Advances in research and application of remote sensing-based snow monitoring products

doi:10.6046/zrzyyg.2023065

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Abstract

Snow proves to be both an important factor in characterizing the surface cryosphere and a critical parameter for weather and hydrological phenomena. Employing remote sensing to conduct long-term and large-scale monitoring of snow morphologies and their changes plays a vital role in research into global climate change, investigations into hydrology and water resources, and geological disaster prevention. After decades of development, significant progress has been made in the field of remote sensing-based snow monitoring technology both in China and abroad. Accordingly, the products for remote sensing-based snow monitoring have become increasingly abundant, and the snow-orientated inversion algorithms have been continuously improved. This paper provides a summary of the existing, widely applied products after categorizing them into three types: snow-cover extent (SEC), snow coverage, and snow depth/snow water equivalent (SWE) products. Furthermore, this study organizes the commercialized remote sensing inversion algorithms used in existing, typical SEC and SWE products. The review of advances in the relevant scientific research reveals that, with the constant presence of sensors with high temporal and spatial resolutions in China and abroad and the support of both novel optical and microwave data sources and new technologies, researchers have gradually improved the accuracy of snow-orientated inversion algorithms by optimizing these algorithms based on regional characteristics. This will provide more support for continuously improving remote sensing-based snow monitoring products in the future.

Keywords remote sensing-based snow monitoring product snow cover SWE snow-orientated inversion algorithm

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Issue Date: 03 September 2024

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	Xiyong SUN
	Jiafeng LIU
	Jinghui FAN
	Wenkai ZHANG
	Lijuan SHI
	Yubao QIU
	Farong ZHU

Cite this article:

Xiyong SUN,Jiafeng LIU,Jinghui FAN, et al. Advances in research and application of remote sensing-based snow monitoring products[J]. Remote Sensing for Natural Resources, 2024, 36(3): 13-27.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2023065 OR https://www.gtzyyg.com/EN/Y2024/V36/I3/13

传感器名称	传感器类型	波长(频率)	空间分辨率/km	观测幅度/km	搭载卫星
TM	光学传感器	0.45~0.52 μm		185	Landsat5 (1984—2011年) 美国
		0.52~0.60 μm
		0.63~0.69 μm	0.03
		0.75~0.90 μm
		1.55~1.75 μm
		2.08~2.35 μm
		10.40~12.50 μm	0.12
ETM+	光学传感器	0.52~0.90 μm	0.015	185	Landsat7 (1999年至今) 美国
		0.45~0.52 μm
		0.525~0.605 μm
		0.63~0.69 μm	0.03
		0.75~0.90 μm
		1.55~1.75 μm
		2.09~2.35 μm
		10.40~12.50 μm	0.06
OLI	光学传感器	0.433~0.453 μm		185	Landsat8 (2013年至今) 美国
		0.450~0.515 μm
		0.525~0.600 μm
		0.630~0.680 μm	0.03
		0.845~0.885 μm
		1.560~1.660 μm
		2.100~2.300 μm
		1.360~1.390 μm
		0.500~0.680 μm	0.015
MODIS	光学传感器	0.620~0.876 μm	0.25	2 330	EOS Terra (1999年至今) 美国/日本/加拿大
		0.459~2.155 μm	0.5
		0.405~0.877 μm	1
		0.890~0.965 μm	1
		3.660~14.385 μm	1
NOAA/AVHRR	光学传感器	0.58~0.68 μm	1.09	2 800	TIROS-N (1979年至今) 美国
		0.725~1.00 μm
		1.58~1.64 μm
		3.55~3.93 μm
		10.30~11.30 μm
		11.50~12.50 μm
MODIS	光学传感器	0.620~0.876 μm	0.25	2 330	EOS Aqua (2001年至今) 美国
		0.459~2.155 μm	0.5
		0.405~0.877 μm	1
		0.890~0.965 μm	1
		3.660~14.385 μm	1
AMSR-E	被动微波传感器	6.925 GHz		1 445	EOS Aqua (2001年至今) 美国
		10.65 GHz	10
		18.7 GHz
		23.8 GHz
		36.5 GHz	5
		89.0 GHz
SMMR	被动微波传感	6.33 GHz 10.69 GHz 18.00 GHz 21.00 GHz 37.00 GHz	96×153 59×91 41×55 30×46 18×27	地平线 \| 地平线	NIMBUS-7
MWRI	被动微波传感器	10.65 GHz 18.70 GHz 23.80 GHz 36.50 GHz 89.00 GHz	85×51 50×30 45×27 30×18 15×9	1 400	FY-3B/3C/3D (2008年至今/2010年至今/2013年至今) 中国
SMM/I	被动微波传感器	19.30 GHz 22.20 V 37.00 GHz 85.50 GHz	70×45 60×40 38×30 16×14	1 394	DMSP-F8/ F11/ F13 (1987—1991年/1991— 2000年/1995—2009年) 美国
SSMIS	被动微波传感器	19.30 GHz 22.20 V 37.00 GHz 85.50 GHz	70×45 60×40 38×30 16×13	1 700	DMSP-F17 (2006—2017年) 美国
SSMIS	被动微波传感器	19.30 GHz 22.20 V 37.00 GHz 85.50 GHz	70×45 60×40 38×30 16×13	1 700	DMSP-F18 (2009年至今) 美国
Sentinel-1A	主动微波传感器	C波段: 5.405 GHz	0.025	>80	Sentinel (2014—2016年) 欧洲太空局
Sentinel-1A			0.1	>250
Sentinel-1B			1	>400
Sentinel-1B			0.025	400

Tab.1 Snow remote sensing commonly used sensors

Tab.2 Major snow cover products

Tab.3 Major fractional snow cover products

Tab.4 Major snow depth/water equivalent products

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