Analyzing floating and bedfast lake ice regimes across Arctic Alaska using 25 years of space-borne SAR imagery
Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ice (BI) and when MIT is less than maximum water depth lakes have floating ice (FI). Both airborne radar and space-borne s...
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description | Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ice (BI) and when MIT is less than maximum water depth lakes have floating ice (FI). Both airborne radar and space-borne synthetic aperture radar (SAR) imagery (Ku-, X-, C-, and L-band) have been used previously to determine whether lakes have a BI or FI regime in a given year, across a number of years, or across large regions. In this study, we use a combination of ERS-1/2, RADARSAT-2, Envisat, and Sentinel-1 SAR imagery for seven lake-rich regions in Arctic Alaska to analyze lake ice regime extents and dynamics over a 25-year period (1992–2016). Our interactive threshold classification method determines a unique statistic-based intensity threshold for each SAR scene, allowing for the comparison of classification results from C-band SAR data acquired with different polarizations and incidence angles. Additionally, our novel method accommodates declining signal strength in aging extended-mission satellite SAR instruments. Comparison of SAR ice regime classifications with extensive field measurements from six years yielded a 93% accuracy. Significant declines in BI regimes were only observed in the Fish Creek area with 3% of lakes exhibiting transitional ice regimes—lakes that switch from BI to FI during this 25-year period. This analysis suggests that the potential conversion from BI to FI regimes is primarily a function of lake depth distributions in addition to regional differences in climate variability. Remote sensing of lake ice regimes with C-band SAR is a useful tool to monitor the associated thermal impacts on permafrost, since lake ice regimes can be used as a proxy for of sub-lake permafrost thaw, considered by the Global Climate Observing System as an Essential Climate Variable (ECV). Continued winter warming and variable snow conditions in the Arctic are expected and our long-term analysis provides a valuable baseline for predicting where potential future lake ice regimes shifts will be most pronounced.
•Results of a 25-year C-band SAR lake ice regime classification are presented.•Bedfast and floating lake ice regimes are cataloged in seven lake regions in Alaska.•Comparison of SAR results with extensive field measurements showed 93% accuracy.•A no-bias adaptive threshold method is presented as more appropriate than a single threshold.•There is a 25-year trend from bedf |
doi_str_mv | 10.1016/j.rse.2018.02.022 |
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•Results of a 25-year C-band SAR lake ice regime classification are presented.•Bedfast and floating lake ice regimes are cataloged in seven lake regions in Alaska.•Comparison of SAR results with extensive field measurements showed 93% accuracy.•A no-bias adaptive threshold method is presented as more appropriate than a single threshold.•There is a 25-year trend from bedfast to floating lake ice in one of the regions.</description><identifier>ISSN: 0034-4257</identifier><identifier>EISSN: 1879-0704</identifier><identifier>DOI: 10.1016/j.rse.2018.02.022</identifier><language>eng</language><publisher>New York: Elsevier Inc</publisher><subject>Aging ; Airborne radar ; Aperture ; Arctic lakes ; C band ; Classification ; Climate ; Climate variability ; Cryosphere ; Data acquisition ; Floating ice ; Glaciers ; Global climate ; Global warming ; Ice ; Ice cover ; Ice regime ; Ice thickness ; Icebergs ; Incidence angle ; Lake ice ; Lakes ; Overwinter fish habitat ; Permafrost ; Permafrost thaw ; Polar environments ; Radar ; Radar imaging ; Radarsat ; Remote sensing ; Satellite-borne instruments ; Satellites ; Signal strength ; Synthetic aperture radar ; Thermokarst lakes ; Water depth ; Water supply ; Winter ; Winter water supply</subject><ispartof>Remote sensing of environment, 2018-05, Vol.209, p.660-676</ispartof><rights>2018 The Authors</rights><rights>Copyright Elsevier BV May 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c368t-dd8932fba629e5bd001fed3dfcef1bd218e6677ea6f454358d01105fb019ef983</citedby><cites>FETCH-LOGICAL-c368t-dd8932fba629e5bd001fed3dfcef1bd218e6677ea6f454358d01105fb019ef983</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.rse.2018.02.022$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Engram, Melanie</creatorcontrib><creatorcontrib>Arp, Christopher D.</creatorcontrib><creatorcontrib>Jones, Benjamin M.</creatorcontrib><creatorcontrib>Ajadi, Olaniyi A.</creatorcontrib><creatorcontrib>Meyer, Franz J.</creatorcontrib><title>Analyzing floating and bedfast lake ice regimes across Arctic Alaska using 25 years of space-borne SAR imagery</title><title>Remote sensing of environment</title><description>Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ice (BI) and when MIT is less than maximum water depth lakes have floating ice (FI). Both airborne radar and space-borne synthetic aperture radar (SAR) imagery (Ku-, X-, C-, and L-band) have been used previously to determine whether lakes have a BI or FI regime in a given year, across a number of years, or across large regions. In this study, we use a combination of ERS-1/2, RADARSAT-2, Envisat, and Sentinel-1 SAR imagery for seven lake-rich regions in Arctic Alaska to analyze lake ice regime extents and dynamics over a 25-year period (1992–2016). Our interactive threshold classification method determines a unique statistic-based intensity threshold for each SAR scene, allowing for the comparison of classification results from C-band SAR data acquired with different polarizations and incidence angles. Additionally, our novel method accommodates declining signal strength in aging extended-mission satellite SAR instruments. Comparison of SAR ice regime classifications with extensive field measurements from six years yielded a 93% accuracy. Significant declines in BI regimes were only observed in the Fish Creek area with 3% of lakes exhibiting transitional ice regimes—lakes that switch from BI to FI during this 25-year period. This analysis suggests that the potential conversion from BI to FI regimes is primarily a function of lake depth distributions in addition to regional differences in climate variability. Remote sensing of lake ice regimes with C-band SAR is a useful tool to monitor the associated thermal impacts on permafrost, since lake ice regimes can be used as a proxy for of sub-lake permafrost thaw, considered by the Global Climate Observing System as an Essential Climate Variable (ECV). Continued winter warming and variable snow conditions in the Arctic are expected and our long-term analysis provides a valuable baseline for predicting where potential future lake ice regimes shifts will be most pronounced.
•Results of a 25-year C-band SAR lake ice regime classification are presented.•Bedfast and floating lake ice regimes are cataloged in seven lake regions in Alaska.•Comparison of SAR results with extensive field measurements showed 93% accuracy.•A no-bias adaptive threshold method is presented as more appropriate than a single threshold.•There is a 25-year trend from bedfast to floating lake ice in one of the regions.</description><subject>Aging</subject><subject>Airborne radar</subject><subject>Aperture</subject><subject>Arctic lakes</subject><subject>C band</subject><subject>Classification</subject><subject>Climate</subject><subject>Climate variability</subject><subject>Cryosphere</subject><subject>Data acquisition</subject><subject>Floating ice</subject><subject>Glaciers</subject><subject>Global climate</subject><subject>Global warming</subject><subject>Ice</subject><subject>Ice cover</subject><subject>Ice regime</subject><subject>Ice thickness</subject><subject>Icebergs</subject><subject>Incidence angle</subject><subject>Lake ice</subject><subject>Lakes</subject><subject>Overwinter fish habitat</subject><subject>Permafrost</subject><subject>Permafrost thaw</subject><subject>Polar environments</subject><subject>Radar</subject><subject>Radar imaging</subject><subject>Radarsat</subject><subject>Remote sensing</subject><subject>Satellite-borne instruments</subject><subject>Satellites</subject><subject>Signal strength</subject><subject>Synthetic aperture radar</subject><subject>Thermokarst lakes</subject><subject>Water depth</subject><subject>Water supply</subject><subject>Winter</subject><subject>Winter water supply</subject><issn>0034-4257</issn><issn>1879-0704</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kM1KxDAUhYMoOI4-gLuA69Yk_UtxVcQ_GBD8WYc0uRnS6bQ16Qh15Rv5Tj6JqeNauHDv4nyXcw5C55TElND8somdh5gRymPCwrADtKC8KCNSkPQQLQhJ0ihlWXGMTrxvCKEZL-gCDVUn2-nDdmts2l6O8yE7jWvQRvoRt3ID2CrADtZ2Cx5L5XrvceXUaBWuWuk3Eu_8zLHs-_NrAuk87g32g1QQ1b3rAD9XT9hu5RrcdIqOjGw9nP3tJXq9vXm5vo9Wj3cP19UqUknOx0hrXibM1DJnJWS1DoYN6EQbBYbWmlEOeV4UIHOTZmmScU0oJZmpCS3BlDxZoov938H1bzvwo2j6nQthvWChk5IVPKdBRfeq31QOjBhcMOomQYmYixWNCMWKuVhBWBgWmKs9A8H-uwUnvLLQKdDWgRqF7u0_9A-Lp4JF</recordid><startdate>201805</startdate><enddate>201805</enddate><creator>Engram, Melanie</creator><creator>Arp, Christopher D.</creator><creator>Jones, Benjamin M.</creator><creator>Ajadi, Olaniyi A.</creator><creator>Meyer, Franz J.</creator><general>Elsevier Inc</general><general>Elsevier BV</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SN</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TG</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KL.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope></search><sort><creationdate>201805</creationdate><title>Analyzing floating and bedfast lake ice regimes across Arctic Alaska using 25 years of space-borne SAR imagery</title><author>Engram, Melanie ; Arp, Christopher D. ; Jones, Benjamin M. ; Ajadi, Olaniyi A. ; Meyer, Franz J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-dd8932fba629e5bd001fed3dfcef1bd218e6677ea6f454358d01105fb019ef983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Aging</topic><topic>Airborne radar</topic><topic>Aperture</topic><topic>Arctic lakes</topic><topic>C band</topic><topic>Classification</topic><topic>Climate</topic><topic>Climate variability</topic><topic>Cryosphere</topic><topic>Data acquisition</topic><topic>Floating ice</topic><topic>Glaciers</topic><topic>Global climate</topic><topic>Global warming</topic><topic>Ice</topic><topic>Ice cover</topic><topic>Ice regime</topic><topic>Ice thickness</topic><topic>Icebergs</topic><topic>Incidence angle</topic><topic>Lake ice</topic><topic>Lakes</topic><topic>Overwinter fish habitat</topic><topic>Permafrost</topic><topic>Permafrost thaw</topic><topic>Polar environments</topic><topic>Radar</topic><topic>Radar imaging</topic><topic>Radarsat</topic><topic>Remote sensing</topic><topic>Satellite-borne instruments</topic><topic>Satellites</topic><topic>Signal strength</topic><topic>Synthetic aperture radar</topic><topic>Thermokarst lakes</topic><topic>Water depth</topic><topic>Water supply</topic><topic>Winter</topic><topic>Winter water supply</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Engram, Melanie</creatorcontrib><creatorcontrib>Arp, Christopher D.</creatorcontrib><creatorcontrib>Jones, Benjamin M.</creatorcontrib><creatorcontrib>Ajadi, Olaniyi A.</creatorcontrib><creatorcontrib>Meyer, Franz J.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Ecology Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</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>Biotechnology and BioEngineering Abstracts</collection><jtitle>Remote sensing of environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Engram, Melanie</au><au>Arp, Christopher D.</au><au>Jones, Benjamin M.</au><au>Ajadi, Olaniyi A.</au><au>Meyer, Franz J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Analyzing floating and bedfast lake ice regimes across Arctic Alaska using 25 years of space-borne SAR imagery</atitle><jtitle>Remote sensing of environment</jtitle><date>2018-05</date><risdate>2018</risdate><volume>209</volume><spage>660</spage><epage>676</epage><pages>660-676</pages><issn>0034-4257</issn><eissn>1879-0704</eissn><abstract>Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ice (BI) and when MIT is less than maximum water depth lakes have floating ice (FI). Both airborne radar and space-borne synthetic aperture radar (SAR) imagery (Ku-, X-, C-, and L-band) have been used previously to determine whether lakes have a BI or FI regime in a given year, across a number of years, or across large regions. In this study, we use a combination of ERS-1/2, RADARSAT-2, Envisat, and Sentinel-1 SAR imagery for seven lake-rich regions in Arctic Alaska to analyze lake ice regime extents and dynamics over a 25-year period (1992–2016). Our interactive threshold classification method determines a unique statistic-based intensity threshold for each SAR scene, allowing for the comparison of classification results from C-band SAR data acquired with different polarizations and incidence angles. Additionally, our novel method accommodates declining signal strength in aging extended-mission satellite SAR instruments. Comparison of SAR ice regime classifications with extensive field measurements from six years yielded a 93% accuracy. Significant declines in BI regimes were only observed in the Fish Creek area with 3% of lakes exhibiting transitional ice regimes—lakes that switch from BI to FI during this 25-year period. This analysis suggests that the potential conversion from BI to FI regimes is primarily a function of lake depth distributions in addition to regional differences in climate variability. Remote sensing of lake ice regimes with C-band SAR is a useful tool to monitor the associated thermal impacts on permafrost, since lake ice regimes can be used as a proxy for of sub-lake permafrost thaw, considered by the Global Climate Observing System as an Essential Climate Variable (ECV). Continued winter warming and variable snow conditions in the Arctic are expected and our long-term analysis provides a valuable baseline for predicting where potential future lake ice regimes shifts will be most pronounced.
•Results of a 25-year C-band SAR lake ice regime classification are presented.•Bedfast and floating lake ice regimes are cataloged in seven lake regions in Alaska.•Comparison of SAR results with extensive field measurements showed 93% accuracy.•A no-bias adaptive threshold method is presented as more appropriate than a single threshold.•There is a 25-year trend from bedfast to floating lake ice in one of the regions.</abstract><cop>New York</cop><pub>Elsevier Inc</pub><doi>10.1016/j.rse.2018.02.022</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aging Airborne radar Aperture Arctic lakes C band Classification Climate Climate variability Cryosphere Data acquisition Floating ice Glaciers Global climate Global warming Ice Ice cover Ice regime Ice thickness Icebergs Incidence angle Lake ice Lakes Overwinter fish habitat Permafrost Permafrost thaw Polar environments Radar Radar imaging Radarsat Remote sensing Satellite-borne instruments Satellites Signal strength Synthetic aperture radar Thermokarst lakes Water depth Water supply Winter Winter water supply |
title | Analyzing floating and bedfast lake ice regimes across Arctic Alaska using 25 years of space-borne SAR imagery |
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