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

Huaiwei Dong; Yang Gao; Chen Zhao

doi:10.1117/12.2625598

9 December 2021 Improving snow retrieval performance by fusing multiple snow cover remote sensing data

Huaiwei Dong, Yang Gao, Chen Zhao

Proceedings Volume 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021); 1212907 (2021) https://doi.org/10.1117/12.2625598
Event: 2021 International Conference on Environmental Remote Sensing and Big Data, 2021, Wuhan, China

Abstract

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.

Citation Download Citation

Huaiwei Dong, Yang Gao, and Chen Zhao "Improving snow retrieval performance by fusing multiple snow cover remote sensing data", Proc. SPIE 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021), 1212907 (9 December 2021); https://doi.org/10.1117/12.2625598

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

MODIS

Clouds

Remote sensing

Snow cover

Satellites

Spatial resolution

Meteorological satellites

Show All Keywords

Keywords/Phrases

Search In:

Publication Years