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Microwave Indices from Active and Passive Sensors for Remote Sensing Applications
Emanuele Santi and Simonetta Paloscia
2019
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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.
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Keywords
- active microwaves
- AMSR2
- co-pol ratio
- Crops
- Data fusion
- dual-frequency ratios
- harvest
- microwave indices
- microwave radiometry
- Microwaves
- mountain region
- NDVI
- passive microwave
- passive microwave soil moisture
- Polarization
- Radar
- RADARSAT-2
- radiometer
- roughness
- SAR
- scale gap
- scatterometer
- sea ice
- Sentinel-1
- Sentinel-1 and Sentinel-2
- Sentinel-1 backscatter
- SMAP
- smos
- Snow
- snow correlation length
- snow cover characteristics
- Snow Depth and Snow Water Equivalent
- snow water equivalent
- soil moisture
- soil moisture content
- soil moisture downscaling
- soil scattering
- start of season
- start of season, harvest, mountain region
- Terra MODIS
- Time Series Analysis
- vegetation biomass
- vegetation descriptor
- vegetation index
- vegetation water content
- water-cloud model
Links
DOI: 10.3390/books978-3-03897-821-3Editions
