TY  - GEN
AU  - Santi,Emanuele
AU  - Paloscia,Simonetta
TI  - Microwave Indices from Active and Passive Sensors for Remote Sensing Applications
SN  - books978-3-03897-821-3
PY  - 2019///
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - time series analysis
KW  - passive microwave soil moisture
KW  - Sentinel-1 and Sentinel-2
KW  - Snow Depth and Snow Water Equivalent
KW  - snow cover characteristics
KW  - vegetation biomass
KW  - roughness
KW  - sea ice
KW  - SMOS
KW  - microwave radiometry
KW  - soil moisture downscaling
KW  - Vegetation Biomass
KW  - vegetation index
KW  - Terra MODIS
KW  - Sentinel-1
KW  - Microwave Indices
KW  - soil moisture content
KW  - dual-frequency ratios
KW  - SMAP
KW  - passive microwave
KW  - water-cloud model
KW  - snow
KW  - Sentinel-1 backscatter
KW  - AMSR2
KW  - data fusion
KW  - microwaves
KW  - mountain region
KW  - SAR
KW  - start of season
KW  - crops
KW  - NDVI
KW  - scatterometer
KW  - Radarsat-2
KW  - polarization
KW  - vegetation water content
KW  - co-pol ratio
KW  - active microwaves
KW  - microwave indices
KW  - harvest
KW  - Microwave Radiometry
KW  - soil moisture
KW  - Soil Moisture Content
KW  - snow correlation length
KW  - radiometer
KW  - radar
KW  - soil scattering
KW  - vegetation descriptor
KW  - scale gap
KW  - snow water equivalent
N1  - Open Access
N2  - Past 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
UR  - https://mdpi.com/books/pdfview/book/1730
UR  - https://directory.doabooks.org/handle/20.500.12854/53452
ER  -