Mr. Chen Zhao Profile

Chen Zhao

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Proceedings Article | 9 December 2021 Paper

Improving snow retrieval performance by fusing multiple snow cover remote sensing data

Huaiwei Dong, Yang Gao, Chen Zhao

Proceedings Volume 12129, 1212907 (2021) https://doi.org/10.1117/12.2625598

KEYWORDS: MODIS, Clouds, Remote sensing, Snow cover, Satellites, Spatial resolution, Meteorological satellites, Data fusion, Ocean optics, Composites

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Remote sensing can be used to monitor snow cover in a large area, which has a major contribution to climate and environmental research, the establishment of hydrological models, and disaster prevention and mitigation. Multiple remote sensing data fusion is an important means to improve the efficiency of snow cover detection. This study used 192 SNOTEL stations in the northwestern United States to evaluate the commonly used MODIS datasets and IMS snow and ice product. It is found that the snow inversion effect in the cloud-free area of the MODIS datasets is better, and IMS snow and ice product has lower snow recognition rate but no cloud. Based on this, we integrated the snowy area of the MODIS datasets into the IMS snow and ice product, and generated a new product called MIMS. The results show that the SRP of MIMS is 72.93%, which is higher than the MODIS datasets (72.78%) and the IMS snow and ice procduct (70.46%). At the same time, the new product eliminates cloud pollution and improves the spatial resolution. It can be seen that the fusion of multiple remote sensing data can effectively improve the performance of snow inversion, and has important reference value for the accurate monitoring of snow in different regions.

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