A new MODIS daily cloud free snow cover mapping algorithm on the Tibetan Plateau

Because of similar reflective characteristics of snow and cloud, the weather status seriously affects snow monitoring using optical remote sensing data. Cloud amount analysis during 2010 to 2011 snow seasons shows that cloud cover is the major limitation for snow cover monitoring using MOD10A1 and MYD10A1. By use of MODIS daily snow cover products and AMSR-E snow wa- ter equivalent products （SWE）, several cloud elimination methods were integrated to produce a new daily cloud flee snow cover product, and information of snow depth from 85 climate stations in Tibetan Plateau area （TP） were used to validate the accuracy of the new composite snow cover product. The results indicate that snow classification accuracy of the new daily snow cover product reaches 91.7% when snow depth is over 3 cm. This suggests that the new daily snow cover mapping algorithm is suitable for monitoring snow cover dynamic changes in TP.

The urgent need to develop a new grassland map in China:based on the consistency and accuracy of ten land cover products

Grasslands are the most dominant terrestrial ecosystem in China, but few national grassland maps have been generated. The grassland resource map produced in the 1980s is widely used as background data, but it has not been updated for almost 40 years.Therefore, a reliable map depicting the current spatial distribution of grasslands across the country is urgently needed. In this study, we evaluated the grassland consistency and accuracy of ten land cover datasets(GLC2000, GlobCover, CCI-LC,MCD12Q1, CLUD, GlobeLand30, GLC-FCS30, CGLS-LC100, CLCD, and FROM-GLC) for 2000, 2010, and 2020 based on extensive fieldwork. We concluded that the area of these ten grassland products ranges from 107.80×10^(4)to 332.46×10^(4)km^(2), with CLCD and MCD12Q1 having the highest area consistency. The spatial and sample consistency is highest in the regions of eastcentral Inner Mongolia, the Qinghai-Tibet Plateau and northern Xinjiang, while the distribution of southern grasslands is scattered and differs considerably among the ten products. MCD12Q1 is significantly more accurate than the other nine products,with an overall accuracy(OA) reaching 77.51% and a kappa coefficient of 0.51;CLCD is slightly less accurate than MCD12Q1(OA=73.02%, kappa coefficient=0.45) and is more conducive to the fine monitoring and management of grassland because of its30-meter resolution. The highest accuracy of grassland was found in the Inner Mongolia-Ningxia region and Qinghai-Tibet Plateau, while the accuracy was worst in the southeastern region. In the future grassland mapping, cartographers should improve the accuracy of the grassland distribution in South China and regions where grassland is confused with forest, cropland and bare land. We specify the availability of valuable data in existing land cover datasets for China’s grasslands and call for researchers and the government to actively produce a new generation of grassland maps.

A novel solution for outlier removal of ICESat altimetry data： a case study in the Yili watershed, China

Due to the influence of cloud and saturated waveforms, ICESat data contain many contaminated elevation data that cannot be directly used in examining surface elevation and change. This study provides a novel solution for removing bad data and getting clean ICESat data for land applications by using threshold values of reflectivity, saturation, and gain directly from ICESat＇s GLAS （Geoscience Laser Alteimeter System） 01, 05, and 06 products. It is found that each laser campaign needs different threshold compositions to assure qualified ICESat data and that bad data removal rates range from 9.6% （laser 2A） to 62.3% （laser 2B） for the test area in the Yili watershed, China. These thresholds would possibly be used in other regions to extract qualified ICESat footprints for land applications. However, it is recommended to use the steps proposed here to further examine the transferability of threshold values for other regions of different elevations and climate regimes. As an example, the resulting ICESat data are applied to examine lake level changes of two lakes in the study area.