乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T05:55:55Z","timestamp":1725429355258},"reference-count":33,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T00:00:00Z","timestamp":1496275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["BO1228\/13-1","DE2174\/3-1"],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Open water areas surrounded by sea ice significantly influence the ocean-ice-atmosphere interaction and contribute to Arctic climate change. Satellite altimetry can detect these ice openings and enables one to estimate sea surface heights and further altimetry data derived products. This study introduces an innovative, unsupervised classification approach for detecting open water areas in the Greenland Sea based on high-frequency data from Envisat and SARAL. Altimetry radar echoes, also called waveforms, are analyzed regarding different surface conditions. Six waveform features are defined to cluster radar echoes into different groups indicating open water and sea ice waveforms. Therefore, the partitional clustering algorithm K-medoids and the memory-based classification method K-nearest neighbor are employed, yielding an internal misclassification error of about 2%. A quantitative comparison with several SAR images reveals a consistency rate of 76.9% for SARAL and 70.7% for Envisat. These numbers strongly depend on the quality of the SAR images and the time lag between the measurements of both techniques. For a few examples, a consistency rate of more than 90% and a true water detection rate of 94% can be demonstrated. The innovative classification procedure can be used to detect water areas with different spatial extents and can be applied to all available pulse-limited altimetry datasets.<\/jats:p>","DOI":"10.3390\/rs9060551","type":"journal-article","created":{"date-parts":[[2017,6,1]],"date-time":"2017-06-01T14:36:36Z","timestamp":1496327796000},"page":"551","source":"Crossref","is-referenced-by-count":21,"title":["Monitoring the Arctic Seas: How Satellite Altimetry Can Be Used to Detect Open Water in Sea-Ice Regions"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-4219-0407","authenticated-orcid":false,"given":"Felix","family":"M\u00fcller","sequence":"first","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinstitut, Technische Universit\u00e4t M\u00fcnchen, Arcisstra\u00dfe 21, 80333 Munich, Germany"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-8940-4639","authenticated-orcid":false,"given":"Denise","family":"Dettmering","sequence":"additional","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinstitut, Technische Universit\u00e4t M\u00fcnchen, Arcisstra\u00dfe 21, 80333 Munich, Germany"}]},{"given":"Wolfgang","family":"Bosch","sequence":"additional","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinstitut, Technische Universit\u00e4t M\u00fcnchen, Arcisstra\u00dfe 21, 80333 Munich, Germany"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-0718-6069","authenticated-orcid":false,"given":"Florian","family":"Seitz","sequence":"additional","affiliation":[{"name":"Deutsches Geod\u00e4tisches Forschungsinstitut, Technische Universit\u00e4t M\u00fcnchen, Arcisstra\u00dfe 21, 80333 Munich, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2017,6,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Comiso, J. (2010). Polar Oceans from Space, Atmospheric and Oceanographic Sciences Library, Springer.","DOI":"10.1007\/978-0-387-68300-3"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1216","DOI":"10.1002\/2013GL058951","article-title":"Changes in Arctic melt season and implications for sea ice loss","volume":"41","author":"Stroeve","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"L17605","DOI":"10.1029\/2005GL023740","article-title":"One more step toward a warmer Arctic","volume":"32","author":"Polyakov","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.epsl.2012.03.033","article-title":"Timing and origin of recent regional ice-mass loss in Greenland","volume":"333\u2013334","author":"Sasgen","year":"2012","journal-title":"Earth Planet. Sci. Lett."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1080\/01431169408954124","article-title":"Sea-Ice Altimeter Processing Scheme at the EODC","volume":"15","author":"Laxon","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Rio, M.H., and Hernandez, F. (2004). A mean dynamic topography computed over the world ocean from altimetry, in situ measurements, and a geoid model. J. Geophys. Res. Oceans, 109.","DOI":"10.1029\/2003JC002226"},{"key":"ref_7","unstructured":"Dwyer, R., and Godin, R. (1980). Determining Sea-Ice Boundaries and Ice Roughness Using GEOS-3 Altimeter Data, Technical Report."},{"key":"ref_8","unstructured":"Fetterer, F.M., Drinkwater, M.R., Jezek, K.C., Laxon, S.W.C., Onstott, R.G., and Ulander, L.M.H. (2013). Sea Ice Altimetry. Microwave Remote Sensing of Sea Ice, American Geophysical Union."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"947","DOI":"10.1038\/nature02050","article-title":"High interannual variability of sea ice thickness in the Arctic region","volume":"425","author":"Laxon","year":"2003","journal-title":"Nature"},{"key":"ref_10","first-page":"C07001","article-title":"Sea surface height determination in the Arctic Ocean from ERS altimetry","volume":"109","author":"Peacock","year":"2004","journal-title":"J. Geophys. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1016\/j.rse.2008.10.015","article-title":"Comparison of Envisat radar and airborne laser altimeter measurements over Arctic sea ice","volume":"113","author":"Connor","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1080\/01490419.2015.1019655","article-title":"Sea Ice Leads Detection Using SARAL\/AltiKa Altimeter","volume":"38","author":"Zakharova","year":"2015","journal-title":"Mar. Geod."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1315","DOI":"10.5194\/tc-7-1315-2013","article-title":"Waveform classification of airborne synthetic aperture radar altimeter over Arctic sea ice","volume":"7","author":"Zygmuntowska","year":"2013","journal-title":"Cryosphere"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Passaro, M., M\u00fcller, F.L., and Dettmering, D. (2017). Lead Detection using Cryosat-2 Delay-Doppler Processing and Sentinel-1 SAR images. Adv. Space Res., under review.","DOI":"10.1016\/j.asr.2017.07.011"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1016\/S0967-0645(99)00015-6","article-title":"The Arctic Circumpolar Boundary Current","volume":"46","author":"Rudels","year":"1999","journal-title":"Deep-Sea Res. Part II"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Serreze, M., and Barry, R. (2014). The Arctic Climate System, Cambridge University Press.","DOI":"10.1017\/CBO9781139583817"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1583","DOI":"10.1016\/0967-0637(95)00071-D","article-title":"On the circulation of the northeastern North Atlantic","volume":"42","author":"Bersch","year":"1995","journal-title":"Deep-Sea Res. Part II"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"18059","DOI":"10.1029\/1999JC900146","article-title":"Structure and transports of the East Greenland Current at 75\u2218N from moored current meters","volume":"104","author":"Woodgate","year":"1999","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1080\/01490419.2014.1000471","article-title":"The SARAL\/AltiKa Altimetry Satellite Mission","volume":"38","author":"Verron","year":"2015","journal-title":"Mar. Geod."},{"key":"ref_20","unstructured":"Japan Aerospace Exploration Agency (JAXA) (2008). ALOS Data Users Handbook, Revision C, Japan Aerospace Exploration Agency."},{"key":"ref_21","unstructured":"MDA (2016). RADARSAT-2 Product Description, MacDonald, Dettwiler and Associates Ltd.. Report RN-SP-52-1238, Issue 1\/13."},{"key":"ref_22","unstructured":"Sentinel-1 Team (2013). Sentinel-1 User Handbook, European Space Agency. GMES-S1OP-EOPG-TN-13-0001, Issue Draft."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Dierking, W. (2013). Sea Ice Monitoring by Synthetic Aperture Radar. Oceanography, 26.","DOI":"10.5670\/oceanog.2013.33"},{"key":"ref_24","unstructured":"Jackson, C.R., and Apel, J.R. (2004). Synthetic Aperture Radar: Marine User\u2019s Manual."},{"key":"ref_25","unstructured":"Tschudi, M., Fowler, C., Maslanik, J., and Stewart, J.S. (2016). Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, Version 3, National Snow and Ice Data Center. Subset: Greenland Sea, Date Accessed: 16.11.2016."},{"key":"ref_26","unstructured":"Cavalieri, D., Parkinson, C., Gloersen, P., and Zwally, J.H. (1996). Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM\/I-SSMIS Passive Microwave Data, Version 1, Subset: Greenland Sea, Date Accessed: 16.11.2016."},{"key":"ref_27","unstructured":"Xu, R., and Wunsch, D.C. (2009). Clustering, Wiley. IEEE Press Series on Computational Intelligence."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., and Friedman, J. (2009). The Elements of Statistical Learning, Springer.","DOI":"10.1007\/978-0-387-84858-7"},{"key":"ref_29","unstructured":"Kohonen, T. (2012). Self-Organizing Maps, Springer."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Celebi, M. (2014). Partitional Clustering Algorithms, EBL-Schweitzer, Springer International Publishing.","DOI":"10.1007\/978-3-319-09259-1"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Kaufman, L., and Rousseeuw, P.J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis, Wiley.","DOI":"10.1002\/9780470316801"},{"key":"ref_32","unstructured":"Kvingedal, B. (2013). Sea-Ice Extent and Variability in the Nordic Seas, 1967\u20132002. The Nordic Seas: An Integrated Perspective, American Geophysical Union."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"G\u00f6ttl, F., Dettmering, D., M\u00fcller, F.L., and Schwatke, C. (2016). Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification. Remote Sens., 8.","DOI":"10.3390\/rs8110885"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/6\/551\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,7]],"date-time":"2024-06-07T19:01:46Z","timestamp":1717786906000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/6\/551"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6,1]]},"references-count":33,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2017,6]]}},"alternative-id":["rs9060551"],"URL":"https:\/\/doi.org\/10.3390\/rs9060551","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,6,1]]}}}