Evaluation and Adjustment of the AMSR2 Snow Depth Algorithm for the Northern Xinjiang Region, China
Evaluation and Adjustment of the AMSR2 Snow Depth Algorithm for the Northern Xinjiang Region, China
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DOI：
10.1109/jstars.2016.2620521
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发表时间：
2017-09
影响因子：
5.5
通讯作者：
Renping Zhang;Tiangang Liang;Qisheng Feng;Xiaodong Huang;Wei Wang;H. Xie;Jing Guo
中科院分区：
文献类型：
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作者：
Renping Zhang;Tiangang Liang;Qisheng Feng;Xiaodong Huang;Wei Wang;H. Xie;Jing Guo
利用被动微波遥感技术精确测绘积雪深度仍然是一个挑战。本研究首先对北疆地区标准的AMSR2积雪深度产品中国进行了验证，然后结合该地区的实测资料，提出了一种改进的基于AMSR2亮温数据的积雪深度反演算法。结果表明：1)近15年来，基于气象站的平均雪深变化范围为1.1~20.4 cm(平均8.9 cm)，当雪深小于30 cm时，标准AMSR2雪深积高估(低估)雪深，总体估计误差(均方根误差)随雪深的增加而增大；对于上升模式(AMSR2_A)和下降模式(AMSR2_D)，我们的改进算法分别比标准AMSR2产品(5.7和6.7 cm)和(11.2和12.1 cm)具有更小的偏差(2.5和3.9 cm)和更小的误差(6.9和8.2 cm)。这表明，基于AMSR2_A亮温数据的改进算法具有较好的精度和较小的误差，可用于北疆非林区寒冷期积雪深度的反演。
It is still a challenge to accurately map snow depth using passive microwave remote sensing. This study first validates the standard AMSR2 snow depth product in Northern Xinjiang, China, and then proposes an improved snow depth retrieving algorithm using the AMSR2 brightness temperature data in combination with in-situ measurements in the same region. The results show that: 1) in the past 15 years the mean snow depth based on the metrological stations ranges from 1.1 to 20.4 cm (mean 8.9 cm); 2) the standard AMSR2 snow depth product overestimates (underestimates) snow depth when snow depth thinner (thicker) than 30 cm, with an overall increased estimation error (root mean squared error) as snow depth increase; and 3) for the ascending mode (AMSR2_A) and descending mode (AMSR2_D), our improved algorithm shows smaller bias (2.5 and 3.9 cm) and smaller error (6.9 and 8.2 cm) as compared with the standard AMSR2 products (5.7 and 6.7 cm) and (11.2 and 12.1 cm), respectively. This suggests that the improved algorithm based on brightness temperature data of AMSR2_A has better accuracy and smaller error and can be used to retrieve snow depth of nonforest areas in cold period in the Northern Xinjiang.