{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T03:59:37Z","timestamp":1777435177252,"version":"3.51.4"},"reference-count":14,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2012,4,25]],"date-time":"2012-04-25T00:00:00Z","timestamp":1335312000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In this study, daily maps of snow cover distribution and sea ice extent produced by NOAA\u2019s interactive multisensor snow and ice mapping system (IMS) were validated using in situ snow depth data from observing stations obtained from NOAA\u2019s National Climatic Data Center (NCDC) for calendar years 2006 to 2010. IMS provides daily maps of snow and sea ice extent within the Northern Hemisphere using data from combination of geostationary and polar orbiting satellites in visible, infrared and microwave spectrums. Statistical correspondence between the IMS and in situ point measurements has been evaluated assuming that ground measurements are discrete and continuously distributed over a 4 km IMS snow cover maps. Advanced Very High Resolution Radiometer (AVHRR) land and snow classification data are supplemental datasets used in the further analysis of correspondence between the IMS product and in situ measurements. The comparison of IMS maps with in situ snow observations conducted over a period of four years has demonstrated a good correspondence of the data sets. The daily rate of agreement between the products mostly ranges between 80% and 90% during the Northern Hemisphere through the winter seasons when about a quarter to one third of the territory of continental US is covered with snow. Further, better agreement was observed for stations recording higher snow depth. The uncertainties in validation of IMS snow product with stationed NCDC data were discussed.<\/jats:p>","DOI":"10.3390\/rs4051134","type":"journal-article","created":{"date-parts":[[2012,4,25]],"date-time":"2012-04-25T11:42:51Z","timestamp":1335354171000},"page":"1134-1145","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Validation of NOAA-Interactive Multisensor Snow and Ice Mapping System (IMS) by Comparison with Ground-Based Measurements over Continental United States"],"prefix":"10.3390","volume":"4","author":[{"given":"Christine","family":"Chen","sequence":"first","affiliation":[{"name":"NOAA-Cooperative Remote Sensing and Technology Center (NOAA-CREST), New York, NY 10031, USA"},{"name":"Byrd Polar Research Center, The Ohio State University, Columbus, OH 43210, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tarendra","family":"Lakhankar","sequence":"additional","affiliation":[{"name":"NOAA-Cooperative Remote Sensing and Technology Center (NOAA-CREST), New York, NY 10031, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Romanov","sequence":"additional","affiliation":[{"name":"NOAA-Cooperative Remote Sensing and Technology Center (NOAA-CREST), New York, NY 10031, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sean","family":"Helfrich","sequence":"additional","affiliation":[{"name":"National Ice Center, NOAA, Washington, DC 20395, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Al","family":"Powell","sequence":"additional","affiliation":[{"name":"Center for Satellite Application and Research, NOAA, Washington, DC 20395, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Reza","family":"Khanbilvardi","sequence":"additional","affiliation":[{"name":"NOAA-Cooperative Remote Sensing and Technology Center (NOAA-CREST), New York, NY 10031, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2012,4,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1080\/02626669609491521","article-title":"Spaceborne remote sensing for snow hydrology applications","volume":"41","author":"Rango","year":"1996","journal-title":"Hydrol. 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Climate"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/4\/5\/1134\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:49:58Z","timestamp":1760219398000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/4\/5\/1134"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,4,25]]},"references-count":14,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2012,5]]}},"alternative-id":["rs4051134"],"URL":"https:\/\/doi.org\/10.3390\/rs4051134","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,4,25]]}}}