Snow depth and snow water equivalent estimation from AMSR-E data based on a priori snow characteristics in Xinjiang, China

Dai, Liyun; Che, Tao; Wang, Jian; Zhang, Pu

doi:10.1016/j.rse.2011.08.029

Cited by 146 publications

(99 citation statements)

References 37 publications

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“…The mean slope of snow surface undulation and the cross-polarization ratio were set to 0.1 and 0.15, respectively [51]. The exponential correlation length in MEMLS3&a is used to describe the snow structure, which is a function of snow density and grain size [56,57], and is illustrated as follows:…”

Section: Rgz Classification Using Sentinel-1mentioning

confidence: 99%

Mapping Radar Glacier Zones and Dry Snow Line in the Antarctic Peninsula Using Sentinel-1 Images

Zhou

Zheng

2017

Remote Sensing

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Surface snowmelt causes changes in mass and energy balance, and endangers the stabilities of the ice shelves in the Antarctic Peninsula (AP). The dynamic changes of the snow and ice conditions in the AP were observed by Sentinel-1 images with a spatial resolution of 40 m in this study. Snowmelt detected by the special sensor microwave/imager (SSM/I) is used to study the relationship between summer snowmelt and winter synthetic aperture radar (SAR) backscatter. Radar glacier zones (RGZs) classifications were conducted based on their differences in liquid snow content, snow grain size, and the relative elevations. We developed a practical method based on the simulations of a microwave scattering model to classify RGZs by using Sentinel-1 images in the AP. The summer snowmelt detected by SSM/I and Sentinel-1 data are compared between 2014 and 2015. The SSM/I-derived melting days is used to validate the winter dry snow line (DSL). RGZs derived from Sentinel-1 images suggest that snowmelt expanded from inland of the Larsen C Ice Shelf to the coastal area, whereas an opposite direction was found in the George VI Ice Shelf. The long melting season in the grounding zone of the Larsen C Ice Shelf may result from the adiabatically-dried föhn winds on the east side of the AP. As the uppermost limit of summer snowmelt, DSL was mapped based on the winter Sentinel-1 mosaic of the AP. Compared with the SSM/I-derived melting days, the winter DSL mainly distributed in the areas melted for one to three days in summer. DSL elevations on the Palmer Land increased from south to north.

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Section: Rgz Classification Using Sentinel-1mentioning

confidence: 99%

Mapping Radar Glacier Zones and Dry Snow Line in the Antarctic Peninsula Using Sentinel-1 Images

Zhou

Zheng

2017

Remote Sensing

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“…The SD data used in this study were from the "Environmental and Ecological Science Data Center for West China" (http://westdc.westgis.ac.cn), which is a database with a long time series of SD in China (1979China ( -2014 (Che et al, 2008(Che et al, , 2016Dai et al, 2012Dai et al, , 2015. It is a daily SD database that was inverted using the brightness temperature data of the Scanning Multichannel Radiometer (SMMR) (1978)(1979)(1980)(1981)(1982)(1983)(1984)(1985)(1986)(1987), Special Sensor Microwave/Imager (SSM/I) , and Special Sensor Microwave Imager/Sounder (SSMI/S) (2008)(2009)(2010)(2011)(2012)(2013)(2014) passive microwave remote sensing instruments.…”

Section: Remote Sensing Snow Productsmentioning

confidence: 99%

Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China

et al. 2016

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Abstract. By combining optical remote sensing snow cover products with passive microwave remote sensing snow depth (SD) data, we produced a MODIS (Moderate Resolution Imaging Spectroradiometer) cloudless binary snow cover product and a 500 m snow depth product. The temporal and spatial variations of snow cover from December 2000 to November 2014 in China were analyzed. The results indicate that, over the past 14 years, (1) the mean snow-covered area (SCA) in China was 11.3 % annually and 27 % in the winter season, with the mean SCA decreasing in summer and winter seasons, increasing in spring and fall seasons, and not much change annually; (2) the snow-covered days (SCDs) showed an increase in winter, spring, and fall, and annually, whereas they showed a decrease in summer; (3) the average SD decreased in winter, summer, and fall, while it increased in spring and annually; (4) the spatial distributions of SD and SCD were highly correlated seasonally and annually; and (5) the regional differences in the variation of snow cover in China were significant. Overall, the SCD and SD increased significantly in south and northeast China, and decreased significantly in the north of Xinjiang province. The SCD and SD increased on the southwest edge and in the southeast part of the Tibetan Plateau, whereas it decreased in the north and northwest regions.

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“…The Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) supplied SWE and brightness temperature (BT) products Frei et al, 2012). Previous research has shown that AMSR-E BT data can simulate snow depth of the Heihe River watershed and Xinjiang region in China with accuracy above 78 % (Che et al, 2004Dai et al, 2012). Using AMSR-E BT data and state-of-the-art simulation methods (Foster et al, 1997;Yu et al, 2012), we have built a snow depth model on the TP, and have produced SD images daily, every 5 days and every 10 days from 2001 to 2010.…”

Section: Snow Remote Sensing Monitoring Datamentioning

confidence: 99%

Early warning of snow-caused disasters in pastoral areas on the Tibetan Plateau

Wang

Liang

Huang

et al. 2013

Nat. Hazards Earth Syst. Sci.

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This study develops a model for early warning of snow-caused livestock disasters on a county basis and proposes a method of qualitative risk assessment of snow disasters at 500 m resolution for pastoral areas on the Tibetan Plateau (TP). Data used for the model development include remote sensing data, statistical data of weather, livestock, and social economy, and 45 typical snow disaster cases from 2000 to 2010. The principal component analysis (PCA) approach is used to choose 7 crucial factors that contribute over 85% of information for early warning snow disasters on the TP. They are mean annual probability of snow disaster, number of snow-covered days, livestock stocking rate, continual days of mean daily temperature below −10 °C, grassland burial index, rate of snow-covered grassland, and per livestock gross domestic product. The chosen 411 cases from 2008 to 2010 are used to validate the prediction results from the developed early warning model, with an overall accuracy of 85.64% in predicting snow disasters and no disasters. This suggests that the early warning approach developed in the study has operational potential for predicting snow disasters on the TP

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Snow depth and snow water equivalent estimation from AMSR-E data based on a priori snow characteristics in Xinjiang, China

Cited by 146 publications

References 37 publications

Mapping Radar Glacier Zones and Dry Snow Line in the Antarctic Peninsula Using Sentinel-1 Images

Mapping Radar Glacier Zones and Dry Snow Line in the Antarctic Peninsula Using Sentinel-1 Images

Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China

Early warning of snow-caused disasters in pastoral areas on the Tibetan Plateau

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