing</jtitle><stitle>TGRS</stitle><date>2014-05-01</date><risdate>2014</risdate><volume>52</volume><issue>5</issue><spage>2678</spage><epage>2689</epage><pages>2678-2689</pages><issn>0196-2892</issn><eissn>1558-0644</eissn><coden>IGRSD2</coden><abstract>One of the main limitations in measuring ground deformation using synthetic aperture radar interferometry (InSAR) is atmospheric phase delay effects. In volcanic regions, the atmospheric phase delay effects can cause serious problems in detecting volcanic unrest because atmospheric thickness is inversely related with the elevation of a volcanic mountain. It is commonly known that the atmospheric phase screen (APS) can be decomposed spatially into stratified and turbulent components. In this paper, the stratified and turbulent atmospheric conditions of a volcanic area were simulated using weather research and forecasting (WRF) model, and the simulated atmospheric conditions were compared with in situ radiosonde data. The comparison results proved that the stratified APS from the WRF model could reflect the reasonable patterns of seasonal changes and vertical profiles with dependable quality. We also found that the stratified APS was significantly correlated with time and sometimes severely contaminated the quality of volcanic deformation estimation. These results indicate that the temporal high-pass (HP) filtering, which has been usually applied in time series InSAR analysis for extracting and removing APS, cannot work properly in volcanic area. Thus, we propose a new method that employs the stratified APS obtained from the WRF model by correlating with topography and the (residual) turbulent APS that can be effectively eliminated by temporal HP filtering in persistent scatterer interferometry (PSI). We applied the proposed method (atmosphere-corrected PSI) to Advanced Land Observing Satellite Phased Array type L-band SAR data that cover Shinmoedake volcano, Japan, and found that the estimated surface deformation and APS agreed well with those measured from GPS and Moderate-Resolution Imaging Spectroradiometer data, respectively.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TGRS.2013.2264532</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Applied geophysics Atmospheric measurements Atmospheric modeling Atmospheric phase screen (APS) Atmospherics Computational fluid dynamics Data models Deformation Delays Earth sciences Earth, ocean, space Exact sciences and technology Filtering Interferometry Internal geophysics Mathematical models Meteorology Predictive models Strain stratified APS Synthetic aperture radar Time series time series interferometric synthetic aperture radar (InSAR) Turbulence volcano weather research and forecasting (WRF) |
title | Correction of Atmospheric Phase Screen in Time Series InSAR Using WRF Model for Monitoring Volcanic Activities |
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