%0 Dataset
%T "The Belt and Road" Snow Area Proportion Daily Data Product Dataset (2000-2024)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/e03459ac-6880-4492-af57-2041de728344
%W NCDC
%R 10.12072/ncdc.nieer.db6622.2024
%A HAO Xiaohua 
%A ZHAO Qin
%A JI Wenzheng
%A GAO Weiqinag
%K The Belt and Road;snow coverage;snow coverage ratio
%X Aiming at the problem that the existing snow cover products in the "the Belt and Road" area are underestimated in mountain areas and woodlands, based on multi-source remote sensing data, a set of snow cover data in the "the Belt and Road" area was generated by using the MARS model combined with the method of land type characteristics to automatically identify snow cover. By leveraging the advantages of machine learning in solving nonlinear fitting problems and avoiding the misjudgment of traditional snow remote sensing recognition in complex terrain and terrain, the accuracy of this product in mountainous and forested areas has significantly improved compared to existing MODIS snow products.