Research Of Snow Parameters In The Western Jilin Province Of China Based On Satellite Remote Sensing Data

Snow is an important part of the Earth's surface cover and is one of the most important factors that affect climate and human activities,it is quite meaningful to accurately monitor snow parameters.The Western Jilin Province is located in the south-central part of the Songnen Plain in Northeast China.The snow cover in there has a large area and long period in winter,it deeply influences the local economy and people's livelihood.In addition,the high degree of salinization in this area forms its unique land surface characteristics.In this study,FY3B-MWRI data are selected as the experimental data.Combined with spectral remote sensing data,the snow cover and snow depth of Western Jilin Province are observed and analyzed,and the main work and results are listed as follows.(1)Snow cover identification of Western Jilin Province of China based on MWRI data.In this part of the article,through comparing with existing snow cover identification algorithms based on passive remote sensing data,three representative algorithms,Singh snow cover identification algorithm,Lixiaojing snow cover identification algorithm and Panjinmei snow cover identification algorithm,are selected to analyze the snow cover condition of the study area.The observation periods are December in 2010 and every January in 2012 to 2016.Then the retrieval results of snow depth were compared with MOD10A1 snow product.The final results indicate that each of these three algorithms doesn't have a good accuracy.After error analysis and parameter optimization of the three algorithms,an algorithm which is more suitable for Western Jilin Province is proposed in this paper.The result shows that the total accuracy of the proposed algorithm is 95.4%,which is definitely higher than the total accuracy of Singh snow cover identification algorithm(78.3%),Panjinmei snow cover identification algorithm(76.7%)and Lixiaojing snow cover identification algorithm(89.6%).(2)Snow depth retrieval algorithm of saline-alkali land in the Western Jilin Province of China using passive microwave remote sensing data.In this part of the article,the Chang algorithm and the FY3 B operational retrieval algorithm are used to retrieve the snow depth in December in 2010 and every January in 2012 to 2015 based on FY3B-MWRI passive microwave remote sensing data.Combined with the land classification data,the retrieval snow depth in different land surface are compared and analyzed.In order to further improve the algorithm accuracy,the retrieval results of snow depth is combined with the results of snow cover identification,and the values in no snow areas are eliminated.Then the final results indicate that the snow depth of the four land surface types obviously increase.In addition,the results also show that the snow depth of the observation area gradually decreases from southeast to northwest in spatial distribution.