%0 Dataset
%T Annual average surface temperature and freezing index of remote sensing in 2008
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/803901c0-ca43-4df5-aa64-8372c45f67ca
%W NCDC
%R 10.12072/ncdc.westdc.db3801.2023
%A Ran youhua
%K Land Temperature;Freezing index
%X Ran Youhua et al. (2015) based on MODIS Aqua / Terra develops a new method to estimate the annual average surface temperature and freezing index by using the average of LST observed in the last afternoon. The core of this method is how to recover the missing data of LST products. This method has two characteristics: (1) the variation of LST observed by remote sensing is carried out in space Inter interpolation, using the spatial continuous daily surface temperature variation obtained by interpolation, so that only once a day satellite observation data can be applied; (2) using a new missing data time series filtering method, that is, based on the discrete cosine transform, the penalty least square regression method.The results show that the accuracy of annual mean surface temperature and freezing index is only related to the accuracy of original MODIS LST, that is to say, the accuracy of MODIS LST products is maintained. It can be used in permafrost mapping and related resources and environment applications.