{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T05:16:05Z","timestamp":1780722965893,"version":"3.54.1"},"reference-count":21,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2013,1,11]],"date-time":"2013-01-11T00:00:00Z","timestamp":1357862400000},"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>It is difficult and time consuming to use traditional measurement methods to estimate the physical properties of snow. However, the emergence of hyperspectral imagery for estimating the physical properties of snow provides a powerful tool. Snow albedo, grain size, and temperature are important factors for evaluating the surface energy balance. Using the spectrum-reflection curves of the different grain sizes of snow measured in the fields of the Binggou watershed of the Heihe River Basin, China, we analyzed the spectral reflection characteristics of snow. A statistical detection method was used to choose the most sensitive bands in the field spectra and find the corresponding band (band 89) in the Hyperion imagery. The bands near 1033 nm were sensitive to the snow grain size. According to the relationship between the snow grain size and the measured spectrum, we built a snow grain-size estimation model. The results showed that the snow reflectance had a good linear and exponential relationship with the snow grain size. The correlation coefficients  of the two models were 0.81 and 0.84, respectively. We obtained the location of the absorption valley at the near-infrared wavelength, and the results showed that 6.9% of the pixels were affected by the snow water content. The locations of the absorption valley moved 1\u20134 bands from band 89 to shorter wavelengths. The accuracy of the snow grain size estimates based on the Hyperion imagery was relatively high.<\/jats:p>","DOI":"10.3390\/rs5010238","type":"journal-article","created":{"date-parts":[[2013,1,11]],"date-time":"2013-01-11T11:16:17Z","timestamp":1357902977000},"page":"238-253","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Snow Grain-Size Estimation Using Hyperion Imagery in a Typical Area of the Heihe River Basin, China"],"prefix":"10.3390","volume":"5","author":[{"given":"Shuhe","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Geographic & Oceanographic Sciences, Nanjing University, Nanjing 210093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tenglong","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Geographic & Oceanographic Sciences, Nanjing University, Nanjing 210093, China"},{"name":"Jinan Environmental Monitoring Center Station, Jinan 250014, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaojun","family":"Wang","sequence":"additional","affiliation":[{"name":"Jinan Environmental Monitoring Center Station, Jinan 250014, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2013,1,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1097","DOI":"10.3390\/rs1041097","article-title":"A simple method to determine the timing of snow melt by remote sensing with application to the CO2 balances of northern mire and heath ecosystems","volume":"1","author":"Rinne","year":"2009","journal-title":"Remote Sens"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2700","DOI":"10.3390\/rs2122700","article-title":"Temporal and spatial aspects of snow distribution in the Nam Co Basin on the Tibetan Plateau from MODIS data","volume":"2","author":"Kropacek","year":"2010","journal-title":"Remote Sens"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2712","DOI":"10.1175\/1520-0469(1980)037<2712:AMFTSA>2.0.CO;2","article-title":"A model for the spectral albedo of snow: I Pure snow","volume":"37","author":"Wiscombe","year":"1980","journal-title":"J. Atoms. Sci"},{"key":"ref_4","unstructured":"Salm, B., and Gubler, H. (1987). Avalanche Formation, Movement and Effects, International Association of Hydrological Sciences Publication."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"97","DOI":"10.3189\/S026030550000046X","article-title":"Snow mapping and classification from Landsat Thematic Mapper data","volume":"9","author":"Dozier","year":"1987","journal-title":"Ann. Glaciol"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1016\/S0034-4257(96)00113-7","article-title":"Comparison of in situ and Landsat Thematic Mapper derived snow grain characteristics in the Alps","volume":"59","author":"Fily","year":"1997","journal-title":"Remote Sens. Environ"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/0034-4257(93)90018-S","article-title":"Estimating snow grain size using AVIRIS data","volume":"44","author":"Nolin","year":"1993","journal-title":"Remote Sens. Environ"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/S0034-4257(00)00111-5","article-title":"Hyperspectral method for remotely sensing the grain size of snow","volume":"74","author":"Nolin","year":"2000","journal-title":"Remote Sens. Environ"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/S0034-4257(03)00102-0","article-title":"Spatial relationships between snow contaminant content, grain size, and surface temperature from multispectral images of Mt. Rainier, Washington (USA)","volume":"86","author":"Jennifer","year":"2003","journal-title":"Remote Sens. Environ"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.rse.2006.12.020","article-title":"MODIS-based Mosaic of Antarctica (MOA) data sets: Continent-wide surface morphology and snow grain size","volume":"111","author":"Scambos","year":"2007","journal-title":"Remote Sens. 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Geoc"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.rse.2007.03.023","article-title":"ADEOS-II\/GLI snow\/ice products-Part I: Scientific basis","volume":"111","author":"Stamnes","year":"2007","journal-title":"Remote Sens. Environ"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2734","DOI":"10.1175\/1520-0469(1980)037<2734:AMFTSA>2.0.CO;2","article-title":"A model for the spectral albedo of snow. II: Snow containing atmospheric aerosols","volume":"37","author":"Warren","year":"1980","journal-title":"J. Atoms. Sci"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"121","DOI":"10.3189\/172756507781833947","article-title":"Contact spectroscopy for determination of stratigraphy of snow optical grain size","volume":"53","author":"Painter","year":"2007","journal-title":"J. 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