Snow depth retrieval algorithm of saline-alkali land in the western Jilin Province of China using passive microwave remote sensing data

Mingbo Sun; Lingjia Gu; Ruizhi Ren; Haoyang Fu

doi:10.1117/12.2186292

4 September 2015 Snow depth retrieval algorithm of saline-alkali land in the western Jilin Province of China using passive microwave remote sensing data

Mingbo Sun, Lingjia Gu, Ruizhi Ren, Haoyang Fu

Author Affiliations +

Proceedings Volume 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII; 96100Y (2015) https://doi.org/10.1117/12.2186292
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

The western region of Jilin Province is an important part of fragile ecological environment in Northeast China where the soil salinization problem is particularly obvious. Meanwhile, it belongs to a typical snow-covered area and has a northerly continental monsoon climate, with long, cold winters and short, warm summers. It has one single large snowfall period of six month. Therefore, in this paper, the western Jilin Province was selected as the study area and divided into five land surface types including water bodies, grassland, farmland, slight saline-alkali land, moderate and severe saline-alkali land. Furthermore, the two snow depth retrieval algorithms of Chang algorithm and FY3B operational retrieval algorithm were validated and analyzed by using FY-3B/MWRI passive microwave remote sensing data. The main research focused on the analysis of the snow depth covered on the other four different land surface types except water bodies. Based on the five years' observation data from 2011 to 2015, the changes of snow depth on the four land surface types were analyzed and compared with that of MODIS 09A1 snow cover data. The analysis results demonstrated that the snow depth in farmland type is greater than that in grassland type. In addition, the snow depth in slight saline-alkali land type is greater than that in the moderate and severe saline-alkali land type. The study results also showed that the snow depth of Chang's algorithm is more accurate than that of FY3B operational retrieval algorithm in the study area. This research provided important information to the research of snow depth in saline-alkali land area.

Citation Download Citation

Mingbo Sun, Lingjia Gu, Ruizhi Ren, and Haoyang Fu "Snow depth retrieval algorithm of saline-alkali land in the western Jilin Province of China using passive microwave remote sensing data", Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 96100Y (4 September 2015); https://doi.org/10.1117/12.2186292

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KEYWORDS

Microwave remote sensing

MODIS

Algorithm development

Analytical research

Snow cover

Agriculture

Meteorological satellites

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