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000153465 0247_ $$2doi$$a10.1016/j.isprsjprs.2014.02.005
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000153465 1001_ $$0P:(DE-Juel1)143638$$aHasan, Sayeh$$b0$$eCorresponding Author
000153465 245__ $$aSoil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data
000153465 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2014
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000153465 520__ $$aFor the soil moisture retrieval from passive microwave sensors, such as ESA’s Soil Moisture and Ocean Salinity (SMOS) and the NASA Soil Moisture Active and Passive (SMAP) mission, a good knowledge about the vegetation characteristics is indispensable. Vegetation cover is a principal factor in the attenuation, scattering and absorption of the microwave emissions from the soil; and has a direct impact on the brightness temperature by way of its canopy emissions. Here, brightness temperatures were measured at three altitudes across the TERENO (Terrestrial Environmental Observatories) Rur catchment site in Germany to achieve a range of spatial resolutions using the airborne Polarimetric L-band Multibeam Radiometer 2 (PLMR2). The L-band Microwave Emission of the Biosphere (L-MEB) model which simulates microwave emissions from the soil–vegetation layer at L-band was used to retrieve surface soil moisture for all resolutions. A Monte Carlo approach was developed to simultaneously estimate soil moisture and the vegetation parameter b’ describing the relationship between the optical thickness τ and the Leaf Area Index (LAI). LAI was retrieved from multispectral RapidEye imagery and the plant specific vegetation parameter b′ was estimated from the lowest flight altitude data for crop, grass, coniferous forest, and deciduous forest. Mean values of b’ were found to be 0.18, 0.07, 0.26 and 0.23, respectively. By assigning the estimated b′ to higher flight altitude data sets, a high accuracy soil moisture retrieval was achieved with a Root Mean Square Difference (RMSD) of 0.035 m3 m−3 when compared to ground-based measurements.
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000153465 588__ $$aDataset connected to CrossRef, juser.fz-juelich.de
000153465 7001_ $$0P:(DE-Juel1)129506$$aMontzka, Carsten$$b1
000153465 7001_ $$0P:(DE-HGF)0$$aRüdiger, Christoph$$b2
000153465 7001_ $$0P:(DE-Juel1)145515$$aAli, Muhammed$$b3
000153465 7001_ $$0P:(DE-Juel1)129440$$aBogena, Heye$$b4$$ufzj
000153465 7001_ $$0P:(DE-Juel1)129549$$aVereecken, Harry$$b5
000153465 773__ $$0PERI:(DE-600)2012663-3$$a10.1016/j.isprsjprs.2014.02.005$$gVol. 91, p. 59 - 71$$p59 - 71$$tISPRS journal of photogrammetry and remote sensing$$v91$$x0924-2716$$y2014
000153465 8564_ $$uhttps://juser.fz-juelich.de/record/153465/files/FZJ-2014-03063.pdf$$yRestricted$$zPublished final document.
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000153465 9132_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$aDE-HGF$$bMarine, Küsten- und Polare Systeme$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x0
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