Recent Patterns and Trends of Snow Cover (2000–2023) in the Cantabrian Mountains (Spain) from Satellite Imagery Using Google Earth Engine

Snow cover is a relevant component of the Earth’s 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 (5–8), 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 (−0.26 days per year, and −0.92 days per year in areas with a significant trend). Altitudes between 1000–2000 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.

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Publication Details

Journal
Remote Sensing
Published
2024-09-26
DOI
https://doi.org/10.3390/rs16193592
Citations
3
Primary Topic
Cryospheric studies and observations
Type
article
Field-Weighted Citation Impact
1.13
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article

Recent Patterns and Trends of Snow Cover (2000–2023) in the Cantabrian Mountains (Spain) from Satellite Imagery Using Google Earth Engine

Adrián Melón‐Nava
3 citations
Remote Sensing
Cryospheric studies and observations
1.13
article

Recent Patterns and Trends of Snow Cover (2000–2023) in the Cantabrian Mountains (Spain) from Satellite Imagery Using Google Earth Engine

Adrián Melón‐Nava
article en
3 citations

Abstract

Snow cover is a relevant component of the Earth’s 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 (5–8), 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 (−0.26 days per year, and −0.92 days per year in areas with a significant trend). Altitudes between 1000–2000 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.

Remote SensingVol. 16(19)
Universidad de León (ES)
Openalex Percentile: Top 24%
Cryospheric studies and observations
1.13
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Recent Patterns and Trends of Snow Cover (2000–2023) in the Cantabrian Mountains (Spain) from Satellite Imagery Using Google Earth Engine — Adrián Melón‐Nava · Remote Sensing (2024) | TGRS Research Map | TGRS