Validation of the MODIS snow product and cloud mask using student and NWS cooperative station observations in the Lower Great Lakes Region

Ault, Timothy W.; Czajkowski, Kevin; Benko, Teresa; Coss, J.; Struble, J.; Spongberg, Alison L.; Templin, Mark; Gross, C.

doi:10.1016/j.rse.2006.07.004

Cited by 103 publications

(76 citation statements)

References 25 publications

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“…The MODIS data are processed in three steps: (1) mosaicking the five individual tiles into one map and re-projecting it to geographic latitude/longitude projection for each period by using MRT, (2) extracting the data of Tibet Autonomous Region from the merged five tiles' data using GIS, and (3) extracting the snow and cloud information for all periods in GIS. In order to compare with the snow observations at the ground stations, two further steps were taken: (4) The MODIS snow parameter for each location of the 37 stations is extracted by using 'The Maximum Neighborhood Analysis' tool in GIS [42,43]. The procedure is to extract the values of the station pixel and its eight surrounding neighbor pixels from the MOD10A2 data.…”

Section: Modis Eight-day Snow Productsmentioning

confidence: 99%

Satellite and Ground Observations of Snow Cover in Tibet during 2001–2015

2017

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Abstract:The seasonal snow cover of the Tibetan Plateau exerts a profound environmental influence both regionally and globally. Daily observations of snow depth at 37 meteorological stations in Tibet and MODIS eight-day snow products (MOD10A2) during the period 2001-2015 are analyzed with respect to the frequency and spatial distribution of snow cover for each season and for various altitude ranges. The results show that the average snow cover percentage was 16%. Snow cover frequency was less than 21% for 70% of the Tibetan area, while it was more than 40% in eastern Tibet and in the Himalayas. We also estimated the variations in the starting times of snow accumulation and ablation. During the 15 years, both datasets revealed a significant trend of earlier onset of ablation, but no evident trend for the start of accumulation. The two datasets differed slightly with respect to the seasonal variation of snow cover. MODIS data showed more snow in winter than in other seasons, but the ground data showed most snow in early spring. For the station locations, the correlation between ground and MODIS snow cover percentage (number of snow-covered stations/number of cloud-free stations) is 0.77. Combining the advantages of remote sensing data and ground observation data is the best way to investigate snow in Tibet.

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Section: Modis Eight-day Snow Productsmentioning

confidence: 99%

Satellite and Ground Observations of Snow Cover in Tibet during 2001–2015

2017

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“…As a consequence, the NDVI test for forested areas is not activated for Aqua products. The successive versions of the MODIS snow products were compared with snow maps obtained from other sources at similar or lower resolution (i.e., relative validation, Hall et al, 2002;Klein and Barnett, 2003;Maurer et al, 2003;Simic et al, 2004;Rittger et al, 2013) and validated using ground snow measurements (i.e., absolute validation) (Klein and Barnett, 2003;Maurer et al, 2003;Simic et al, 2004;Ault et al, 2006;Parajka and Blöschl, 2006;Arsenault et al, 2014). Most of these studies were done using the Terra MODIS daily snow product (MOD10A1).…”

Section: Introductionmentioning

confidence: 99%

A snow cover climatology for the Pyrenees from MODIS snow products

Gascoin

Hagolle

Huc

et al. 2015

Hydrol. Earth Syst. Sci.

146

118

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Abstract. The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (w.e.) and 150 mm, respectively, for both MOD10A1 and MYD10A1. κ coefficients are within 0.74 and 0.92 depending on the product and the variable for these thresholds. However, we also find a seasonal trend in the optimal SWE and SD thresholds, reflecting the hysteresis in the relationship between the depth of the snowpack (or SWE) and its extent within a MODIS pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97 % (κ = 0.85) for MOD10A1 and 96 % (κ = 0.81) for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96 %, κ = 0.77; MYD10A1: 95 %, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50 % of the time above 1600 m between December and April. We finally analyze the snow patterns for the atypical winter 2011-2012. Snow cover duration anomalies reveal a deficient snowpack on the Spanish side of the Pyrenees, which seems to have caused a drop in the national hydropower production.

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“…Previous a Previous studies have compared MODIS snow maps with ground observations and snow maps produced by the National Operational Hydrologic Remote Sensing Center, USA (NOHRSC) (Hall et al, 2002;Klein and Barnett, 2003;Tekeli et al, 2005;Aulta et al, 2006). Klein and Barnett (2003) compared MODIS and NOHRSC products with ground observations (SNOTEL measurements), obtaining an overall accuracy of 94 and 76 %, respectively.…”

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confidence: 99%

Snow cover dynamics in Andean watersheds of Chile (32.0–39.5° S) during the years 2000–2016

Stehr¹,

Aguayo²

2017

Hydrol. Earth Syst. Sci.

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Abstract. Andean watersheds present important snowfall accumulation mainly during the winter, which melts during the spring and part of the summer. The effect of snowmelt on the water balance can be critical to sustain agriculture activities, hydropower generation, urban water supplies and wildlife. In Chile, 25 % of the territory between the region of Valparaiso and Araucanía comprises areas where snow precipitation occurs. As in many other difficult-to-access regions of the world, there is a lack of hydrological data of the Chilean Andes related to discharge, snow courses, and snow depths, which complicates the analysis of important hydrological processes (e.g. water availability). Remote sensing provides a promising opportunity to enhance the assessment and monitoring of the spatial and temporal variability of snow characteristics, such as the snow cover area (SCA) and snow cover dynamic (SCD). With regards to the foregoing questions, the objective of the study is to evaluate the spatiotemporal dynamics of the SCA at five watersheds (Aconcagua, Rapel, Maule, Biobío and Toltén) located in the Chilean Andes, between latitude 32.0 and 39.5 • S, and to analyse its relationship with the precipitation regime/pattern and El Niño-Southern Oscillation (ENSO) events. Those watersheds were chosen because of their importance in terms of their number of inhabitants, and economic activities depending on water resources. The SCA area was obtained from MOD10A2 for the period 2000-2016, and the SCD was analysed through a number of statistical tests to explore observed trends. In order to verify the SCA for trend analysis, a validation of the MOD10A2 product was done, consisting of the comparison of snow presence predicted by MODIS with ground observations. Results indicate that there is an overall agreement of 81 to 98 % between SCA determined from ground observations and MOD10A2, showing that the MODIS snow product can be taken as a feasible remote sensing tool for SCA estimation in southern-central Chile. Regarding SCD, no significant reduction in SCA for the period 2000-2016 was detected, with the exception of the Aconcagua and Rapel watersheds. In addition to that, an important decline in SCA in the five watersheds for the period of 2012 and 2016 was also evident, which is coincidental with the rainfall deficit for the same years. Findings were compared against ENSO episodes that occurred during 2010-2016, detecting that Niña years are coincident with maximum SCA during winter in all watersheds.

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Validation of the MODIS snow product and cloud mask using student and NWS cooperative station observations in the Lower Great Lakes Region

Cited by 103 publications

References 25 publications

Satellite and Ground Observations of Snow Cover in Tibet during 2001–2015

Satellite and Ground Observations of Snow Cover in Tibet during 2001–2015

A snow cover climatology for the Pyrenees from MODIS snow products

Snow cover dynamics in Andean watersheds of Chile (32.0–39.5° S) during the years 2000–2016

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Validation of the MODIS snow product and cloud mask using student and NWS cooperative station observations in the Lower Great Lakes Region

Cited by 103 publications

References 25 publications

Satellite and Ground Observations of Snow Cover in Tibet during 2001–2015

Satellite and Ground Observations of Snow Cover in Tibet during 2001–2015

A snow cover climatology for the Pyrenees from MODIS snow products

Snow cover dynamics in Andean watersheds of Chile (32.0–39.5° S) during the years 2000–2016

Contact Info

Product

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Snow cover dynamics in Andean watersheds of Chile (32.0–39.5° S) during the years 2000–2016