MODIS积雪产品的精度验证和去云处理是积雪监测研究的基础.首先利用青藏高原典型地区的ETM+数据作为“真值”影像,对MODIS积雪面积比例(FSC)产品在无云条件下的精度进行验证,发展了一个基于三次样条函数插值的去云算法,并采用基于“云假设”的检验和地面站积雪覆盖日数(SCD)检验两种方法对去云算法的精度进行了分析评价.结果表明:MODIS FSC产品在青藏高原地区具有较高的精度,与FSC“真值”相比,其平均绝对误差、均方根误差以及相关系数分别为0.098、0.156和0.916；去云算法能够有效地获取云遮蔽像元的FSC信息,平均绝对误差为0.092,用新生成的无云MODIS FSC产品计算得到的SCD与地面观测值具有较高的一致性(87.03％),平均绝对误差为3.82 d.
Accuracy Validation and Cloud Obscuration Removal of MODIS Fractional Snow Cover Products over Tibetan Plateau
Accuracy validation and cloud obscuration removal are the basis of using MODIS snow cover products to monitor snow cover change.In this paper,selecting Landsat ETM+ data of typical snow covered region as “ground truth” images,the accuracy of the MODIS Fractional Snow Cover (FSC) products over Tibetan Plateau (TP) is evaluated by comparing with these “ground truth” images.Then,to fill in the data gaps caused by clouds,a cloud removal method which based on cubic spline interpolation is developed.And the effectiveness of this method is evaluated by using the “cloud assumption” method and comparing the MODIS-derived Snow Covered Days (SCD) with the in-situ observed SCD.The results show MODIS FSC products have higher accuracy to reflect snow cover information over the TP.Comparing with the FSC “ground truth”,the overall absolute error,standard deviation and correlation coefficient for the MODIS FSC products over the TP is 0.098,0.156 and 0.916 respectively.The cloud removal method is efficient in retrieving the FSC information of these cloud covered pixels,the overall absolute error of the retrieved FSC data is 0.092.There is a relatively high consistency between MODIS-derived SCD (which is derived from the cloud removed MODIS FSC products) and in-situ observed SCD,and the mean absolute error is 3.82 days.
Tibet PlateauMODISFractional Snow CoverAccuracy validationCloud obscuration removal
NETL
NSTL
万方数据
维普
