Microwave Indices from Active and Passive Sensors for Remote Sensing Applications

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 i...

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Bibliographic Details
Main Author: Santi, Emanuele (auth)
Other Authors: Paloscia, Simonetta (auth)
Format: Book Chapter
Published: MDPI - Multidisciplinary Digital Publishing Institute 2019
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DOAB: description of the publication
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020 |a books978-3-03897-821-3 
020 |a 9783038978213 
020 |a 9783038978206 
024 7 |a 10.3390/books978-3-03897-821-3  |c doi 
041 0 |a English 
042 |a dc 
100 1 |a Santi, Emanuele  |4 auth 
700 1 |a Paloscia, Simonetta  |4 auth 
245 1 0 |a Microwave Indices from Active and Passive Sensors for Remote Sensing Applications 
260 |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2019 
300 |a 1 electronic resource (224 p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a 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. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-nc-nd/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ 
546 |a English 
653 |a time series analysis 
653 |a passive microwave soil moisture 
653 |a Sentinel-1 and Sentinel-2 
653 |a Snow Depth and Snow Water Equivalent 
653 |a snow cover characteristics 
653 |a vegetation biomass 
653 |a roughness 
653 |a sea ice 
653 |a SMOS 
653 |a microwave radiometry 
653 |a soil moisture downscaling 
653 |a Vegetation Biomass 
653 |a vegetation index 
653 |a Terra MODIS 
653 |a Sentinel-1 
653 |a Microwave Indices 
653 |a soil moisture content 
653 |a dual-frequency ratios 
653 |a SMAP 
653 |a passive microwave 
653 |a water-cloud model 
653 |a snow 
653 |a Sentinel-1 backscatter 
653 |a AMSR2 
653 |a data fusion 
653 |a microwaves 
653 |a mountain region 
653 |a SAR 
653 |a start of season 
653 |a crops 
653 |a NDVI 
653 |a scatterometer 
653 |a Radarsat-2 
653 |a polarization 
653 |a vegetation water content 
653 |a co-pol ratio 
653 |a active microwaves 
653 |a microwave indices 
653 |a harvest 
653 |a Microwave Radiometry 
653 |a soil moisture 
653 |a Soil Moisture Content 
653 |a snow correlation length 
653 |a radiometer 
653 |a radar 
653 |a soil scattering 
653 |a vegetation descriptor 
653 |a scale gap 
653 |a snow water equivalent 
856 4 0 |a www.oapen.org  |u https://mdpi.com/books/pdfview/book/1730  |7 0  |z Get Fullteks 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/53452  |7 0  |z DOAB: description of the publication