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010   $a9783038978213
010   $a3038978213
024 8 $a10.3390/books978-3-03897-821-3
035   $a(CKB)4100000010106201
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/53452
035   $a(ScCtBLL)5be3c837-a520-4fcc-90d2-3fb8d1d3205c
035   $a(OCoLC)1163809781
035   $a(oapen)doab53452
035   $a(EXLCZ)994100000010106201
100   $a20250203i20192019  uu 
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aMicrowave Indices from Active and Passive Sensors for Remote Sensing Applications$fSimonetta Paloscia, Emanuele Santi
210   $cMDPI - Multidisciplinary Digital Publishing Institute$d2019
210  1$aBasel, Switzerland :$cMDPI,$d2019.
215   $a1 electronic resource (224 p.)
311 08$a9783038978206 
311 08$a3038978205 
330   $aPast research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth's surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices.
606   $aGeography$2bicssc
610   $atime series analysis
610   $apassive microwave soil moisture
610   $aSentinel-1 and Sentinel-2
610   $aSnow Depth and Snow Water Equivalent
610   $asnow cover characteristics
610   $avegetation biomass
610   $aroughness
610   $asea ice
610   $aSMOS
610   $amicrowave radiometry
610   $asoil moisture downscaling
610   $aVegetation Biomass
610   $avegetation index
610   $aTerra MODIS
610   $aSentinel-1
610   $aMicrowave Indices
610   $asoil moisture content
610   $adual-frequency ratios
610   $aSMAP
610   $apassive microwave
610   $awater-cloud model
610   $asnow
610   $aSentinel-1 backscatter
610   $aAMSR2
610   $adata fusion
610   $amicrowaves
610   $amountain region
610   $aSAR
610   $astart of season
610   $acrops
610   $aNDVI
610   $ascatterometer
610   $aRadarsat-2
610   $apolarization
610   $avegetation water content
610   $aco-pol ratio
610   $aactive microwaves
610   $amicrowave indices
610   $aharvest
610   $aMicrowave Radiometry
610   $asoil moisture
610   $aSoil Moisture Content
610   $asnow correlation length
610   $aradiometer
610   $aradar
610   $asoil scattering
610   $avegetation descriptor
610   $ascale gap
610   $asnow water equivalent
615  7$aGeography
700   $aPaloscia$b Simonetta$01787925
702   $aSanti$b Emanuele
801  0$bScCtBLL
801  1$bScCtBLL
906   $aBOOK
912   $a9910367751603321
996   $aMicrowave Indices from Active and Passive Sensors for Remote Sensing Applications$94322004
997   $aUNINA