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Estimating Atmospheric Dust Pollutants Content Deposited on Snow Surfaces From In Situ Spectral Reflectance Measurements and Satellite Data

Authors :
Donghang Shao
Hongyi Li
Alexander Kokhanovsky
Wenzheng Ji
Xinyue Zhong
Haojie Li
Hongxing Li
Xiaohua Hao
Source :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 7903-7917 (2024)
Publication Year :
2024
Publisher :
IEEE, 2024.

Abstract

Dust deposited on the surface of snow and glaciers can significantly reduce the snow and ice albedo and accelerate melting. Manual observations of the dust mass concentration (DMC) on snow and glacier surfaces are routinely performed at many locations worldwide. However, snow and ice surface DMC monitoring methods based on remote sensing data still face challenges. This study presents a new retrieval scheme for estimating dust load on snow-covered surfaces from a moderate-resolution imaging spectroradiometer and visible infrared imaging radiometer suite in Northeast and Northwest China that utilizes a classical snow radiative transfer model. Our results indicate that the coefficient of variation of DMC retrieved from the in situ measurements of snow spectral reflectance is 4%, which is within a +4% difference compared with DMC observed in snow and ice samples. Estimating atmospheric dust pollutants content deposited on snow surfaces based on satellite remote sensing observations is feasible. In Northwest China, the root-mean-square error (RMSE) of the DMC values retrieved from VNP09GA data is 9.78 ppm, while that of the DMC values retrieved from MOD09GA data is 13.74 ppm. In Northeast China, the RMSE of the DMC values retrieved from VNP09GA data is 73.98 ppm, while that of the DMC values retrieved from MOD09GA data is 184.32 ppm. The research results can realize continuous monitoring of the atmospheric dust pollutants deposited on snow surfaces, which is of great practical significance to understanding and studying the pollution process of atmospheric dust on snow.

Details

Language :
English
ISSN :
19391404 and 21511535
Volume :
17
Database :
Directory of Open Access Journals
Journal :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.46a708bf5788451db97ec9c709ae6041
Document Type :
article
Full Text :
https://doi.org/10.1109/JSTARS.2024.3381009