Quality Assessment of MOD10A1 in the Tianshan Mountains Based on Multiple Statistical Sample Scales
CHEN Xiao-na 1,2， BAO An-ming 1， LIU Ping 1,2
1. Xinjiang Institute of Ecology and Geography， CAS， Urmqi 830011， China；
2. Graduate University of the Chinese Academy of Science， Beijing 100049， China
In this paper，the MOD10A1 and Landsat-5 TM images were used as the basic data，and the snow information was extracted from Landsat-5 TM with SNOMAP developed by Hell et al.. Furthermore，a comparison between the MOD10A1 data and the classification map from Landsat-5 TM was made，and the quality accuracy of MOD10A1 was calculated at three statistical sample scales (50 pixel × 50 pixel，10 pixel × 10 pixel and 3 pixel ×3 pixel). The results show that, with the decrease of statistical sample scales，the statistical classification accuracy of snow in MOD10A1 images decreases，and the mean quantity accuracies at 50 pixel × 50 pixel，10 pixel × 10 pixel and 3 pixel ×3 pixel scale are 0.94，0.87 and 0.80 respectively. These data suggest that，limited by the spatial resolution，there is an efficient or optimum scale when MOD10A1 is applied. Meanwhile，the statistic results show that, with the decrease of the statistical classification accuracy，the stability of the MOD10A1 gradually becomes lower.
陈晓娜, 包安明, 刘萍. 基于多尺度统计样本的天山山区MOD10A1分类精度评价[J]. 国土资源遥感, 2010, 22(3): 80-85.
CHEN Xiao-Na, BAO An-Ming, LIU Ping. Quality Assessment of MOD10A1 in the Tianshan Mountains Based on Multiple Statistical Sample Scales. REMOTE SENSING FOR LAND & RESOURCES, 2010, 22(3): 80-85.
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2010, Vol. 22 
