Accuracy Analysis for MODIS Snow Products of MOD10A1 and MOD10A2 in Northern Xinjiang Area
By the use of NASA EOS Terra/MODIS snow products of MOD10A1 and MOD10A2 and climatic data, the snow classification accuracy was analyzed using Geographic Information System (GIS) techniques for 90 temporal daily snow composite products of MOD16A1 and 11 temporal eight-day composite products of MOD10A2 from December 1, 2004 to February 28, 2005, Results showed that: 1) When snow depth is less than 3 cm, the precision of snow identified by MOD10A1 is very low, only 7.5%; as snow depth is between 4 cm to 6 cm, MOD10A1 snow identification accuracy reaches to 29. 3% ; and the precision is 45.6% when snow depth is between 15 to 20 cm; The mean accuracy is 31. 5% when the snow depth is great than 20 cm; 2) the precision of snow identification for MOD10A1 products is severely affected by climatic situation. Under sunshine weather conditions, the snow identification accuracy of MOD10A1 reaches to 50.6%; but the average of snow identification rate was only 18% when it is cloudy or overcast; 3) The condition of underlying surface is another factor affecting the MOD10A1 classification results, such as, under clear sky conditions, the precision of snow identified by MOD10A1 is 68% for grasslands with sparse trees and shrubs; in desert, the snow identification rate is 64. 4% , and only 40% for agricultural land and 4) It can better eliminate the influence of amount of clouds and improve the snow classification precision for MOD10A2 products, as a result, the mean precision of snow identification is 87.5%, which can reflect better the ground snow distribution and plays an important role in snow disaster monitoring in pastoral areas.
NETL
NSTL
万方数据
维普
