Estimation of snow depth from multi-source data fusion based on data assimilation algorithm

被引：0

作者：

Wang H. ^{[1
]}

Huang C. ^{[1
]}

Hou J. ^{[1
]}

Li X. ^{[2
,3
]}

机构：

[1] Key Laboratory of Remote Sensing of Gansu Province, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou

[2] State Key Laboratory of Frozen Soil Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou

[3] University of Chinese Academy of Sciences, Beijing

来源：

Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2016年 / 41卷 / 06期

基金：

中国国家自然科学基金;

关键词：

AMSR-E; Data assimilation algorithm; Kriging interpolation; MODIS; Snow cover;

D O I：

10.13203/j.whugis20140568

中图分类号：

学科分类号：

摘要：

In snow depth studies, the smoothing effect of ground data interpolation and the low spatial resolution of remote sensing have a great impact on the estimation accuracy. In this paper, by using cloud-removed snow cover products from the fusion of MODIS (moderate resolution imaging spectro-radiometer) and AMSR-E (advanced microwave scanning radiometer-EOS) to construct virtual station, we make up the shortage of meteorological stations less and unevenness and correct the smoothing effect of Kriging interpolation. At the same time, a new scheme is proposed to improve the estimation accuracy of snow depth interpolation, which integrates data assimilation algorithm and Kriging method to fuse ground-based snow depth measurements, MODIS snow cover products. and snow depth derived from the AMSR-E microwave brightness temperature. This method was applied in the area of northern Xinjiang. Three independent stations at different elevations were chosen to evaluate fusion results. The results indicate that the proposed algorithm can effectively improve the accuracy of snow depth spatial distribution. © 2016, Research and Development Office of Wuhan University. All right reserved.

引用

页码：848 / 852

页数：4

共 21 条

[1]

Foster J.L., Chang A.T.C., Hall D.K., Comparison of Snow Mass Estimates from a Prototype Passive Microwave Snow Algorithm, a Revised Algorithm and a Snow Depth Climatology, Remote Sensing of Environment, 62, 2, pp. 132-142, (1997)

[2]

Kelly R.E., Chang A.T., Tsang L., Et al., A Prototype AMSR-E Global Snow Area and Snow Depth Algorithm, IEEE Transactions on Geoscience and Remote Sensing, 41, 2, pp. 230-242, (2003)

[3]

Liu Y., Ruan H., Zhang P., Et al., Kriging Interpolation of Snow Depth at the North of Tianshan Mountains Assisted by MODIS Data, Geomatics and Information Science of Wuhan University, 37, 4, pp. 403-405, (2012)

[4]

Feng X., Bo Y., Shi Z., Et al., Snow Depth in North Xinjiang Region Estimated by Kriging Interpolation, Journal of Glaciology and Geocryology, 22, 4, pp. 358-361, (2000)

[5]

Chang A.T.C., Foster J.L., Hall D.K., Nimbus-7 SMMR Derived Global Snow Cover Parameters, Ann. Glaciol, 9, 9, pp. 39-44, (1987)

[6]

Che T., Li X., Jin R., Et al., Snow Depth Derived from Passive Microwave Remote-Sensing Data in China, Annals of Glaciology, 49, 1, pp. 145-154, (2008)

[7]

Che T., Li X., Retrieval of Snow Depth in China by Passive Microwave Remote Sensing Data and Its Accuracy Assessment, Remote Sensing Technology and Application, 19, 5, pp. 301-306, (2004)

[8]

Jiang L., Wang P., Zhang L., Et al., Improvement of Snow Depth Retrieval for FY3B-MWRI in China, Science China: Earth Sciences, 44, 3, pp. 531-547, (2014)

[9]

Yamamoto J.K., Correcting the Smoothing Effect of Ordinary Kriging Estimates, Mathematical Geology, 37, 1, pp. 69-94, (2005)

[10]

Wang X., Xie H., Liang T., Evaluation of MODISSnow Cover and Cloud Mask and Its Application in Northern Xinjiang, China, Remote Sensing of Environment, 112, 4, pp. 1497-1513, (2008)

← 1 2 3 →