A Dynamic Snow Depth Inversion Algorithm Derived from AMSR2 Passive Microwave Brightness Temperature Data and Snow Characteristics in Northeast China

Snow cover plays an important role in climate, hydrology, and ecosystem. At present, passive microwave remote sensing is the most effective method for monitoring global and regional snow depth (SD). Traditional SD inversion algorithms use empirical or semi-empirical methods to establish a fixed rela...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 14; s. 1
Hlavní autoři:	Wei, Yanlin, Li, Xiaofeng, Gu, Lingjia, Zheng, Ming xing, Jiang, Tao, Li, Xiaojie, Wan, Xiangkun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Attenuation Brightness Brightness temperature Coefficients Dynamic Algorithm Dynamic stability Forestry Heterogeneity Heuristic algorithms Hydrology Metamorphism Microwave emission Microwave theory and techniques Monitoring methods Northeast China Passive Microwave Remote sensing Retrieval Snow Snow cover Snow density Snow depth Snow Depth (SD) Snowpack Surface radiation temperature Surveying Temperature data Temperature differences Temperature gradients Temperature measurement Weather stations China
ISSN:	1939-1404, 2151-1535
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!