Snow Cover Identification of Saline-alkali Land in the Western Jilin Province of China based on MWRI Data

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原文链接

NETL
Spie-Int Soc Optical Engineering

外文摘要：Snow parameters are important physical quantities of climatology and hydrology research, improving the accuracy of snow parameters is important for climatology, hydrology and disaster prevention and reduction. The western Jilin Province of China has obvious salinization problem. Meanwhile, it belongs to a typical snow-covered area. In this paper, the western Jilin Province is selected as the study area and the main research focuses on analyzing the snow cover conditions. The FY3B-MWRI passive microwave remote sensing data from year 2011 to 2016 are selected as experimental data. Compared with optical remote sensing data, using MWRI data can better obtain snow information, and it is also the preliminary work to retrieve snow depth and snow water equivalent. Furthermore, a new decision tree algorithm for snow cover identification was built to distinguish different snow cover conditions. Compared with the existing three algorithms reported in other literatures, the proposed algorithm improves the identification accuracy of snow cover up to 95.06%. While the accuracy for Singh's algorithm, Pan's algorithm and Li's algorithm were about 80.19%, 78.79% and 90.13%, respectively. This study provides important information to the research of snow cover in saline-alkali land.

外文关键词：

saline-alkali landMWRIdecision tree algorithmsnow identification

作者：

Mingbo Sun、Lingjia Gu、Ruizhi Ren、Qiong Cao

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作者单位：

College of Electronic Science and Engineering, Jilin University Changchun, Jilin, 130012, China

会议名称：

Conference on remote sensing and modeling of ecosystems for sustainability XIII

会议地点：

San Diego, CA(US)

会议母体文献：

Remote sensing and modeling of ecosystems for sustainability XIII

页码：

99750K.1-99750K.16

出版时间：

2016

DOI：

10.1117/12.2235531