{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T03:08:59Z","timestamp":1776395339719,"version":"3.51.2"},"reference-count":93,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T00:00:00Z","timestamp":1727308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministerio de Universidades","award":["FPU20\/01220"],"award-info":[{"award-number":["FPU20\/01220"]}]},{"name":"Spanish Ministerio de Universidades","award":["2022\/00232\/001"],"award-info":[{"award-number":["2022\/00232\/001"]}]},{"name":"Universidad de Le\u00f3n","award":["FPU20\/01220"],"award-info":[{"award-number":["FPU20\/01220"]}]},{"name":"Universidad de Le\u00f3n","award":["2022\/00232\/001"],"award-info":[{"award-number":["2022\/00232\/001"]}]},{"name":"publication-Universidad de Le\u00f3n","award":["FPU20\/01220"],"award-info":[{"award-number":["FPU20\/01220"]}]},{"name":"publication-Universidad de Le\u00f3n","award":["2022\/00232\/001"],"award-info":[{"award-number":["2022\/00232\/001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Snow cover is a relevant component of the Earth\u2019s climate system, influencing water supply, ecosystem health, and natural hazard management. This study aims to monitor daily snow cover in the Cantabrian Mountains using Sentinel-2, Landsat (5\u20138), and MODIS data processed in Google Earth Engine (GEE). The main purpose is to extract metrics on snow cover extent, duration, frequency, and trends. Key findings reveal significant spatial and temporal variability in Snow-Cover Days (SCDs) across the region. Over the past 23 years, there has been a notable overall decrease in snow-cover days (\u22120.26 days per year, and \u22120.92 days per year in areas with a significant trend). Altitudes between 1000\u20132000 m a.s.l. showed marked decreases. The analysis of Snow-Cover Fraction (SCF) indicates high interannual variability and records the highest values at the end of January and the beginning of February. The effectiveness of satellite data and GEE is highlighted in providing detailed, long-term snow cover analysis, despite some limitations in steep slopes, forests, and prolonged cloud-cover areas. These results underscore the capacity for continuous monitoring with satellite imagery, especially in areas with sparse snow observation networks, where studies could be enhanced with more localized studies or additional ground-based observations.<\/jats:p>","DOI":"10.3390\/rs16193592","type":"journal-article","created":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T06:55:52Z","timestamp":1727333752000},"page":"3592","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Recent Patterns and Trends of Snow Cover (2000\u20132023) in the Cantabrian Mountains (Spain) from Satellite Imagery Using Google Earth Engine"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4796-7214","authenticated-orcid":false,"given":"Adri\u00e1n","family":"Mel\u00f3n-Nava","sequence":"first","affiliation":[{"name":"Departamento de Geograf\u00eda y Geolog\u00eda, Universidad de Le\u00f3n, Campus de Vegazana s\/n, 24071 Le\u00f3n, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1038\/s41558-020-0746-8","article-title":"Agricultural Risks from Changing Snowmelt","volume":"10","author":"Qin","year":"2020","journal-title":"Nat. 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