{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T11:23:37Z","timestamp":1761218617526,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T00:00:00Z","timestamp":1698019200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000104","name":"NASA\/AMES Research Cooperative Agreement","doi-asserted-by":"publisher","award":["NASA-NNX12AD05A","CFDA No. 43.001"],"award-info":[{"award-number":["NASA-NNX12AD05A","CFDA No. 43.001"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Bay Area Environmental Research Institute","award":["NASA-NNX12AD05A","CFDA No. 43.001"],"award-info":[{"award-number":["NASA-NNX12AD05A","CFDA No. 43.001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Snow parameters have traditionally been retrieved using discontinuous, multi-band sensors; however, continuous hyperspectral sensors are now being developed as an alternative. In this paper, we investigate the performance of various sensor configurations using machine learning neural networks trained on a simulated dataset. Our results show improvements in the accuracy of retrievals of snow grain size and impurity concentration for continuous hyperspectral channel configurations. Retrieval accuracy of snow albedo was found to be similar for all channel configurations.<\/jats:p>","DOI":"10.3390\/a16100493","type":"journal-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T05:54:35Z","timestamp":1698040475000},"page":"493","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Remote Sensing of Snow Parameters: A Sensitivity Study of Retrieval Performance Based on Hyperspectral versus Multispectral Data"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-5381-1302","authenticated-orcid":false,"given":"Elliot","family":"Pachniak","sequence":"first","affiliation":[{"name":"Light and Life Laboratory, Physics Department, Stevens Institute of Technology, Hoboken, NJ 07030, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Li","sequence":"additional","affiliation":[{"name":"Light and Life Laboratory, Physics Department, Stevens Institute of Technology, Hoboken, NJ 07030, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8516-6514","authenticated-orcid":false,"given":"Tomonori","family":"Tanikawa","sequence":"additional","affiliation":[{"name":"Meteorological Research Institute, Japan Meteorological Agency, Tsukuba 3050052, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9261-2239","authenticated-orcid":false,"given":"Charles","family":"Gatebe","sequence":"additional","affiliation":[{"name":"NASA Ames Research Center, Moffett Field, CA 94035, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8880-6070","authenticated-orcid":false,"given":"Knut","family":"Stamnes","sequence":"additional","affiliation":[{"name":"Light and Life Laboratory, Physics Department, Stevens Institute of Technology, Hoboken, NJ 07030, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1016\/j.asr.2011.12.021","article-title":"A review of global satellite-derived snow products","volume":"50","author":"Frei","year":"2012","journal-title":"Adv. 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