article · International Journal of Applied Earth Observation and Geoinformation
In semi-arid Mediterranean regions, downstream populations rely heavily on water from mountain snowmelt. Ground-based hydroclimatic data in these areas is limited, making remote sensing critical for monitoring snow cover. An investigation evaluated the MODIS version 6 snow cover product and developed models for fractional snow cover estimation across the Moroccan Atlas Mountains. Using 448 Sentinel-2 scenes alongside thousands of MODIS images from 2000 to 2023, the approach lowered cloud-covered pixels from 25.7% to 0.4%. Testing demonstrated that a local Normalised Difference Snow Index threshold of 0.2 outperforms the standard global threshold of 0.4, preventing substantial underestimations. Fractional snow cover models and a daily snow cover product were developed and verified against high-resolution Sentinel-2 imagery, showing strong correlation and low error rates.
Snowpack in the Moroccan Atlas Mountains acts as a vital water tower, feeding rivers and replenishing groundwater for downstream populations. Because on-the-ground weather stations are sparse, refining satellite observation methods provides water authorities and climate researchers with more dependable daily data to assess available water supplies and track seasonal snow dynamics in water-stressed environments.
The work represents an applied and validated data product that could be incorporated into operational hydrological modelling tools, regional water resource planning platforms, and meteorological monitoring services. Direct users would include water basin agencies, environmental consultancies, and government departments managing water infrastructure. The method is fully demonstrated on historical satellite data, positioning it close to operational deployment for regional monitoring initiatives.
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• Assessment of MODIS V6 snow product in the southern Mediterranean (2000–2023). • Development of an adaptive ML model for snow detection from Sentinel-2 images. • The NDSI threshold of 0.2 is more reasonable than 0.4 for use in Morocco. • Formulation of suitable models for estimating fractional snow cover. • Generation of precise daily snow cover product for the Moroccan Atlas Mountains. In semi-arid Mediterranean areas, a significant proportion of the population living downstream depends on water resources from snowmelt and precipitation as their main source of water. Consequently, snow-covered mountain regions can be considered as a vital water tower, providing a steady supply of water, and contributing significantly to streamflow and groundwater recharge. Given the scarcity of ground-based hydroclimatic measurements, remote sensing could be an effective technique for mapping and monitoring snow cover. This study evaluates the last version of MODIS (version 6, called V6) snow cover product, optimizing the NDSI threshold for accurate snow cover mapping and developing models for local fractional snow cover estimation in the southern Mediterranean region, particularly in the Moroccan Atlas Mountains. For this purpose, 448 Sentinel-2 (S2) scenes from six different regions across the Atlas Range were used to adjust the NDSI threshold and to develop FSC estimation models. In addition, a total of 8419 MOD10A1 images from March 2000 to June 2023, and 7561 MYD10A1 images from September 2002 to June 2023, were processed to improve cloud filtering and to develop a highly accurate daily snow cover product suitable for the Moroccan Atlas Mountains. The cloud correction approach significantly reduced the number of cloud-covered pixels, from 25.7% to 0.4% after filtering. Two schemes for selecting the MODIS NDSI threshold were tested: (1) the global reference of 0.4 and (2) the locally optimal threshold of 0.2. The average snow cover estimation errors using the optimal and global NDSI thresholds for Terra are an average overestimation of 0.34% and a significant underestimation of 6.13%, respectively. For Aqua, the corresponding errors are an overestimation of 1.4% and an underestimation of 6.8%. Thus, the optimal NDSI threshold of 0.2 could be more appropriate than the threshold of 0.4 for use in the southern Mediterranean region. The new FSC estimation models developed showed satisfactory performance with significant correlation coefficients (mean of 0.85 for Terra and 0.83 for Aqua), and with low RMSE and MAE values (mean of 0.17 and 0.12 for Terra and mean of 0.19 and 0.14 for Aqua) when comparing FSC derived from high-resolution S2 data with predicted FSC from MODIS NDSI. The daily snow cover product developed was compared with the high-resolution snow maps obtained from S2 satellite imagery in different regions of the Moroccan Atlas. On average, the product showed a mean correlation coefficient of 0.96, a mean absolute error of 0.22%, and a mean reasonable negative bias of −0.17%. This research concludes that the enhanced daily snow cover product could improve the understanding of spatiotemporal dynamics of snow extent and, therefore, contribute to quantifying the snowmelt contribution to the water budget through modeling approaches in the southern Mediterranean region.
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DOI: 10.1016/j.jag.2024.103851
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