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2012•Journal of Glaciology and GeocryologyRequires access

Algorithms for Cloud Removal in MODIS Daily Snow Products

Liang Tian-gang

Open publisher page 12 citations

Abstract

Because of the similar reflective characteristics of snow and cloud,the weather status can affect the snow monitoring by using optical remote sensing seriously.Cloud amount analysis during 2010-2011 snow season shows that the cloud cover is the major limitation to monitoring the snow cover using MOD10A1 and MYD10A1.By the use of MODIS daily snow products and AMSR-E Snow Water Equivalent products,several cloud elimination methods were integrated to produce MODIS daily cloudless snow products.To validate the accuracy of the new composited snow product,the information of snow depths from 85 climate stations in the study area was used.The snow classification accuracy of the new daily snow products reaches 91.7% when snow depth larger than 3 cm,which can be used for monitoring snow cover dynamic change in the Tibetan Plateau.

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What this paper is about

Because of the similar reflective characteristics of snow and cloud,the weather status can affect the snow monitoring by using optical remote sensing seriously.Cloud amount analysis during 2010-2011 snow season shows that the cloud cover is the major limitation to monitoring the snow cover using MOD10A1 and MYD10A1.By the use of MODIS daily snow products and AMSR-E Snow Water Equivalent products,several cloud elimination methods were integrated to produce MODIS daily cloudless snow products.To validate the accuracy of the new composited snow product,the information of snow depths from 85 climate stations in the study area was used.The snow classification accuracy of the new daily snow products reaches 91.7% when snow depth larger than 3 cm,which can be used for monitoring snow cover dynamic change in the Tibetan Plateau.

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Available abstract

Because of the similar reflective characteristics of snow and cloud,the weather status can affect the snow monitoring by using optical remote sensing seriously.Cloud amount analysis during 2010-2011 snow season shows that the cloud cover is the major limitation to monitoring the snow cover using MOD10A1 and MYD10A1.By the use of MODIS daily snow products and AMSR-E Snow Water Equivalent products,several cloud elimination methods were integrated to produce MODIS daily cloudless snow products.To validate the accuracy of the new composited snow product,the information of snow depths from 85 climate stations in the study area was used.The snow classification accuracy of the new daily snow products reaches 91.7% when snow depth larger than 3 cm,which can be used for monitoring snow cover dynamic change in the Tibetan Plateau.

Key concepts: Snow, Environmental science, Snow cover, Cloud computing, Cloud cover, Water equivalent, Snow field, Meteorology

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