2021
DOI: 10.1109/jstars.2021.3089655
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Performance Assessment of Optical Satellite-Based Operational Snow Cover Monitoring Algorithms in Forested Landscapes

Abstract: Forest cover is a crucial factor that influences the performance of optical satellite-based snow cover monitoring algorithms. However, evaluation of such algorithms in forested landscapes are rare due to lack of reliable in-situ data in such regions. In this investigation, we assessed the performance of the operational snow detection (SCA) and fractional snow cover estimation (FSC) algorithms employed by the Copernicus Land Monitoring Service (CLMS) for High-Resolution Snow & Ice Monitoring (HR-S&I) with a com… Show more

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Cited by 52 publications
(28 citation statements)
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“…Recent studies show that the MODIS snow cover product overestimates the snow cover areas for the Mount Everest region, with the absolute error ranging from 20.1 % to 55.7 %, whereas the improved algorithm estimates the snow cover for the HKH region with an absolute accuracy greater than 90 % . The cloud cover and topographic shading in the mountainous regions are known to be the major factors affecting the accuracy of snow cover products (Muhuri et al, 2021). Parajka et al (2010) developed and validated a regional snow line method (SNOWL) for estimating snow cover from the MODIS daily product, especially during cloudy conditions (up to 90 %) over Austria.…”
Section: Reported Analysis Of Modis Snow Cover Datamentioning
confidence: 99%
“…Recent studies show that the MODIS snow cover product overestimates the snow cover areas for the Mount Everest region, with the absolute error ranging from 20.1 % to 55.7 %, whereas the improved algorithm estimates the snow cover for the HKH region with an absolute accuracy greater than 90 % . The cloud cover and topographic shading in the mountainous regions are known to be the major factors affecting the accuracy of snow cover products (Muhuri et al, 2021). Parajka et al (2010) developed and validated a regional snow line method (SNOWL) for estimating snow cover from the MODIS daily product, especially during cloudy conditions (up to 90 %) over Austria.…”
Section: Reported Analysis Of Modis Snow Cover Datamentioning
confidence: 99%
“…We have used unsupervised classification technique to classify the surface features because of the large study area [87]. A confusion or error matrix and Kappa coefficient (K) has been used to perform the accuracy assessment [88]. A set of 261 random points were created for accuracy assessment, which were then overlaid on the Google Earth image for cross checking the unsupervised classification result with the actual ground feature.…”
Section: Land Cover and Usementioning
confidence: 99%
“…As shown in Figure 3, the Landsat-7 and Sentinel-2 derived velocities have a measurement error of −3.4 ± 11.6 m yr −1 and 0.4 ± 4.6 m yr −1 , respectively. Since all the image pairs are centred around December with little interannual fluctuations, the uncertainty depends largely on radiometric quality and image resolution, indicating that Sentinel-2 imagery has a better radiometric quality than Landsat-7 imagery [21], and higher resolution improves pixel matching [20], hence yielding more consistent results. 2.…”
Section: Methodsmentioning
confidence: 99%
“…We first derived glacier velocities for two periods, early winter in 1999-2000 and 2017-2018, using Landsat-7 and Sentinel-2 image pairs, respectively. High-resolution satellites provide a powerful tool for monitoring ice and snow [19,20]. We chose Sentinel-2 over Landsat-7 for mapping the present glacier motion because it has been tested to have a better geometric and radiometric quality [21].…”
Section: Introductionmentioning
confidence: 99%