001038101 001__ 1038101
001038101 005__ 20250128215419.0
001038101 0247_ $$2doi$$a10.1594/PANGAEA.968754
001038101 037__ $$aFZJ-2025-01148
001038101 1001_ $$0P:(DE-HGF)0$$aFan, Dong$$b0
001038101 245__ $$aA global soil moisture product at 1 km resolution based on Sentinel-1 (2016-2022)
001038101 260__ $$bPANGAEA$$c2025
001038101 3367_ $$2BibTeX$$aMISC
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001038101 3367_ $$2DataCite$$aDataset
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001038101 520__ $$aSoil moisture, although a small fraction of total water content, plays a critical role in the Earth's surface water-heat cycle by influencing processes such as evaporation, infiltration, and vegetation growth and development. Remote sensing has emerged as a critical method for obtaining global-scale soil moisture data. A dual-polarization algorithm (DPA) is proposed and the dual-polarization (VV+VH) observations from the Sentinel-1 C-band synthetic aperture radar are used to generate a global soil moisture dataset with a spatial resolution of 1 km. Due to the observation mode of Sentinel-1, the temporal resolution of this dataset is higher in European and high latitude regions compared to other continents and lower latitude regions. The dataset is provided in raster format, with one set of ascending and one set of descending data for each day, and to ensure data quality, certain areas not suitable for soil moisture retrieval have been excluded, such as water bodies, permanent wetlands, frozen areas, ice and snow covered surfaces, and urban and built-up areas. Feedback and collaboration to improve the dataset is encouraged.
001038101 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x0
001038101 588__ $$aDataset connected to DataCite
001038101 650_7 $$2Other$$a1km spatial resolution
001038101 650_7 $$2Other$$aglobal
001038101 650_7 $$2Other$$aSAR
001038101 650_7 $$2Other$$aSentinel-1
001038101 650_7 $$2Other$$asoil moisture/water content
001038101 650_7 $$2Other$$aBinary Object
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001038101 650_7 $$2Other$$aMATLAB ® - modeling and processing
001038101 650_7 $$2Other$$aModel-Data fusion for understanding Environmental Variability (MoDEV)
001038101 650_7 $$2Other$$aMonitoring and Modelling Climate Change in Water, Energy and Carbon Cycles in the Pan-Third Pole Environment (CLIMATE-Pan-TPE)
001038101 7001_ $$0P:(DE-HGF)0$$aZhao, Tianjie$$b1
001038101 7001_ $$0P:(DE-HGF)0$$aJiang, Xiaoguang$$b2
001038101 7001_ $$0P:(DE-HGF)0$$aGarcía-García, Almudena$$b3
001038101 7001_ $$0P:(DE-HGF)0$$aSchmidt, Toni$$b4
001038101 7001_ $$00000-0002-8449-4428$$aSamaniego, Luis$$b5
001038101 7001_ $$0P:(DE-HGF)0$$aAttinger, Sabine$$b6
001038101 7001_ $$0P:(DE-HGF)0$$aWu, Hua$$b7
001038101 7001_ $$0P:(DE-HGF)0$$aJiang, Yazhen$$b8
001038101 7001_ $$0P:(DE-HGF)0$$aShi, Jiancheng$$b9
001038101 7001_ $$0P:(DE-HGF)0$$aFan, Lei$$b10
001038101 7001_ $$0P:(DE-HGF)0$$aTang, Bohui$$b11
001038101 7001_ $$0P:(DE-HGF)0$$aWagner, Wolfgang$$b12
001038101 7001_ $$00000-0001-8054-7572$$aDorigo, Wouter$$b13
001038101 7001_ $$00000-0002-3280-7023$$aGruber, Alexander$$b14
001038101 7001_ $$0P:(DE-HGF)0$$aMattia, Francesco$$b15
001038101 7001_ $$0P:(DE-HGF)0$$aBalenzano, Anna$$b16
001038101 7001_ $$00000-0002-9080-260X$$aBrocca, Luca$$b17
001038101 7001_ $$0P:(DE-HGF)0$$aJagdhuber, Thomas$$b18
001038101 7001_ $$0P:(DE-HGF)0$$aWigneron, Jean-Pierre$$b19
001038101 7001_ $$0P:(DE-Juel1)129506$$aMontzka, Carsten$$b20
001038101 7001_ $$00000-0002-4071-0512$$aPeng, Jian$$b21
001038101 773__ $$a10.1594/PANGAEA.968754
001038101 909CO $$ooai:juser.fz-juelich.de:1038101$$pVDB
001038101 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129506$$aForschungszentrum Jülich$$b20$$kFZJ
001038101 9131_ $$0G:(DE-HGF)POF4-217$$1G:(DE-HGF)POF4-210$$2G:(DE-HGF)POF4-200$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-2173$$aDE-HGF$$bForschungsbereich Erde und Umwelt$$lErde im Wandel – Unsere Zukunft nachhaltig gestalten$$vFür eine nachhaltige Bio-Ökonomie – von Ressourcen zu Produkten$$x0
001038101 9141_ $$y2025
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001038101 980__ $$aUNRESTRICTED