{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T11:45:34Z","timestamp":1762429534415,"version":"build-2065373602"},"reference-count":46,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,1,29]],"date-time":"2023-01-29T00:00:00Z","timestamp":1674950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Foundation from Key Laboratory of Disaster Prevention and Mitigation in Qinghai Province","award":["QFZ-2021-G01","41971399","2020-ZJ-731"],"award-info":[{"award-number":["QFZ-2021-G01","41971399","2020-ZJ-731"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["QFZ-2021-G01","41971399","2020-ZJ-731"],"award-info":[{"award-number":["QFZ-2021-G01","41971399","2020-ZJ-731"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012579","name":"Natural Science Foundation of Qinghai Province","doi-asserted-by":"publisher","award":["QFZ-2021-G01","41971399","2020-ZJ-731"],"award-info":[{"award-number":["QFZ-2021-G01","41971399","2020-ZJ-731"]}],"id":[{"id":"10.13039\/501100012579","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Snow cover is an essential indicator of global climate change. The composition of the underlying surface in the Pan-Arctic region is complex; forest and other areas with high vegetation coverage have a significant influence on the retrieval accuracy of fractional snow cover (FSC). Therefore, to explore the impact of vegetation on the extraction of the FSC algorithm, this study developed the normalized difference vegetation index (NDVI)-based Bivariate Linear Regression Model (BV-BLRM) to calculate the FSC. Then, the overall accuracy of the model and its changes under different classification conditions were evaluated and the relationship between the accuracy improvement and different underlying surfaces and elevations was analyzed. The results show that the BV-BLRM model is more accurate than MODIS\u2019s traditional univariate linear algorithm for FSC (MOD-FSC) in each underlying surface. Overall, regarding the accuracy of the BV-BLRM model, the RMSE is 0.2, MAE is 0.15, and accuracy is 28.6% higher than the MOD-FSC model. The newly developed BV-BLRM model has the most significant improvement in the accuracy of FSC retrieval when the underlying surface has high vegetation coverage. Under different classification accuracies, the accuracy of BV-BLRM model was higher than that of MOD-FSC model, with an average of 30.5%. The improvement of FSC extraction accuracy by the model is smaller when the underlying surface is perpetual snow zone, with an average of 12.2%. This study is applicable to the scale mapping of FSC in large areas and is helpful to improve the FSC accuracy in areas with high vegetation coverage.<\/jats:p>","DOI":"10.3390\/rs15030775","type":"journal-article","created":{"date-parts":[[2023,1,30]],"date-time":"2023-01-30T10:19:28Z","timestamp":1675073968000},"page":"775","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Estimating Fractional Snow Cover in the Pan-Arctic Region Using Added Vegetation Extraction Algorithm"],"prefix":"10.3390","volume":"15","author":[{"given":"Yuan","family":"Ma","sequence":"first","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"},{"name":"Key Laboratory of Disaster Prevention and Mitigation in Qinghai Province, Xining 810000, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6681-3640","authenticated-orcid":false,"given":"Donghang","family":"Shao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haojie","family":"Li","sequence":"additional","affiliation":[{"name":"College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8756-0104","authenticated-orcid":false,"given":"Hongyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenzheng","family":"Ji","sequence":"additional","affiliation":[{"name":"Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"67","DOI":"10.5194\/tc-7-67-2013","article-title":"An analysis of present and future seasonal Northern Hemisphere land snow cover simulated by CMIP5 coupled climate models","volume":"7","author":"Krinner","year":"2013","journal-title":"Cryosphere"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2339","DOI":"10.1175\/1520-0442(2000)013<2339:NHSCVA>2.0.CO;2","article-title":"Northern Hemisphere snow cover variability and change, 1915\u201397","volume":"13","author":"Brown","year":"2000","journal-title":"J. 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