Print Email Facebook Twitter Downscaling MODIS NDSI to Sentinel-2 fractional snow cover by random forest regression Title Downscaling MODIS NDSI to Sentinel-2 fractional snow cover by random forest regression Author Kollert, Andreas (University of Innsbruck) Mayr, Andreas (University of Innsbruck) Dullinger, Stefan (University of Vienna) Hülber, Karl (University of Vienna) Moser, Dietmar (University of Vienna) Lhermitte, S.L.M. (TU Delft Mathematical Geodesy and Positioning; Katholieke Universiteit Leuven) Gascoin, Simon (Université de Toulouse) Rutzinger, Martin (University of Innsbruck) Date 2024 Abstract Imagery acquired by the Moderate-resolution Imaging Spectroradiometer (MODIS) provides a global archive of dailyNormalized Difference Snow Index (NDSI) at 500 m nominal resolution since the year 2000. While Sentinel-2 (S2) NDSI provides an increased spatial resolution of 20 m since the year 2015, the temporal resolution amounts to only 5 days and thus lacks the high temporal resolution of MODIS. Efforts to combine NDSI datasets for an increased temporal and spatial resolution have so far focused on the deriving binary snow cover maps or combining data from other sensors. In contrast, we produce fine scale (20 m) fractional snow cover (FSC) by downscaling MODIS NDSI to S2 resolution. Random forest regression predicts S2 NDSI based on dynamic features (MODIS NDSI, day-of-year) and static, topographic features for an alpine study site. Subsequently, FSC is derived from S2 NDSI. Cross-validation results in R2 of 0.795 and RMSE of 0.155 for FSC and outperforms common resampling methods. Multi-annual S2 NDSI metrics are able to slightly improve model accuracy. Our results suggest that combining topographical data and low-resolution NDSI allows to produce daily, high-resolution S2 NDSI and FSC and improve fine scale characterization of snow cover dynamics in mountain landscapes. Subject downscalingFractional Snow Cover (FSC)machine learningMODISNormalized Difference Snow Index (NDSI)Sentinel-2 (S2) To reference this document use: http://resolver.tudelft.nl/uuid:f7731f60-10c2-4f82-b34b-e41ba95ffacb DOI https://doi.org/10.1080/2150704X.2024.2327084 ISSN 2150-704X Source Remote Sensing Letters, 15 (4), 363-372 Part of collection Institutional Repository Document type journal article Rights © 2024 Andreas Kollert, Andreas Mayr, Stefan Dullinger, Karl Hülber, Dietmar Moser, S.L.M. Lhermitte, Simon Gascoin, Martin Rutzinger Files PDF Downscaling_MODIS_NDSI_to ... ession.pdf 3.66 MB Close viewer /islandora/object/uuid:f7731f60-10c2-4f82-b34b-e41ba95ffacb/datastream/OBJ/view